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Sample records for multiple genetic models

  1. A general framework for the evaluation of genetic association studies using multiple marginal models

    Kitsche, Andreas; Ritz, Christian; Hothorn, Ludwig A.

    2016-01-01

    OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies. METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology...

  2. Estimation in a multiplicative mixed model involving a genetic relationship matrix

    Eccleston John A

    2009-04-01

    Full Text Available Abstract Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

  3. Evaluation of genetically inactivated alpha toxin for protection in multiple mouse models of Staphylococcus aureus infection.

    Rebecca A Brady

    Full Text Available Staphylococcus aureus is a major human pathogen and a leading cause of nosocomial and community-acquired infections. Development of a vaccine against this pathogen is an important goal. While S. aureus protective antigens have been identified in the literature, the majority have only been tested in a single animal model of disease. We wished to evaluate the ability of one S. aureus vaccine antigen to protect in multiple mouse models, thus assessing whether protection in one model translates to protection in other models encompassing the full breadth of infections the pathogen can cause. We chose to focus on genetically inactivated alpha toxin mutant HlaH35L. We evaluated the protection afforded by this antigen in three models of infection using the same vaccine dose, regimen, route of immunization, adjuvant, and challenge strain. When mice were immunized with HlaH35L and challenged via a skin and soft tissue infection model, HlaH35L immunization led to a less severe infection and decreased S. aureus levels at the challenge site when compared to controls. Challenge of HlaH35L-immunized mice using a systemic infection model resulted in a limited, but statistically significant decrease in bacterial colonization as compared to that observed with control mice. In contrast, in a prosthetic implant model of chronic biofilm infection, there was no significant difference in bacterial levels when compared to controls. These results demonstrate that vaccines may confer protection against one form of S. aureus disease without conferring protection against other disease presentations and thus underscore a significant challenge in S. aureus vaccine development.

  4. Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model.

    Furlotte, Nicholas A; Eskin, Eleazar

    2015-05-01

    Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM. Copyright © 2015 by the Genetics Society of America.

  5. Bayesian state space models for dynamic genetic network construction across multiple tissues.

    Liang, Yulan; Kelemen, Arpad

    2016-08-01

    Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

  6. Behavioral phenotypes in schizophrenic animal models with multiple combinations of genetic and environmental factors.

    Hida, Hirotake; Mouri, Akihiro; Noda, Yukihiro

    2013-01-01

    Schizophrenia is a multifactorial psychiatric disorder in which both genetic and environmental factors play a role. Genetic [e.g., Disrupted-in-schizophrenia 1 (DISC1), Neuregulin-1 (NRG1)] and environmental factors (e.g., maternal viral infection, obstetric complications, social stress) may act during the developmental period to increase the incidence of schizophrenia. In animal models, interactions between susceptibility genes and the environment can be controlled in ways not possible in humans; therefore, such models are useful for investigating interactions between or within factors in the pathogenesis and pathophysiology of schizophrenia. We provide an overview of schizophrenic animal models investigating interactions between or within factors. First, we reviewed gene-environment interaction animal models, in which schizophrenic candidate gene mutant mice were subjected to perinatal immune activation or adolescent stress. Next, environment-environment interaction animal models, in which mice were subjected to a combination of perinatal immune activation and adolescent administration of drugs, were described. These animal models showed interaction between or within factors; behavioral changes, which were obscured by each factor, were marked by interaction of factors and vice versa. Appropriate behavioral approaches with such models will be invaluable for translational research on novel compounds, and also for providing insight into the pathogenesis and pathophysiology of schizophrenia.

  7. Genetic variations in multiple myeloma I

    Vangsted, A.; Klausen, T.W.; Vogel, Ulla Birgitte

    2012-01-01

    Few risk factors have been established for the plasma cell disorder multiple myeloma, but some of these like African American ethnicity and a family history of B-cell lymphoproliferative diseases suggest a genetic component for the disease. Genetic variation represents the genetic basis of variab......Few risk factors have been established for the plasma cell disorder multiple myeloma, but some of these like African American ethnicity and a family history of B-cell lymphoproliferative diseases suggest a genetic component for the disease. Genetic variation represents the genetic basis...

  8. Genetic and functional analyses of SHANK2 mutations suggest a multiple hit model of autism spectrum disorders.

    Claire S Leblond

    2012-02-01

    Full Text Available Autism spectrum disorders (ASD are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls. We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4% patients and in 16 of 1,090 (1.5% controls (P = 0.004, OR = 2.37, 95% CI = 1.23-4.70. In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013. Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11-q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the "multiple hit model" for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD.

  9. Genetic variants and multiple myeloma risk

    Martino, Alessandro; Campa, Daniele; Jurczyszyn, Artur

    2014-01-01

    BACKGROUND: Genetic background plays a role in multiple myeloma susceptibility. Several single-nucleotide polymorphisms (SNP) associated with genetic susceptibility to multiple myeloma were identified in the last years, but only a few of them were validated in independent studies. METHODS...... with multiple myeloma risk (P value range, 0.055-0.981), possibly with the exception of the SNP rs2227667 (SERPINE1) in women. CONCLUSIONS: We can exclude that the selected polymorphisms are major multiple myeloma risk factors. IMPACT: Independent validation studies are crucial to identify true genetic risk...

  10. Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium

    Pierre Coenraets

    1997-01-01

    Full Text Available Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (covariance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires estimated with the single-trait and multiple-trait models were over .98 (.99 in fat yield and over .99 (.99 in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1% in milk yield, 6% (3% in fat yield, and .4% (.2% in protein yield for cows (for sires. Relative genetic gains were 3% (1%, 6% (2% and .5% (.2% respectively in milk, fat and protein yields for cows (for sires. The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods.

  11. Improvement in genetic evaluation of female fertility in dairy cattle using multiple-trait models including milk production traits

    Sun, C; Madsen, P; Lund, M S

    2010-01-01

    This study investigated the improvement in genetic evaluation of fertility traits by using production traits as secondary traits (MILK = 305-d milk yield, FAT = 305-d fat yield, and PROT = 305-d protein yield). Data including 471,742 records from first lactations of Denmark Holstein cows, covering...... the years of inseminations during first lactations from 1995 to 2004, were analyzed. Six fertility traits (i.e., interval in days from calving to first insemination, calving interval, days open, interval in days from first to last insemination, numbers of inseminations per conception, and nonreturn rate...... stability and predictive ability than single-trait models for all the fertility traits, except for nonreturn rate within 56 d after first service. The stability and predictive ability for the model including MILK or PROT were similar to the model including all 3 milk production traits and better than...

  12. Genetic and Functional Analyses of SHANK2 Mutations Suggest a Multiple Hit Model of Autism Spectrum Disorders

    Leblond, Claire S.; Heinrich, Jutta; Delorme, Richard; Proepper, Christian; Betancur, Catalina; Huguet, Guillaume; Konyukh, Marina; Chaste, Pauline; Ey, Elodie; Rastam, Maria; Anckarsäter, Henrik; Nygren, Gudrun; Gillberg, I. Carina; Melke, Jonas; Toro, Roberto; Regnault, Beatrice; Fauchereau, Fabien; Mercati, Oriane; Lemière, Nathalie; Skuse, David; Poot, Martin; Holt, Richard; Monaco, Anthony P.; Järvelä, Irma; Kantojärvi, Katri; Vanhala, Raija; Curran, Sarah; Collier, David A.; Bolton, Patrick; Chiocchetti, Andreas; Klauck, Sabine M.; Poustka, Fritz; Freitag, Christine M.; Waltes, Regina; Kopp, Marnie; Duketis, Eftichia; Bacchelli, Elena; Minopoli, Fiorella; Ruta, Liliana; Battaglia, Agatino; Mazzone, Luigi; Maestrini, Elena; Sequeira, Ana F.; Oliveira, Barbara; Vicente, Astrid; Oliveira, Guiomar; Pinto, Dalila; Scherer, Stephen W.; Zelenika, Diana; Delepine, Marc; Lathrop, Mark; Bonneau, Dominique; Guinchat, Vincent; Devillard, Françoise; Assouline, Brigitte; Mouren, Marie-Christine; Leboyer, Marion; Gillberg, Christopher; Boeckers, Tobias M.; Bourgeron, Thomas

    2012-01-01

    Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls). We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4%) patients and in 16 of 1,090 (1.5%) controls (P = 0.004, OR = 2.37, 95% CI = 1.23–4.70). In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013). Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11–q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the “multiple hit model” for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD. PMID:22346768

  13. A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

    García-Gómez, Mónica L; Azpeitia, Eugenio; Álvarez-Buylla, Elena R

    2017-04-01

    The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results

  14. A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

    Mónica L García-Gómez

    2017-04-01

    Full Text Available The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell

  15. Genetic Algorithms for Multiple-Choice Problems

    Aickelin, Uwe

    2010-04-01

    This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems.It shows that such information can significantly enhance performance, but that the choice of information and the way it is included are important factors for success.Two multiple-choice problems are considered.The first is constructing a feasible nurse roster that considers as many requests as possible.In the second problem, shops are allocated to locations in a mall subject to constraints and maximising the overall income.Genetic algorithms are chosen for their well-known robustness and ability to solve large and complex discrete optimisation problems.However, a survey of the literature reveals room for further research into generic ways to include constraints into a genetic algorithm framework.Hence, the main theme of this work is to balance feasibility and cost of solutions.In particular, co-operative co-evolution with hierarchical sub-populations, problem structure exploiting repair schemes and indirect genetic algorithms with self-adjusting decoder functions are identified as promising approaches.The research starts by applying standard genetic algorithms to the problems and explaining the failure of such approaches due to epistasis.To overcome this, problem-specific information is added in a variety of ways, some of which are designed to increase the number of feasible solutions found whilst others are intended to improve the quality of such solutions.As well as a theoretical discussion as to the underlying reasons for using each operator,extensive computational experiments are carried out on a variety of data.These show that the indirect approach relies less on problem structure and hence is easier to implement and superior in solution quality.

  16. On coding genotypes for genetic markers with multiple alleles in genetic association study of quantitative traits

    Wang Tao

    2011-09-01

    Full Text Available Abstract Background In genetic association study of quantitative traits using F∞ models, how to code the marker genotypes and interpret the model parameters appropriately is important for constructing hypothesis tests and making statistical inferences. Currently, the coding of marker genotypes in building F∞ models has mainly focused on the biallelic case. A thorough work on the coding of marker genotypes and interpretation of model parameters for F∞ models is needed especially for genetic markers with multiple alleles. Results In this study, we will formulate F∞ genetic models under various regression model frameworks and introduce three genotype coding schemes for genetic markers with multiple alleles. Starting from an allele-based modeling strategy, we first describe a regression framework to model the expected genotypic values at given markers. Then, as extension from the biallelic case, we introduce three coding schemes for constructing fully parameterized one-locus F∞ models and discuss the relationships between the model parameters and the expected genotypic values. Next, under a simplified modeling framework for the expected genotypic values, we consider several reduced one-locus F∞ models from the three coding schemes on the estimability and interpretation of their model parameters. Finally, we explore some extensions of the one-locus F∞ models to two loci. Several fully parameterized as well as reduced two-locus F∞ models are addressed. Conclusions The genotype coding schemes provide different ways to construct F∞ models for association testing of multi-allele genetic markers with quantitative traits. Which coding scheme should be applied depends on how convenient it can provide the statistical inferences on the parameters of our research interests. Based on these F∞ models, the standard regression model fitting tools can be used to estimate and test for various genetic effects through statistical contrasts with the

  17. Feature extraction from multiple data sources using genetic programming.

    Szymanski, J. J. (John J.); Brumby, Steven P.; Pope, P. A. (Paul A.); Eads, D. R. (Damian R.); Galassi, M. C. (Mark C.); Harvey, N. R. (Neal R.); Perkins, S. J. (Simon J.); Porter, R. B. (Reid B.); Theiler, J. P. (James P.); Young, A. C. (Aaron Cody); Bloch, J. J. (Jeffrey J.); David, N. A. (Nancy A.); Esch-Mosher, D. M. (Diana M.)

    2002-01-01

    Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

  18. A yeast screening system for simultaneously monitoring multiple genetic endpoints

    Dixon, M.L.; Mortimer, R.K.

    1986-01-01

    Mutation, recombination, and mitochondrial deficiencies have been proposed to have roles in the carcinogenic process. The authors describe a diploid strain of the yeast Saccharomyces cerevisiae capable of detecting this wide spectrum of genetic changes. The markers used for monitoring these events have been especially well characterized genetically. Ultraviolet light was chosen as a model carcinogenic agent to test this system. In addition to highly significant increases in the frequencies of each genetic change, increases in the absolute numbers of each change indicated induction and not selective survival. The relative amounts of each type of genetic change varied with dose. The wide spectrum of endpoints monitored in the XD83 yeast system may allow the detection of certain carcinogens and other genetically toxic agents which have escaped detection in more limited systems. Since only one strain is required to simultaneously monitor these genetic changes, this assay system should facilitate comparisons of the induced changes and be more efficient than using multiple strains to monitor the same endpoints. (Auth.)

  19. Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

    He, Dan; Kuhn, David; Parida, Laxmi

    2016-06-15

    Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

  20. Genetic background can result in a marked or minimal effect of gene knockout (GPR55 and CB2 receptor in experimental autoimmune encephalomyelitis models of multiple sclerosis.

    Sofia Sisay

    Full Text Available Endocannabinoids and some phytocannabinoids bind to CB1 and CB2 cannabinoid receptors, transient receptor potential vanilloid one (TRPV1 receptor and the orphan G protein receptor fifty-five (GPR55. Studies using C57BL/10 and C57BL/6 (Cnr2 (tm1Zim CB2 cannabinoid receptor knockout mice have demonstrated an immune-augmenting effect in experimental autoimmune encephalomyelitis (EAE models of multiple sclerosis. However, other EAE studies in Biozzi ABH mice often failed to show any treatment effect of either CB2 receptor agonism or antagonism on inhibition of T cell autoimmunity. The influence of genetic background on the induction of EAE in endocannabinoid system-related gene knockout mice was examined. It was found that C57BL/6.GPR55 knockout mice developed less severe disease, notably in female mice, following active induction with myelin oligodendrocyte glycoprotein 35-55 peptide. In contrast C57BL/6.CB2 (Cnr2 (Dgen receptor knockout mice developed augmented severity of disease consistent with the genetically and pharmacologically-distinct, Cnr2 (tm1Zim mice. However, when the knockout gene was bred into the ABH mouse background and EAE induced with spinal cord autoantigens the immune-enhancing effect of CB2 receptor deletion was lost. Likewise CB1 receptor and transient receptor potential vanilloid one knockout mice on the ABH background demonstrated no alteration in immune-susceptibility, in terms of disease incidence and severity of EAE, in contrast to that reported in some C57BL/6 mouse studies. Furthermore the immune-modulating influence of GPR55 was marginal on the ABH mouse background. Whilst sedative doses of tetrahydrocannabinol could induce immunosuppression, this was associated with a CB1 receptor rather than a CB2 receptor-mediated effect. These data support the fact that non-psychoactive doses of medicinal cannabis have a marginal influence on the immune response in MS. Importantly, it adds a note of caution for the translational

  1. Graphical models for genetic analyses

    Lauritzen, Steffen Lilholt; Sheehan, Nuala A.

    2003-01-01

    This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas...... of graphical models and genetics. The potential of graphical models is explored and illustrated through a number of example applications where the genetic element is substantial or dominating....

  2. Genetic variations in multiple myeloma II

    Vangsted, A.; Klausen, T.W.; Vogel, U.

    2012-01-01

    Association studies on genetic variation to treatment effect may serve as a predictive marker for effect of treatment and can also uncover biological pathways behind drug effect. Single-nucleotide polymorphisms (SNPs) have been studied in relation to high-dose treatment (HDT), thalidomide- and bo...

  3. Genetics Home Reference: multiple epiphyseal dysplasia

    ... Hamel BC, Spranger J, Zabel B, Cohn DH, Cole WG, Hecht JT, Superti-Furga A. Recessive multiple ... medicine? What is newborn screening? New Pages Lyme disease Fibromyalgia White-Sutton syndrome All New & Updated Pages ...

  4. The multiple genetic causes of central hypothyroidism.

    Persani, Luca; Bonomi, Marco

    2017-03-01

    An insufficient stimulation by thyrotropin (TSH) of an otherwise normal thyroid gland represents the cause of Central Hypothyrodism (CeH). CeH is about 1000-folds rarer than Primary Hypothyroidism and often represents a real challenge for the clinicians, mainly because they cannot rely on adequately sensitive parameters for diagnosis or management, as it occurs with circulating TSH in PH. Therefore, CeH diagnosis can be frequently missed or delayed in patients with a previously unknown pituitary involvement. A series of genetic defects have been described to account for isolated CeH or combined pituitary hormone defects (CPHDs) with variable clinical characteristics and degrees of severity. The recently identified candidate gene IGSF1 appears frequently involved. This review provides an updated illustration of the different genetic defects accounting for CeH. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Geometrical model of multiple production

    Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

    1988-01-01

    The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

  6. Evolutionary genetics: the Drosophila model

    Unknown

    Evolutionary genetics straddles the two fundamental processes of life, ... of the genus Drosophila have been used extensively as model systems in experimental ... issue will prove interesting, informative and thought-provoking for both estab-.

  7. Behavior genetics: Bees as model

    Nates Parra, Guiomar

    2011-01-01

    The honeybee Apis mellifera (Apidae) is a model widely used in behavior because of its elaborate social life requiring coordinate actions among the members of the society. Within a colony, division of labor, the performance of tasks by different individuals, follows genetically determined physiological changes that go along with aging. Modern advances in tools of molecular biology and genomics, as well as the sequentiation of A. mellifera genome, have enabled a better understanding of honeybee behavior, in particular social behavior. Numerous studies show that aspects of worker behavior are genetically determined, including defensive, hygienic, reproductive and foraging behavior. For example, genetic diversity is associated with specialization to collect water, nectar and pollen. Also, control of worker reproduction is associated with genetic differences. In this paper, I review the methods and the main results from the study of the genetic and genomic basis of some behaviors in bees.

  8. Multiple-trait genetic evaluation using genomic matrix

    Jane

    2011-07-06

    Jul 6, 2011 ... relationships was estimated through computer simulation and was compared with the accuracy of ... programs, detect animals with superior genetic and select ... genomic matrices in the mixed model equations of BLUP.

  9. Population genetics models of local ancestry.

    Gravel, Simon

    2012-06-01

    Migrations have played an important role in shaping the genetic diversity of human populations. Understanding genomic data thus requires careful modeling of historical gene flow. Here we consider the effect of relatively recent population structure and gene flow and interpret genomes of individuals that have ancestry from multiple source populations as mosaics of segments originating from each population. This article describes general and tractable models for local ancestry patterns with a focus on the length distribution of continuous ancestry tracts and the variance in total ancestry proportions among individuals. The models offer improved agreement with Wright-Fisher simulation data when compared to the state-of-the art and can be used to infer time-dependent migration rates from multiple populations. Considering HapMap African-American (ASW) data, we find that a model with two distinct phases of "European" gene flow significantly improves the modeling of both tract lengths and ancestry variances.

  10. Testing the structure of a hydrological model using Genetic Programming

    Selle, Benny; Muttil, Nitin

    2011-01-01

    SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  11. Testing the Structure of Hydrological Models using Genetic Programming

    Selle, B.; Muttil, N.

    2009-04-01

    Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  12. A Hybrid Genetic Algorithm for the Multiple Crossdocks Problem

    Zhaowei Miao

    2012-01-01

    Full Text Available We study a multiple crossdocks problem with supplier and customer time windows, where any violation of time windows will incur a penalty cost and the flows through the crossdock are constrained by fixed transportation schedules and crossdock capacities. We prove this problem to be NP-hard in the strong sense and therefore focus on developing efficient heuristics. Based on the problem structure, we propose a hybrid genetic algorithm (HGA integrating greedy technique and variable neighborhood search method to solve the problem. Extensive experiments under different scenarios were conducted, and results show that HGA outperforms CPLEX solver, providing solutions in realistic timescales.

  13. Uncovering the genetic landscape for multiple sleep-wake traits.

    Christopher J Winrow

    Full Text Available Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci. While many (28 QTL affected a particular sleep-wake trait (e.g., amount of wake across the full 24-hr day, other loci only affected a trait in the light or dark period while some loci had opposite effects on the trait during the light vs. dark. Analysis of a dataset for multiple sleep-wake traits led to previously undetected interactions (including the differential genetic control of number and duration of REM bouts, as well as possible shared genetic regulatory mechanisms for seemingly different unrelated sleep-wake traits (e.g., number of arousals and REM latency. Construction of a Bayesian network for sleep-wake traits and loci led to the identification of sub-networks of linkage not detectable in smaller data sets or limited single-trait analyses. For example, the network analyses revealed a novel chain of causal relationships between the chromosome 17@29cM QTL, total amount of wake, and duration of wake bouts in both light and dark periods that implies a mechanism whereby overall sleep need, mediated by this locus, in turn determines the length of each wake bout. Taken together, the present results reveal a complex genetic landscape underlying multiple sleep-wake traits

  14. The effect of multiple paternity on genetic diversity of small populations during and after colonisation.

    Marina Rafajlović

    Full Text Available Genetic variation within and among populations is influenced by the genetic content of the founders and the migrants following establishment. This is particularly true if populations are small, migration rate low and habitats arranged in a stepping-stone fashion. Under these circumstances the level of multiple paternity is critical since multiply mated females bring more genetic variation into founder groups than single mated females. One such example is the marine snail Littorina saxatilis that during postglacial times has invaded mainland refuge areas and thereafter small islands emerging due to isostatic uplift by occasional rafting of multiply mated females. We modelled effects of varying degrees of multiple paternity on the genetic variation of island populations colonised by the founders spreading from the mainland, by quantifying the population heterozygosity during both the transient colonisation process, and after a steady state (with migration has been reached. During colonisation, multiple mating by [Formula: see text] males increased the heterozygosity by [Formula: see text] in comparison with single paternity, while in the steady state the increase was [Formula: see text] compared with single paternity. In the steady state the increase of heterozygosity due to multiple paternity is determined by a corresponding increase in effective population size. During colonisation, by contrast, the increase in heterozygosity is larger and it cannot be explained in terms of the effective population size alone. During the steady-state phase bursts of high genetic variation spread through the system, and far from the mainland this led to short periods of high diversity separated by long periods of low diversity. The size of these fluctuations was boosted by multiple paternity. We conclude that following glacial periods of extirpation, recolonization of isolated habitats by this species has been supported by its high level of multiple paternity.

  15. The Effect of Multiple Paternity on Genetic Diversity of Small Populations during and after Colonisation

    Rafajlović, Marina

    2013-10-28

    Genetic variation within and among populations is influenced by the genetic content of the founders and the migrants following establishment. This is particularly true if populations are small, migration rate low and habitats arranged in a stepping-stone fashion. Under these circumstances the level of multiple paternity is critical since multiply mated females bring more genetic variation into founder groups than single mated females. One such example is the marine snail Littorina saxatilis that during postglacial times has invaded mainland refuge areas and thereafter small islands emerging due to isostatic uplift by occasional rafting of multiply mated females. We modelled effects of varying degrees of multiple paternity on the genetic variation of island populations colonised by the founders spreading from the mainland, by quantifying the population heterozygosity during both the transient colonisation process, and after a steady state (with migration) has been reached. During colonisation, multiple mating by 2-10 males increased the heterozygosity by 10-300% in comparison with single paternity, while in the steady state the increase was 10-50% compared with single paternity. In the steady state the increase of heterozygosity due to multiple paternity is determined by a corresponding increase in effective population size. During colonisation, by contrast, the increase in heterozygosity is larger and it cannot be explained in terms of the effective population size alone. During the steady-state phase bursts of high genetic variation spread through the system, and far from the mainland this led to short periods of high diversity separated by long periods of low diversity. The size of these fluctuations was boosted by multiple paternity. We conclude that following glacial periods of extirpation, recolonization of isolated habitats by this species has been supported by its high level of multiple paternity. 2013 Rafajlovi? et al.

  16. Multiple Genetic Associations with Irish Wolfhound Dilated Cardiomyopathy.

    Simpson, Siobhan; Dunning, Mark D; Brownlie, Serena; Patel, Janika; Godden, Megan; Cobb, Malcolm; Mongan, Nigel P; Rutland, Catrin S

    2016-01-01

    Cardiac disease is a leading cause of morbidity and mortality in dogs and humans, with dilated cardiomyopathy being a large contributor to this. The Irish Wolfhound (IWH) is one of the most commonly affected breeds and one of the few breeds with genetic loci associated with the disease. Mutations in more than 50 genes are associated with human dilated cardiomyopathy (DCM), yet very few are also associated with canine DCM. Furthermore, none of the identified canine loci explain many cases of the disease and previous work has indicated that genotypes at multiple loci may act together to influence disease development. In this study, loci previously associated with DCM in IWH were tested for associations in a new cohort both individually and in combination. We have identified loci significantly associated with the disease individually, but no genotypes individually or in pairs conferred a significantly greater risk of developing DCM than the population risk. However combining three loci together did result in the identification of a genotype which conferred a greater risk of disease than the overall population risk. This study suggests multiple rather than individual genetic factors, cooperating to influence DCM risk in IWH.

  17. Multiple Genetic Associations with Irish Wolfhound Dilated Cardiomyopathy

    Siobhan Simpson

    2016-01-01

    Full Text Available Cardiac disease is a leading cause of morbidity and mortality in dogs and humans, with dilated cardiomyopathy being a large contributor to this. The Irish Wolfhound (IWH is one of the most commonly affected breeds and one of the few breeds with genetic loci associated with the disease. Mutations in more than 50 genes are associated with human dilated cardiomyopathy (DCM, yet very few are also associated with canine DCM. Furthermore, none of the identified canine loci explain many cases of the disease and previous work has indicated that genotypes at multiple loci may act together to influence disease development. In this study, loci previously associated with DCM in IWH were tested for associations in a new cohort both individually and in combination. We have identified loci significantly associated with the disease individually, but no genotypes individually or in pairs conferred a significantly greater risk of developing DCM than the population risk. However combining three loci together did result in the identification of a genotype which conferred a greater risk of disease than the overall population risk. This study suggests multiple rather than individual genetic factors, cooperating to influence DCM risk in IWH.

  18. Genomic multiple sequence alignments: refinement using a genetic algorithm

    Lefkowitz Elliot J

    2005-08-01

    Full Text Available Abstract Background Genomic sequence data cannot be fully appreciated in isolation. Comparative genomics – the practice of comparing genomic sequences from different species – plays an increasingly important role in understanding the genotypic differences between species that result in phenotypic differences as well as in revealing patterns of evolutionary relationships. One of the major challenges in comparative genomics is producing a high-quality alignment between two or more related genomic sequences. In recent years, a number of tools have been developed for aligning large genomic sequences. Most utilize heuristic strategies to identify a series of strong sequence similarities, which are then used as anchors to align the regions between the anchor points. The resulting alignment is globally correct, but in many cases is suboptimal locally. We describe a new program, GenAlignRefine, which improves the overall quality of global multiple alignments by using a genetic algorithm to improve local regions of alignment. Regions of low quality are identified, realigned using the program T-Coffee, and then refined using a genetic algorithm. Because a better COFFEE (Consistency based Objective Function For alignmEnt Evaluation score generally reflects greater alignment quality, the algorithm searches for an alignment that yields a better COFFEE score. To improve the intrinsic slowness of the genetic algorithm, GenAlignRefine was implemented as a parallel, cluster-based program. Results We tested the GenAlignRefine algorithm by running it on a Linux cluster to refine sequences from a simulation, as well as refine a multiple alignment of 15 Orthopoxvirus genomic sequences approximately 260,000 nucleotides in length that initially had been aligned by Multi-LAGAN. It took approximately 150 minutes for a 40-processor Linux cluster to optimize some 200 fuzzy (poorly aligned regions of the orthopoxvirus alignment. Overall sequence identity increased only

  19. Developing robotic behavior using a genetic programming model

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

  20. Multiple depots vehicle routing based on the ant colony with the genetic algorithm

    ChunYing Liu

    2013-09-01

    Full Text Available Purpose: the distribution routing plans of multi-depots vehicle scheduling problem will increase exponentially along with the adding of customers. So, it becomes an important studying trend to solve the vehicle scheduling problem with heuristic algorithm. On the basis of building the model of multi-depots vehicle scheduling problem, in order to improve the efficiency of the multiple depots vehicle routing, the paper puts forward a fusion algorithm on multiple depots vehicle routing based on the ant colony algorithm with genetic algorithm. Design/methodology/approach: to achieve this objective, the genetic algorithm optimizes the parameters of the ant colony algorithm. The fusion algorithm on multiple depots vehicle based on the ant colony algorithm with genetic algorithm is proposed. Findings: simulation experiment indicates that the result of the fusion algorithm is more excellent than the other algorithm, and the improved algorithm has better convergence effective and global ability. Research limitations/implications: in this research, there are some assumption that might affect the accuracy of the model such as the pheromone volatile factor, heuristic factor in each period, and the selected multiple depots. These assumptions can be relaxed in future work. Originality/value: In this research, a new method for the multiple depots vehicle routing is proposed. The fusion algorithm eliminate the influence of the selected parameter by optimizing the heuristic factor, evaporation factor, initial pheromone distribute, and have the strong global searching ability. The Ant Colony algorithm imports cross operator and mutation operator for operating the first best solution and the second best solution in every iteration, and reserves the best solution. The cross and mutation operator extend the solution space and improve the convergence effective and the global ability. This research shows that considering both the ant colony and genetic algorithm

  1. Genetic susceptibility factors for multiple chemical sensitivity revisited

    Berg, Nikolaj Drimer; Rasmussen, Henrik Berg; Linneberg, Allan

    2010-01-01

    of this study was to investigate genetic susceptibility factors for MCS and self-reported chemical sensitivity in a population sample. Ninety six MCS patients and 1,207 controls from a general population divided into four severity groups of chemical sensitivity were genotyped for variants in the genes encoding......Multiple chemical sensitivity (MCS) is characterised by adverse effects due to exposure to low levels of chemical substances. Various genes, especially genes of importance to the metabolism of xenobiotic compounds, have been associated with MCS, but findings are inconsistent. The purpose...... significant (OR=1.2, p=0.28). Fast arylamine N-acetyltransferase 2 metaboliser status was associated with severity of chemical sensitivity only in the most severely affected group in the population sample (OR=3.1, p=0.04). The cholecystokinin 2 receptor allele with 21 CT repeats was associated with MCS when...

  2. Structural model analysis of multiple quantitative traits.

    Renhua Li

    2006-07-01

    Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

  3. Genetic evidence of multiple loci in dystocia - difficult labour

    Westgren Magnus

    2010-06-01

    Full Text Available Abstract Background Dystocia, difficult labour, is a common but also complex problem during childbirth. It can be attributed to either weak contractions of the uterus, a large infant, reduced capacity of the pelvis or combinations of these. Previous studies have indicated that there is a genetic component in the susceptibility of experiencing dystocia. The purpose of this study was to identify susceptibility genes in dystocia. Methods A total of 104 women in 47 families were included where at least two sisters had undergone caesarean section at a gestational length of 286 days or more at their first delivery. Study of medical records and a telephone interview was performed to identify subjects with dystocia. Whole-genome scanning using Affymetrix genotyping-arrays and non-parametric linkage (NPL analysis was made in 39 women exhibiting the phenotype of dystocia from 19 families. In 68 women re-sequencing was performed of candidate genes showing suggestive linkage: oxytocin (OXT on chromosome 20 and oxytocin-receptor (OXTR on chromosome 3. Results We found a trend towards linkage with suggestive NPL-score (3.15 on chromosome 12p12. Suggestive linkage peaks were observed on chromosomes 3, 4, 6, 10, 20. Re-sequencing of OXT and OXTR did not reveal any causal variants. Conclusions Dystocia is likely to have a genetic component with variations in multiple genes affecting the patient outcome. We found 6 loci that could be re-evaluated in larger patient cohorts.

  4. Genetic evidence of multiple loci in dystocia - difficult labour

    2010-01-01

    Background Dystocia, difficult labour, is a common but also complex problem during childbirth. It can be attributed to either weak contractions of the uterus, a large infant, reduced capacity of the pelvis or combinations of these. Previous studies have indicated that there is a genetic component in the susceptibility of experiencing dystocia. The purpose of this study was to identify susceptibility genes in dystocia. Methods A total of 104 women in 47 families were included where at least two sisters had undergone caesarean section at a gestational length of 286 days or more at their first delivery. Study of medical records and a telephone interview was performed to identify subjects with dystocia. Whole-genome scanning using Affymetrix genotyping-arrays and non-parametric linkage (NPL) analysis was made in 39 women exhibiting the phenotype of dystocia from 19 families. In 68 women re-sequencing was performed of candidate genes showing suggestive linkage: oxytocin (OXT) on chromosome 20 and oxytocin-receptor (OXTR) on chromosome 3. Results We found a trend towards linkage with suggestive NPL-score (3.15) on chromosome 12p12. Suggestive linkage peaks were observed on chromosomes 3, 4, 6, 10, 20. Re-sequencing of OXT and OXTR did not reveal any causal variants. Conclusions Dystocia is likely to have a genetic component with variations in multiple genes affecting the patient outcome. We found 6 loci that could be re-evaluated in larger patient cohorts. PMID:20587075

  5. Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

    Jia, Yi; Jannink, Jean-Luc

    2012-01-01

    Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and tested in practical breeding programs. In this study, three multivariate linear models (i.e., GBLUP, BayesA, and BayesCπ) were presented and compared to univariate models using simulated and real quantitative traits controlled by different genetic architectures. We also extended BayesA with fixed hyperparameters to a full hierarchical model that estimated hyperparameters and BayesCπ to impute missing phenotypes. We found that optimal marker-effect variance priors depended on the genetic architecture of the trait so that estimating them was beneficial. We showed that the prediction accuracy for a low-heritability trait could be significantly increased by multivariate genomic selection when a correlated high-heritability trait was available. Further, multiple-trait genomic selection had higher prediction accuracy than single-trait genomic selection when phenotypes are not available on all individuals and traits. Additional factors affecting the performance of multiple-trait genomic selection were explored. PMID:23086217

  6. Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients

    James, Tojo; Lindé n, Magdalena; Morikawa, Hiromasa; Fernandes, Sunjay Jude; Ruhrmann, Sabrina; Huss, Mikael; Brandi, Maya; Piehl, Fredrik; Jagodic, Maja; Tegner, Jesper; Khademi, Mohsen; Olsson, Tomas; Gomez-Cabrero, David; Kockum, Ingrid

    2018-01-01

    Despite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as Multiple Sclerosis (MS

  7. Multiple models for Rosaceae genomics.

    Shulaev, Vladimir; Korban, Schuyler S; Sosinski, Bryon; Abbott, Albert G; Aldwinckle, Herb S; Folta, Kevin M; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M; Lewers, Kim; Brown, Susan K; Davis, Thomas M; Gardiner, Susan E; Potter, Daniel; Veilleux, Richard E

    2008-07-01

    The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement.

  8. Multiple Indicator Stationary Time Series Models.

    Sivo, Stephen A.

    2001-01-01

    Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

  9. Genetic and infectious profiles of Japanese multiple sclerosis patients.

    Satoshi Yoshimura

    Full Text Available BACKGROUND: Nationwide surveys conducted in Japan over the past thirty years have revealed a four-fold increase in the estimated number of multiple sclerosis (MS patients, a decrease in the age at onset, and successive increases in patients with conventional MS, which shows an involvement of multiple sites in the central nervous system, including the cerebrum and cerebellum. We aimed to clarify whether genetic and infectious backgrounds correlate to distinct disease phenotypes of MS in Japanese patients. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed HLA-DRB1 and -DPB1 alleles, and IgG antibodies specific for Helicobacter pylori, Chlamydia pneumoniae, varicella zoster virus, and Epstein-Barr virus nuclear antigen (EBNA in 145 MS patients and 367 healthy controls (HCs. Frequencies of DRB1*0405 and DPB1*0301 were significantly higher, and DRB1*0901 and DPB1*0401 significantly lower, in MS patients as compared with HCs. MS patients with DRB1*0405 had a significantly earlier age of onset and lower Progression Index than patients without this allele. The proportion and absolute number of patients with DRB1*0405 successively increased with advancing year of birth. In MS patients without DRB1*0405, the frequency of the DRB1*1501 allele was significantly higher, while the DRB1*0901 allele was significantly lower, compared with HCs. Furthermore, DRB1*0405-negative MS patients were significantly more likely to be positive for EBNA antibodies compared with HCs. CONCLUSIONS: Our study suggests that MS patients harboring DRB1*0405, a genetic risk factor for MS in the Japanese population, have a younger age at onset and a relatively benign disease course, while DRB1*0405-negative MS patients have features similar to Western-type MS in terms of association with Epstein-Barr virus infection and DRB1*1501. The recent increase of MS in young Japanese people may be caused, in part, by an increase in DRB1*0405-positive MS patients.

  10. Modeling Multiple Causes of Carcinogenesis

    Jones, T D

    1999-01-24

    An array of epidemiological results and databases on test animal indicate that risk of cancer and atherosclerosis can be up- or down-regulated by diet through a range of 200%. Other factors contribute incrementally and include the natural terrestrial environment and various human activities that jointly produce complex exposures to endotoxin-producing microorganisms, ionizing radiations, and chemicals. Ordinary personal habits and simple physical irritants have been demonstrated to affect the immune response and risk of disease. There tends to be poor statistical correlation of long-term risk with single agent exposures incurred throughout working careers. However, Agency recommendations for control of hazardous exposures to humans has been substance-specific instead of contextually realistic even though there is consistent evidence for common mechanisms of toxicological and carcinogenic action. That behavior seems to be best explained by molecular stresses from cellular oxygen metabolism and phagocytosis of antigenic invasion as well as breakdown of normal metabolic compounds associated with homeostatic- and injury-related renewal of cells. There is continually mounting evidence that marrow stroma, comprised largely of monocyte-macrophages and fibroblasts, is important to phagocytic and cytokinetic response, but the complex action of the immune process is difficult to infer from first-principle logic or biomarkers of toxic injury. The many diverse database studies all seem to implicate two important processes, i.e., the univalent reduction of molecular oxygen and breakdown of aginuine, an amino acid, by hydrolysis or digestion of protein which is attendant to normal antigen-antibody action. This behavior indicates that protection guidelines and risk coefficients should be context dependent to include reference considerations of the composite action of parameters that mediate oxygen metabolism. A logic of this type permits the realistic common-scale modeling of

  11. Class II HLA interactions modulate genetic risk for multiple sclerosis

    Dilthey, Alexander T; Xifara, Dionysia K; Ban, Maria; Shah, Tejas S; Patsopoulos, Nikolaos A; Alfredsson, Lars; Anderson, Carl A; Attfield, Katherine E; Baranzini, Sergio E; Barrett, Jeffrey; Binder, Thomas M C; Booth, David; Buck, Dorothea; Celius, Elisabeth G; Cotsapas, Chris; D’Alfonso, Sandra; Dendrou, Calliope A; Donnelly, Peter; Dubois, Bénédicte; Fontaine, Bertrand; Fugger, Lars; Goris, An; Gourraud, Pierre-Antoine; Graetz, Christiane; Hemmer, Bernhard; Hillert, Jan; Kockum, Ingrid; Leslie, Stephen; Lill, Christina M; Martinelli-Boneschi, Filippo; Oksenberg, Jorge R; Olsson, Tomas; Oturai, Annette; Saarela, Janna; Søndergaard, Helle Bach; Spurkland, Anne; Taylor, Bruce; Winkelmann, Juliane; Zipp, Frauke; Haines, Jonathan L; Pericak-Vance, Margaret A; Spencer, Chris C A; Stewart, Graeme; Hafler, David A; Ivinson, Adrian J; Harbo, Hanne F; Hauser, Stephen L; De Jager, Philip L; Compston, Alastair; McCauley, Jacob L; Sawcer, Stephen; McVean, Gil

    2016-01-01

    Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01–HLA-DRB1*15:01 and HLA-DQB1*03:01–HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles. PMID:26343388

  12. The genetic legacy of multiple beaver reintroductions in Central Europe.

    Frosch, Christiane; Kraus, Robert H S; Angst, Christof; Allgöwer, Rainer; Michaux, Johan; Teubner, Jana; Nowak, Carsten

    2014-01-01

    The comeback of the Eurasian beaver (Castor fiber) throughout western and central Europe is considered a major conservation success. Traditionally, several subspecies are recognised by morphology and mitochondrial haplotype, each linked to a relict population. During various reintroduction programs in the 20th century, beavers from multiple source localities were released and now form viable populations. These programs differed in their reintroduction strategies, i.e., using pure subspecies vs. mixed source populations. This inhomogeneity in management actions generated ongoing debates regarding the origin of present beaver populations and appropriate management plans for the future. By sequencing of the mitochondrial control region and microsatellite genotyping of 235 beaver individuals from five selected regions in Germany, Switzerland, Luxembourg, and Belgium we show that beavers from at least four source origins currently form admixed, genetically diverse populations that spread across the study region. While regional occurrences of invasive North American beavers (n = 20) were found, all but one C. fiber bore the mitochondrial haplotype of the autochthonous western Evolutionary Significant Unit (ESU). Considering this, as well as the viability of admixed populations and the fact that the fusion of different lineages is already progressing in all studied regions, we argue that admixture between different beaver source populations should be generally accepted.

  13. Eco-genetic modeling of contemporary life-history evolution.

    Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

    2009-10-01

    We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by

  14. Behavior genetic modeling of human fertility

    Rodgers, J L; Kohler, H P; Kyvik, K O

    2001-01-01

    Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (First......Try) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males....... A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry....

  15. Genetic coding and gene expression - new Quadruplet genetic coding model

    Shankar Singh, Rama

    2012-07-01

    Successful demonstration of human genome project has opened the door not only for developing personalized medicine and cure for genetic diseases, but it may also answer the complex and difficult question of the origin of life. It may lead to making 21st century, a century of Biological Sciences as well. Based on the central dogma of Biology, genetic codons in conjunction with tRNA play a key role in translating the RNA bases forming sequence of amino acids leading to a synthesized protein. This is the most critical step in synthesizing the right protein needed for personalized medicine and curing genetic diseases. So far, only triplet codons involving three bases of RNA, transcribed from DNA bases, have been used. Since this approach has several inconsistencies and limitations, even the promise of personalized medicine has not been realized. The new Quadruplet genetic coding model proposed and developed here involves all four RNA bases which in conjunction with tRNA will synthesize the right protein. The transcription and translation process used will be the same, but the Quadruplet codons will help overcome most of the inconsistencies and limitations of the triplet codes. Details of this new Quadruplet genetic coding model and its subsequent potential applications including relevance to the origin of life will be presented.

  16. Analysis of Plasminogen Genetic Variants in Multiple Sclerosis Patients

    A. Dessa Sadovnick

    2016-07-01

    Full Text Available Multiple sclerosis (MS is a prevalent neurological disease of complex etiology. Here, we describe the characterization of a multi-incident MS family that nominated a rare missense variant (p.G420D in plasminogen (PLG as a putative genetic risk factor for MS. Genotyping of PLG p.G420D (rs139071351 in 2160 MS patients, and 886 controls from Canada, identified 10 additional probands, two sporadic patients and one control with the variant. Segregation in families harboring the rs139071351 variant, identified p.G420D in 26 out of 30 family members diagnosed with MS, 14 unaffected parents, and 12 out of 30 family members not diagnosed with disease. Despite considerably reduced penetrance, linkage analysis supports cosegregation of PLG p.G420D and disease. Genotyping of PLG p.G420D in 14446 patients, and 8797 controls from Canada, France, Spain, Germany, Belgium, and Austria failed to identify significant association with disease (P = 0.117, despite an overall higher prevalence in patients (OR = 1.32; 95% CI = 0.93–1.87. To assess whether additional rare variants have an effect on MS risk, we sequenced PLG in 293 probands, and genotyped all rare variants in cases and controls. This analysis identified nine rare missense variants, and although three of them were exclusively observed in MS patients, segregation does not support pathogenicity. PLG is a plausible biological candidate for MS owing to its involvement in immune system response, blood-brain barrier permeability, and myelin degradation. Moreover, components of its activation cascade have been shown to present increased activity or expression in MS patients compared to controls; further studies are needed to clarify whether PLG is involved in MS susceptibility.

  17. Hereditary multiple exostoses: from genetics to clinical syndrome and complications

    Vanhoenacker, Filip M.; Hul, Wim van; Wuyts, Wim; Willems, P.J.; Schepper, Arthur M. de

    2001-12-01

    Objective: To give an overview of genetic, clinical and radiological aspects in two families over four generations with known hereditary multiple exostoses (HME). Methods and material: After linkage analysis in both families to localize the defective gene, mutation analysis was performed in these genes to identify the underlying mutation. In the 31 affected individuals, location, number and morphology and evolution of exostosis, evolution of remodeling defects at the metaphysis, and the extent of possible complications were evaluated on clinical and imaging (plain radiography, computed tomography (CT), and magnetic resonance imaging (MRI)) data over a lifetime period. Results and conclusions: Both families demonstrate the gene defect in the same EXT-2 gene locus on chromosome 11p. Exostoses are preferentially located in the lower extremity (hip, knee and lower leg), humerus, and forearm. Any other bone may be involved, except for the calvaria of the skull and the mandible. Exostoses are rather sessile than pedunculated. Exostosis is rarely present at birth but develops gradually and may persist to grow slowly after closure of the growth plates. Preferential expression of the remodeling defect was seen in the hip, distal femur (trumpet-shaped metaphysis) and forearm (shortening of the ulna with secondary bowing of the radius and development of a pseudo-Madelung deformity). These radiological manifestations start at the age of 4-5 years and become more obvious as the enchondral bone formation progresses with age. Reported complications in these families consist of local entrapment phenomenons (vessel, tendon, nerve), frictional bursitis, and sarcomatous transformation. MRI was able to suggest these complications and is the imaging technique of choice in the evaluation of symptomatic exostoses.

  18. Hereditary multiple exostoses: from genetics to clinical syndrome and complications

    Vanhoenacker, Filip M.; Hul, Wim van; Wuyts, Wim; Willems, P.J.; Schepper, Arthur M. de

    2001-01-01

    Objective: To give an overview of genetic, clinical and radiological aspects in two families over four generations with known hereditary multiple exostoses (HME). Methods and material: After linkage analysis in both families to localize the defective gene, mutation analysis was performed in these genes to identify the underlying mutation. In the 31 affected individuals, location, number and morphology and evolution of exostosis, evolution of remodeling defects at the metaphysis, and the extent of possible complications were evaluated on clinical and imaging (plain radiography, computed tomography (CT), and magnetic resonance imaging (MRI)) data over a lifetime period. Results and conclusions: Both families demonstrate the gene defect in the same EXT-2 gene locus on chromosome 11p. Exostoses are preferentially located in the lower extremity (hip, knee and lower leg), humerus, and forearm. Any other bone may be involved, except for the calvaria of the skull and the mandible. Exostoses are rather sessile than pedunculated. Exostosis is rarely present at birth but develops gradually and may persist to grow slowly after closure of the growth plates. Preferential expression of the remodeling defect was seen in the hip, distal femur (trumpet-shaped metaphysis) and forearm (shortening of the ulna with secondary bowing of the radius and development of a pseudo-Madelung deformity). These radiological manifestations start at the age of 4-5 years and become more obvious as the enchondral bone formation progresses with age. Reported complications in these families consist of local entrapment phenomenons (vessel, tendon, nerve), frictional bursitis, and sarcomatous transformation. MRI was able to suggest these complications and is the imaging technique of choice in the evaluation of symptomatic exostoses

  19. Analysis of Plasminogen Genetic Variants in Multiple Sclerosis Patients

    Sadovnick, A. Dessa; Traboulsee, Anthony L.; Bernales, Cecily Q.; Ross, Jay P.; Forwell, Amanda L.; Yee, Irene M.; Guillot-Noel, Lena; Fontaine, Bertrand; Cournu-Rebeix, Isabelle; Alcina, Antonio; Fedetz, Maria; Izquierdo, Guillermo; Matesanz, Fuencisla; Hilven, Kelly; Dubois, Bénédicte; Goris, An; Astobiza, Ianire; Alloza, Iraide; Antigüedad, Alfredo; Vandenbroeck, Koen; Akkad, Denis A.; Aktas, Orhan; Blaschke, Paul; Buttmann, Mathias; Chan, Andrew; Epplen, Joerg T.; Gerdes, Lisa-Ann; Kroner, Antje; Kubisch, Christian; Kümpfel, Tania; Lohse, Peter; Rieckmann, Peter; Zettl, Uwe K.; Zipp, Frauke; Bertram, Lars; Lill, Christina M; Fernandez, Oscar; Urbaneja, Patricia; Leyva, Laura; Alvarez-Cermeño, Jose Carlos; Arroyo, Rafael; Garagorri, Aroa M.; García-Martínez, Angel; Villar, Luisa M.; Urcelay, Elena; Malhotra, Sunny; Montalban, Xavier; Comabella, Manuel; Berger, Thomas; Fazekas, Franz; Reindl, Markus; Schmied, Mascha C.; Zimprich, Alexander; Vilariño-Güell, Carles

    2016-01-01

    Multiple sclerosis (MS) is a prevalent neurological disease of complex etiology. Here, we describe the characterization of a multi-incident MS family that nominated a rare missense variant (p.G420D) in plasminogen (PLG) as a putative genetic risk factor for MS. Genotyping of PLG p.G420D (rs139071351) in 2160 MS patients, and 886 controls from Canada, identified 10 additional probands, two sporadic patients and one control with the variant. Segregation in families harboring the rs139071351 variant, identified p.G420D in 26 out of 30 family members diagnosed with MS, 14 unaffected parents, and 12 out of 30 family members not diagnosed with disease. Despite considerably reduced penetrance, linkage analysis supports cosegregation of PLG p.G420D and disease. Genotyping of PLG p.G420D in 14446 patients, and 8797 controls from Canada, France, Spain, Germany, Belgium, and Austria failed to identify significant association with disease (P = 0.117), despite an overall higher prevalence in patients (OR = 1.32; 95% CI = 0.93–1.87). To assess whether additional rare variants have an effect on MS risk, we sequenced PLG in 293 probands, and genotyped all rare variants in cases and controls. This analysis identified nine rare missense variants, and although three of them were exclusively observed in MS patients, segregation does not support pathogenicity. PLG is a plausible biological candidate for MS owing to its involvement in immune system response, blood-brain barrier permeability, and myelin degradation. Moreover, components of its activation cascade have been shown to present increased activity or expression in MS patients compared to controls; further studies are needed to clarify whether PLG is involved in MS susceptibility. PMID:27194806

  20. Predictive value of testing for multiple genetic variants in multifactorial

    A.C.J.W. Janssens (Cécile); M.J. Khoury (Muin Joseph)

    2009-01-01

    textabstractMultifactorial diseases such as type 2 diabetes, osteoporosis, and cardiovascular disease are caused by a complex interplay of many genetic and nongenetic factors, each of which conveys a minor increase in the risk of disease. Unraveling the genetic origins of these diseases is

  1. Animal models for human genetic diseases

    Sharif Sons

    The study of human genetic diseases can be greatly aided by animal models because of their similarity .... and gene targeting in embryonic stem cells) has been a powerful tool in .... endonucleases that are designed to make a doublestrand.

  2. THE ALLOMETRIC-AUTOREGRESSIVE MODEL IN GENETIC ...

    The application of an allometric-autoregressive model for the quantification of growth and efficiency of feed utilization for purposes of selection for ... be of value in genetic studies. ... mass) gives a fair indication of the cumulative preweaning.

  3. Complete restoration of multiple dystrophin isoforms in genetically corrected Duchenne muscular dystrophy patient–derived cardiomyocytes

    Susi Zatti

    2014-01-01

    Full Text Available Duchenne muscular dystrophy (DMD–associated cardiac diseases are emerging as a major cause of morbidity and mortality in DMD patients, and many therapies for treatment of skeletal muscle failed to improve cardiac function. The reprogramming of patients' somatic cells into pluripotent stem cells, combined with technologies for correcting the genetic defect, possesses great potential for the development of new treatments for genetic diseases. In this study, we obtained human cardiomyocytes from DMD patient–derived, induced pluripotent stem cells genetically corrected with a human artificial chromosome carrying the whole dystrophin genomic sequence. Stimulation by cytokines was combined with cell culturing on hydrogel with physiological stiffness, allowing an adhesion-dependent maturation and a proper dystrophin expression. The obtained cardiomyocytes showed remarkable sarcomeric organization of cardiac troponin T and α-actinin, expressed cardiac-specific markers, and displayed electrically induced calcium transients lasting less than 1 second. We demonstrated that the human artificial chromosome carrying the whole dystrophin genomic sequence is stably maintained throughout the cardiac differentiation process and that multiple promoters of the dystrophin gene are properly activated, driving expression of different isoforms. These dystrophic cardiomyocytes can be a valuable source for in vitro modeling of DMD-associated cardiac disease. Furthermore, the derivation of genetically corrected, patient-specific cardiomyocytes represents a step toward the development of innovative cell and gene therapy approaches for DMD.

  4. Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

    Avval Zhila Mohajeri

    2015-01-01

    Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

  5. Neurofibromatosis type 1 and multiple sclerosis: Genetically related ...

    Solaf M. Elsayed

    2016-10-25

    Oct 25, 2016 ... a Genetics Unit, Children's Hospital, Ain Shams University, Egypt b Neurology Department ... Through the past 6 months, she started to develop short term memory loss with intact long term memory. There was no other motor ...

  6. Multiplicity Control in Structural Equation Modeling

    Cribbie, Robert A.

    2007-01-01

    Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

  7. Population genetic diversity and fitness in multiple environments

    McGreevy Thomas J

    2010-07-01

    Full Text Available Abstract Background When a large number of alleles are lost from a population, increases in individual homozygosity may reduce individual fitness through inbreeding depression. Modest losses of allelic diversity may also negatively impact long-term population viability by reducing the capacity of populations to adapt to altered environments. However, it is not clear how much genetic diversity within populations may be lost before populations are put at significant risk. Development of tools to evaluate this relationship would be a valuable contribution to conservation biology. To address these issues, we have created an experimental system that uses laboratory populations of an estuarine crustacean, Americamysis bahia with experimentally manipulated levels of genetic diversity. We created replicate cultures with five distinct levels of genetic diversity and monitored them for 16 weeks in both permissive (ambient seawater and stressful conditions (diluted seawater. The relationship between molecular genetic diversity at presumptive neutral loci and population vulnerability was assessed by AFLP analysis. Results Populations with very low genetic diversity demonstrated reduced fitness relative to high diversity populations even under permissive conditions. Population performance decreased in the stressful environment for all levels of genetic diversity relative to performance in the permissive environment. Twenty percent of the lowest diversity populations went extinct before the end of the study in permissive conditions, whereas 73% of the low diversity lines went extinct in the stressful environment. All high genetic diversity populations persisted for the duration of the study, although population sizes and reproduction were reduced under stressful environmental conditions. Levels of fitness varied more among replicate low diversity populations than among replicate populations with high genetic diversity. There was a significant correlation

  8. CMCpy: Genetic Code-Message Coevolution Models in Python

    Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.

    2013-01-01

    Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367

  9. The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks

    2012-01-01

    Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms. PMID:22348705

  10. Natural selection affects multiple aspects of genetic variation at putatively neutral sites across the human genome.

    Lohmueller, Kirk E; Albrechtsen, Anders; Li, Yingrui; Kim, Su Yeon; Korneliussen, Thorfinn; Vinckenbosch, Nicolas; Tian, Geng; Huerta-Sanchez, Emilia; Feder, Alison F; Grarup, Niels; Jørgensen, Torben; Jiang, Tao; Witte, Daniel R; Sandbæk, Annelli; Hellmann, Ines; Lauritzen, Torsten; Hansen, Torben; Pedersen, Oluf; Wang, Jun; Nielsen, Rasmus

    2011-10-01

    A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations.

  11. [Application of Multiple Genetic Markers in a Case of Determination of Half Sibling].

    Yang, Xue; Shi, Mei-sen; Yuan, Li; Lu, Di

    2016-02-01

    A case of half sibling was determined with multiple genetic markers, which could be potentially applied for determination of half sibling relationship from same father. Half sibling relationship was detected by 39 autosomal STR genetic markers, 23 Y-chromosomal STR genetic markers and 12 X -chromosomal STR genetic markers among ZHAO -1, ZHAO -2, ZHAO -3, ZHAO -4, and ZHAO-5. According to autosomal STR, Y-STR and X-STR genotyping results, it was determined that ZHAO-4 (alleged half sibling) was unrelated with ZHAO-1 and ZHAO-2; however, ZHAO-3 (alleged half sibling), ZHAO-5 (alleged half sibling) shared same genetic profile with ZHAO-1, and ZHAO-2 from same father. It is reliable to use multiple genetic markers and family gene reconstruction to determine half sibling relationship from same father, but it is difficult to determination by calculating half sibling index with ITO and discriminant functions.

  12. Genetic diagnosis of a Chinese multiple endocrine neoplasia type ...

    However, different families with MEN 2A due to the same RET mutation often have significant variability inthe clinical exhibition of disease and aggressiveness of the MTC, which implies additional genetic loci exsit beyondRET coding region. Whole genome sequencing (WGS) greatly expands the breadth of screening from ...

  13. Use of multiple genetic markers in prediction of breeding values.

    Arendonk, van J.A.M.; Tier, B.; Kinghorn, B.P.

    1994-01-01

    Genotypes at a marker locus give information on transmission of genes from parents to offspring and that information can be used in predicting the individuals' additive genetic value at a linked quantitative trait locus (MQTL). In this paper a recursive method is presented to build the gametic

  14. Noise in Genetic Toggle Switch Models

    Andrecut M.

    2006-06-01

    Full Text Available In this paper we study the intrinsic noise effect on the switching behavior of a simple genetic circuit corresponding to the genetic toggle switch model. The numerical results obtained from a noisy mean-field model are compared to those obtained from the stochastic Gillespie simulation of the corresponding system of chemical reactions. Our results show that by using a two step reaction approach for modeling the transcription and translation processes one can make the system to lock in one of the steady states for exponentially long times.

  15. Genetics Home Reference: Noonan syndrome with multiple lentigines

    ... of Noonan syndrome with multiple lentigines include brown skin spots called lentigines that are similar to freckles, heart ... individuals may have thousands of small dark brown skin spots by the time they reach puberty. Unlike freckles, ...

  16. Volatile terpenoids: multiple functions, biosynthesis, modulation and manipulation by genetic engineering.

    Abbas, Farhat; Ke, Yanguo; Yu, Rangcai; Yue, Yuechong; Amanullah, Sikandar; Jahangir, Muhammad Muzammil; Fan, Yanping

    2017-11-01

    Terpenoids play several physiological and ecological functions in plant life through direct and indirect plant defenses and also in human society because of their enormous applications in the pharmaceutical, food and cosmetics industries. Through the aid of genetic engineering its role can by magnified to broad spectrum by improving genetic ability of crop plants, enhancing the aroma quality of fruits and flowers and the production of pharmaceutical terpenoids contents in medicinal plants. Terpenoids are structurally diverse and the most abundant plant secondary metabolites, playing an important role in plant life through direct and indirect plant defenses, by attracting pollinators and through different interactions between the plants and their environment. Terpenoids are also significant because of their enormous applications in the pharmaceutical, food and cosmetics industries. Due to their broad distribution and functional versatility, efforts are being made to decode the biosynthetic pathways and comprehend the regulatory mechanisms of terpenoids. This review summarizes the recent advances in biosynthetic pathways, including the spatiotemporal, transcriptional and post-transcriptional regulatory mechanisms. Moreover, we discuss the multiple functions of the terpene synthase genes (TPS), their interaction with the surrounding environment and the use of genetic engineering for terpenoid production in model plants. Here, we also provide an overview of the significance of terpenoid metabolic engineering in crop protection, plant reproduction and plant metabolic engineering approaches for pharmaceutical terpenoids production and future scenarios in agriculture, which call for sustainable production platforms by improving different plant traits.

  17. Beyond clinical utility: The multiple values of DTC genetics

    Mauro Turrini

    2016-03-01

    Full Text Available One point of consensus in the otherwise very controversial discussion about the benefits and dangers of DTC genetics in the health domain is the lack of substantial clinical utility. At the same time, both the empirical and conceptual literature indicate that health-related DTC tests can have value and utility outside of the clinic. We argue that a broader and multi-faceted conceptualization of utility and value would enrich the ethical and social discussion of DTC testing in several ways: First, looking at ways in which DTC testing can have personal and social value for users – in the form of entertainment, learning, or a way to relate to others – can help to explain why people still take DTC tests, and will, further down the line, foster a more nuanced understanding of secondary and tertiary uses of DTC test results (which could very well unearth new ethical and regulatory challenges. Second, considering the economic value and broader utility of DTC testing foregrounds wider social and political aspects than have been dominant in the ethical and regulatory debates surrounding DTC genetics so far. These wider political aspects include the profound power asymmetries that characterize the collection and use of personal genetic data in many contexts.

  18. Design of Xen Hybrid Multiple Police Model

    Sun, Lei; Lin, Renhao; Zhu, Xianwei

    2017-10-01

    Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

  19. Multiple Model Approaches to Modelling and Control,

    on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...

  20. Shaping asteroid models using genetic evolution (SAGE)

    Bartczak, P.; Dudziński, G.

    2018-02-01

    In this work, we present SAGE (shaping asteroid models using genetic evolution), an asteroid modelling algorithm based solely on photometric lightcurve data. It produces non-convex shapes, orientations of the rotation axes and rotational periods of asteroids. The main concept behind a genetic evolution algorithm is to produce random populations of shapes and spin-axis orientations by mutating a seed shape and iterating the process until it converges to a stable global minimum. We tested SAGE on five artificial shapes. We also modelled asteroids 433 Eros and 9 Metis, since ground truth observations for them exist, allowing us to validate the models. We compared the derived shape of Eros with the NEAR Shoemaker model and that of Metis with adaptive optics and stellar occultation observations since other models from various inversion methods were available for Metis.

  1. Neurofibromatosis type 1 and multiple sclerosis: Genetically related ...

    Neurofibromatosis type I (NF1) is an autosomal dominant disorder with involvement of both the cutaneous and nervous systems. Patients are susceptible to neurological complication in the form of tumors of the brain and spinal cord. Multiple sclerosis (MS) is a chronic autoimmune disease that affects the myelinated axons ...

  2. New Genetic Insights and Therapy in Multiple Myeloma

    K.L. Wu

    2007-01-01

    textabstractIn the last decade, several significant advances in myeloma therapy have occurred with the pace of change accelerated with the introduction of new anti-myeloma agents. The approach to the treatment of multiple myeloma has become more complex with an array of therapeutic options,

  3. Multiple Epiphyseal Dysplasia: A Clinical and Molecular Genetic Study

    J.B.A. van Mourik (Jan)

    1998-01-01

    textabstractMultiple epiphyseal dysplasia (MED) is one of the most common osteochondrodysplasias [Wynne-Davies and Gormley 1985]. During childhood and adolescence it affects the epiphyses of the tubular bones, resulting in axial deformities and shorter limbs.·Later in life MED can lead to

  4. Class II HLA interactions modulate genetic risk for multiple sclerosis

    Moutsianas, Loukas; Jostins, Luke; Beecham, Ashley H

    2015-01-01

    Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17...

  5. Genetic models for CNS inflammation

    Owens, T; Wekerle, H; Antel, J

    2001-01-01

    The use of transgenic technology to over-express or prevent expression of genes encoding molecules related to inflammation has allowed direct examination of their role in experimental disease. This article reviews transgenic and knockout models of CNS demyelinating disease, focusing primarily on ...

  6. Multiple model cardinalized probability hypothesis density filter

    Georgescu, Ramona; Willett, Peter

    2011-09-01

    The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

  7. Predictive performance models and multiple task performance

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  8. Model comparisons and genetic and environmental parameter ...

    arc

    Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.

  9. Signal Timing Optimization for Corridors with Multiple Highway-Rail Grade Crossings Using Genetic Algorithm

    Yifeng Chen

    2018-01-01

    Full Text Available Safety and efficiency are two critical issues at highway-rail grade crossings (HRGCs and their nearby intersections. Standard traffic signal optimization programs are not designed to work on roadway networks that contain multiple HRGCs, because their underlying assumption is that the roadway traffic is in a steady-state. During a train event, steady-state conditions do not occur. This is particularly true for corridors that experience high train traffic (e.g., over 2 trains per hour. In this situation, the non-steady-state conditions predominate. This paper develops a simulation-based methodology for optimizing traffic signal timing plan on corridors of this kind. The primary goal is to maximize safety, and the secondary goal is to minimize delay. A Genetic Algorithm (GA was used as the optimization approach in the proposed methodology. A new transition preemption strategy for dual tracks (TPS_DT and a train arrival prediction model were integrated in the proposed methodology. An urban road network with multiple HRGCs in Lincoln, NE, was used as the study network. The microsimulation model VISSIM was used for evaluation purposes and was calibrated to local traffic conditions. A sensitivity analysis with different train traffic scenarios was conducted. It was concluded that the methodology can significantly improve both the safety and efficiency of traffic corridors with HRGCs.

  10. Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

    JingRui Zhang

    2015-03-01

    Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

  11. Restless legs syndrome in Czech patients with multiple sclerosis: An epidemiological and genetic study

    Vávrová, J.; Kemlink, D.; Šonka, K.; Havrdová, E.; Horáková, D.; Pardini, Barbara; Müller-Myhsok, B.; Winkelmann, J.

    2012-01-01

    Roč. 13, č. 7 (2012), s. 848-851 ISSN 1389-9457 R&D Projects: GA MZd NR8563 Grant - others:GA ČR(CZ) GD309/08/H079; GA MZd(CZ) NT12141 Institutional research plan: CEZ:AV0Z50390512 Keywords : Secondary restless legs syndrome * Multiple sclerosis * Genetic association study Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.487, year: 2012

  12. Population genetics of the Eastern Hellbender (Cryptobranchus alleganiensis alleganiensis across multiple spatial scales.

    Shem D Unger

    Full Text Available Conservation genetics is a powerful tool to assess the population structure of species and provides a framework for informing management of freshwater ecosystems. As lotic habitats become fragmented, the need to assess gene flow for species of conservation management becomes a priority. The eastern hellbender (Cryptobranchus alleganiensis alleganiensis is a large, fully aquatic paedamorphic salamander. Many populations are experiencing declines throughout their geographic range, yet the genetic ramifications of these declines are currently unknown. To this end, we examined levels of genetic variation and genetic structure at both range-wide and drainage (hierarchical scales. We collected 1,203 individuals from 77 rivers throughout nine states from June 2007 to August 2011. Levels of genetic diversity were relatively high among all sampling locations. We detected significant genetic structure across populations (Fst values ranged from 0.001 between rivers within a single watershed to 0.218 between states. We identified two genetically differentiated groups at the range-wide scale: 1 the Ohio River drainage and 2 the Tennessee River drainage. An analysis of molecular variance (AMOVA based on landscape-scale sampling of basins within the Tennessee River drainage revealed the majority of genetic variation (∼94-98% occurs within rivers. Eastern hellbenders show a strong pattern of isolation by stream distance (IBSD at the drainage level. Understanding levels of genetic variation and differentiation at multiple spatial and biological scales will enable natural resource managers to make more informed decisions and plan effective conservation strategies for cryptic, lotic species.

  13. Genetic Algorithm Based Microscale Vehicle Emissions Modelling

    Sicong Zhu

    2015-01-01

    Full Text Available There is a need to match emission estimations accuracy with the outputs of transport models. The overall error rate in long-term traffic forecasts resulting from strategic transport models is likely to be significant. Microsimulation models, whilst high-resolution in nature, may have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. At the microlevel, this paper discusses the limitations of existing emissions estimation approaches. Emission models for predicting emission pollutants other than CO2 are proposed. A genetic algorithm approach is adopted to select the predicting variables for the black box model. The approach is capable of solving combinatorial optimization problems. Overall, the emission prediction results reveal that the proposed new models outperform conventional equations in terms of accuracy and robustness.

  14. Application of Multiple Evaluation Models in Brazil

    Rafael Victal Saliba

    2008-07-01

    Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

  15. Genetic demographic networks: Mathematical model and applications.

    Kimmel, Marek; Wojdyła, Tomasz

    2016-10-01

    Recent improvement in the quality of genetic data obtained from extinct human populations and their ancestors encourages searching for answers to basic questions regarding human population history. The most common and successful are model-based approaches, in which genetic data are compared to the data obtained from the assumed demography model. Using such approach, it is possible to either validate or adjust assumed demography. Model fit to data can be obtained based on reverse-time coalescent simulations or forward-time simulations. In this paper we introduce a computational method based on mathematical equation that allows obtaining joint distributions of pairs of individuals under a specified demography model, each of them characterized by a genetic variant at a chosen locus. The two individuals are randomly sampled from either the same or two different populations. The model assumes three types of demographic events (split, merge and migration). Populations evolve according to the time-continuous Moran model with drift and Markov-process mutation. This latter process is described by the Lyapunov-type equation introduced by O'Brien and generalized in our previous works. Application of this equation constitutes an original contribution. In the result section of the paper we present sample applications of our model to both simulated and literature-based demographies. Among other we include a study of the Slavs-Balts-Finns genetic relationship, in which we model split and migrations between the Balts and Slavs. We also include another example that involves the migration rates between farmers and hunters-gatherers, based on modern and ancient DNA samples. This latter process was previously studied using coalescent simulations. Our results are in general agreement with the previous method, which provides validation of our approach. Although our model is not an alternative to simulation methods in the practical sense, it provides an algorithm to compute pairwise

  16. Application of Multiple-Population Genetic Algorithm in Optimizing the Train-Set Circulation Plan Problem

    Yu Zhou

    2017-01-01

    Full Text Available The train-set circulation plan problem (TCPP belongs to the rolling stock scheduling (RSS problem and is similar to the aircraft routing problem (ARP in airline operations and the vehicle routing problem (VRP in the logistics field. However, TCPP involves additional complexity due to the maintenance constraint of train-sets: train-sets must conduct maintenance tasks after running for a certain time and distance. The TCPP is nondeterministic polynomial hard (NP-hard. There is no available algorithm that can obtain the optimal global solution, and many factors such as the utilization mode and the maintenance mode impact the solution of the TCPP. This paper proposes a train-set circulation optimization model to minimize the total connection time and maintenance costs and describes the design of an efficient multiple-population genetic algorithm (MPGA to solve this model. A realistic high-speed railway (HSR case is selected to verify our model and algorithm, and, then, a comparison of different algorithms is carried out. Furthermore, a new maintenance mode is proposed, and related implementation requirements are discussed.

  17. Multiple genetic interaction experiments provide complementary information useful for gene function prediction.

    Magali Michaut

    Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

  18. Multiple model adaptive control with mixing

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  19. Genetic search feature selection for affective modeling

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

  20. Genetic diversity and population structure of Lantana camara in India indicates multiple introductions and gene flow.

    Ray, A; Quader, S

    2014-05-01

    Lantana camara is a highly invasive plant, which has spread over 60 countries and island groups of Asia, Africa and Australia. In India, it was introduced in the early nineteenth century, since when it has expanded and gradually established itself in almost every available ecosystem. We investigated the genetic diversity and population structure of this plant in India in order to understand its introduction, subsequent range expansion and gene flow. A total of 179 individuals were sequenced at three chloroplast loci and 218 individuals were genotyped for six nuclear microsatellites. Both chloroplasts (nine haplotypes) and microsatellites (83 alleles) showed high genetic diversity. Besides, each type of marker confirmed the presence of private polymorphism. We uncovered low to medium population structure in both markers, and found a faint signal of isolation by distance with microsatellites. Bayesian clustering analyses revealed multiple divergent genetic clusters. Taken together, these findings (i.e. high genetic diversity with private alleles and multiple genetic clusters) suggest that Lantana was introduced multiple times and gradually underwent spatial expansion with recurrent gene flow. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

  1. Context trees for privacy-preserving modeling of genetic data

    Kusters, C.J.; Ignatenko, T.

    2016-01-01

    In this work, we use context trees for privacypreserving modeling of genetic sequences. The resulting estimated models are applied for functional comparison of genetic sequences in a privacy preserving way. Here we define privacy as uncertainty about the genetic source sequence given its model and

  2. Oligoclonal band status in Scandinavian multiple sclerosis patients is associated with specific genetic risk alleles

    Mero, Inger-Lise; Gustavsen, Marte W; Sæther, Hanne S

    2013-01-01

    The presence of oligoclonal bands (OCB) in cerebrospinal fluid (CSF) is a typical finding in multiple sclerosis (MS). We applied data from Norwegian, Swedish and Danish (i.e. Scandinavian) MS patients from a genome-wide association study (GWAS) to search for genetic differences in MS relating...

  3. Latent spatial models and sampling design for landscape genetics

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  4. Evolutionary model with genetics, aging, and knowledge

    Bustillos, Armando Ticona; de Oliveira, Paulo Murilo

    2004-02-01

    We represent a process of learning by using bit strings, where 1 bits represent the knowledge acquired by individuals. Two ways of learning are considered: individual learning by trial and error, and social learning by copying knowledge from other individuals or from parents in the case of species with parental care. The age-structured bit string allows us to study how knowledge is accumulated during life and its influence over the genetic pool of a population after many generations. We use the Penna model to represent the genetic inheritance of each individual. In order to study how the accumulated knowledge influences the survival process, we include it to help individuals to avoid the various death situations. Modifications in the Verhulst factor do not show any special feature due to its random nature. However, by adding years to life as a function of the accumulated knowledge, we observe an improvement of the survival rates while the genetic fitness of the population becomes worse. In this latter case, knowledge becomes more important in the last years of life where individuals are threatened by diseases. Effects of offspring overprotection and differences between individual and social learning can also be observed. Sexual selection as a function of knowledge shows some effects when fidelity is imposed.

  5. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    Edy Legowo

    2017-01-01

    Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

  6. Genetic Algorithms Principles Towards Hidden Markov Model

    Nabil M. Hewahi

    2011-10-01

    Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
    out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.

  7. Medulloblastoma: Molecular Genetics and Animal Models

    Corey Raffel

    2004-07-01

    Full Text Available Medulloblastoma is a primary brain tumor found in the cerebellum of children. The tumor occurs in association with two inherited cancer syndromes: Turcot syndrome and Gorlin syndrome. Insights into the molecular biology of the tumor have come from looking at alterations in the genes altered in these syndromes, PTC and APC, respectively. Murine models of medulloblastoma have been constructed based on these alterations. Additional murine models that, while mimicking the appearance of the human tumor, seem unrelated to the human tumor's molecular alterations have been made. In this review, the clinical picture, origin, molecular biology, murine models of medulloblastoma are discussed. Although a great deal has been discovered about this tumor, the genetic alterations responsible for tumor development in a majority of patients have yet to be described.

  8. Multiple-trait estimates of genetic parameters for metabolic disease traits, fertility disorders, and their predictors in Canadian Holsteins.

    Jamrozik, J; Koeck, A; Kistemaker, G J; Miglior, F

    2016-03-01

    Producer-recorded health data for metabolic disease traits and fertility disorders on 35,575 Canadian Holstein cows were jointly analyzed with selected indicator traits. Metabolic diseases included clinical ketosis (KET) and displaced abomasum (DA); fertility disorders were metritis (MET) and retained placenta (RP); and disease indicators were fat-to-protein ratio, milk β-hydroxybutyrate, and body condition score (BCS) in the first lactation. Traits in first and later (up to fifth) lactations were treated as correlated in the multiple-trait (13 traits in total) animal linear model. Bayesian methods with Gibbs sampling were implemented for the analysis. Estimates of heritability for disease incidence were low, up to 0.06 for DA in first lactation. Among disease traits, the environmental herd-year variance constituted 4% of the total variance for KET and less for other traits. First- and later-lactation disease traits were genetically correlated (from 0.66 to 0.72) across all traits, indicating different genetic backgrounds for first and later lactations. Genetic correlations between KET and DA were relatively strong and positive (up to 0.79) in both first- and later-lactation cows. Genetic correlations between fertility disorders were slightly lower. Metritis was strongly genetically correlated with both metabolic disease traits in the first lactation only. All other genetic correlations between metabolic and fertility diseases were statistically nonsignificant. First-lactation KET and MET were strongly positively correlated with later-lactation performance for these traits due to the environmental herd-year effect. Indicator traits were moderately genetically correlated (from 0.30 to 0.63 in absolute values) with both metabolic disease traits in the first lactation. Smaller and mostly nonsignificant genetic correlations were among indicators and metabolic diseases in later lactations. The only significant genetic correlations between indicators and fertility

  9. Genetic Programming for Automatic Hydrological Modelling

    Chadalawada, Jayashree; Babovic, Vladan

    2017-04-01

    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  10. Low genetic diversity despite multiple introductions of the invasive plant species Impatiens glandulifera in Europe.

    Hagenblad, Jenny; Hülskötter, Jennifer; Acharya, Kamal Prasad; Brunet, Jörg; Chabrerie, Olivier; Cousins, Sara A O; Dar, Pervaiz A; Diekmann, Martin; De Frenne, Pieter; Hermy, Martin; Jamoneau, Aurélien; Kolb, Annette; Lemke, Isgard; Plue, Jan; Reshi, Zafar A; Graae, Bente Jessen

    2015-08-20

    Invasive species can be a major threat to native biodiversity and the number of invasive plant species is increasing across the globe. Population genetic studies of invasive species can provide key insights into their invasion history and ensuing evolution, but also for their control. Here we genetically characterise populations of Impatiens glandulifera, an invasive plant in Europe that can have a major impact on native plant communities. We compared populations from the species' native range in Kashmir, India, to those in its invaded range, along a latitudinal gradient in Europe. For comparison, the results from 39 other studies of genetic diversity in invasive species were collated. Our results suggest that I. glandulifera was established in the wild in Europe at least twice, from an area outside of our Kashmir study area. Our results further revealed that the genetic diversity in invasive populations of I. glandulifera is unusually low compared to native populations, in particular when compared to other invasive species. Genetic drift rather than mutation seems to have played a role in differentiating populations in Europe. We find evidence of limitations to local gene flow after introduction to Europe, but somewhat less restrictions in the native range. I. glandulifera populations with significant inbreeding were only found in the species' native range and invasive species in general showed no increase in inbreeding upon leaving their native ranges. In Europe we detect cases of migration between distantly located populations. Human activities therefore seem to, at least partially, have facilitated not only introductions, but also further spread of I. glandulifera across Europe. Although multiple introductions will facilitate the retention of genetic diversity in invasive ranges, widespread invasive species can remain genetically relatively invariant also after multiple introductions. Phenotypic plasticity may therefore be an important component of the

  11. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    Edy Legowo

    2017-03-01

    Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

  12. Multiple Temperature Model for Near Continuum Flows

    XU, Kun; Liu, Hongwei; Jiang, Jianzheng

    2007-01-01

    In the near continuum flow regime, the flow may have different translational temperatures in different directions. It is well known that for increasingly rarefied flow fields, the predictions from continuum formulation, such as the Navier-Stokes equations, lose accuracy. These inaccuracies may be partially due to the single temperature assumption in the Navier-Stokes equations. Here, based on the gas-kinetic Bhatnagar-Gross-Krook (BGK) equation, a multitranslational temperature model is proposed and used in the flow calculations. In order to fix all three translational temperatures, two constraints are additionally proposed to model the energy exchange in different directions. Based on the multiple temperature assumption, the Navier-Stokes relation between the stress and strain is replaced by the temperature relaxation term, and the Navier-Stokes assumption is recovered only in the limiting case when the flow is close to the equilibrium with the same temperature in different directions. In order to validate the current model, both the Couette and Poiseuille flows are studied in the transition flow regime

  13. Optimization of Multiple Traveling Salesman Problem Based on Simulated Annealing Genetic Algorithm

    Xu Mingji

    2017-01-01

    Full Text Available It is very effective to solve the multi variable optimization problem by using hierarchical genetic algorithm. This thesis analyzes both advantages and disadvantages of hierarchical genetic algorithm and puts forward an improved simulated annealing genetic algorithm. The new algorithm is applied to solve the multiple traveling salesman problem, which can improve the performance of the solution. First, it improves the design of chromosomes hierarchical structure in terms of redundant hierarchical algorithm, and it suggests a suffix design of chromosomes; Second, concerning to some premature problems of genetic algorithm, it proposes a self-identify crossover operator and mutation; Third, when it comes to the problem of weak ability of local search of genetic algorithm, it stretches the fitness by mixing genetic algorithm with simulated annealing algorithm. Forth, it emulates the problems of N traveling salesmen and M cities so as to verify its feasibility. The simulation and calculation shows that this improved algorithm can be quickly converged to a best global solution, which means the algorithm is encouraging in practical uses.

  14. A Rational Model In Theoretical Genetics

    Karl Javorszky

    2008-07-01

    Full Text Available This model connects information processing in biological organisms with methods and concepts used in classical, technical information processing. The central concept shows copying and regulatory interaction between a logical sequence consisting of triplets and the amount of constituents of a set. The basic mathematical model of information processing within a biological cell has been worked out. The cell in the model copies its present state into a sequence and reads it off the sequence. The sequence comes in triplets and is not one sequence but appears in two almost identical varieties. We treat consecutive and contemporary assemblies of information carrying media as equally suited to contain information. Methods used so far utilised the consecutive property of media, while in biology one observes the concurrent existence of specific realisations of possibilities. Genetics connects the two approaches by using an interplay between consecutively (sequentially ordered logical markers (the DNA and the state of the set engulfing the DNA. Several mathematical tools have been evolved to assemble an interface between sequentially ordered carriers and the same number of carriers if they arrive contemporaneously. Using linguistic theory and formal logic one concludes that measurement(s on a cell are a (set of logical sentence(s relating to an assembly of n objects with group structures among each other. We linearise and count all possible group relations on a set of n objects and introduce the concept of multidimensional partitions hitherto left undefined. We introduce the concept of a maximally structured set by establishing an upper limit to the information carrying capacity of n objects used commutatively and sequentially at the same time (like genetics does. The copying and re-copying mechanism which is the core matter with genetics appears in the model as differing transmission efficiency coefficients of media if the media are used once sequentially

  15. A multiobjective non-dominated sorting genetic algorithm (NSGA-II for the Multiple Traveling Salesman Problem

    Rubén Iván Bolaños

    2015-06-01

    Full Text Available This paper considers a multi-objective version of the Multiple Traveling Salesman Problem (MOmTSP. In particular, two objectives are considered: the minimization of the total traveled distance and the balance of the working times of the traveling salesmen. The problem is formulated as an integer multi-objective optimization model. A non-dominated sorting genetic algorithm (NSGA-II is proposed to solve the MOmTSP. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. Tests on real world instances and instances adapted from the literature show the effectiveness of the proposed algorithm.

  16. Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

    Abkallo, Hussein M.

    2016-10-01

    Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.

  17. The genetics of multiple sclerosis: review of current and emerging candidates

    Muñoz-Culla M

    2013-08-01

    Full Text Available Maider Muñoz-Culla,1,2 Haritz Irizar,1,2 David Otaegui1,2 1Multiple Sclerosis Unit, Instituto Biodonostia, San Sebastián, Spain; 2Red Española de Esclerosis Múltiple (REEM, Barcelona, Spain Abstract: Multiple sclerosis (MS is a complex disease in which environmental, genetic, and epigenetic factors determine the risk of developing the disease. The human leukocyte antigen region is the strongest susceptibility locus linked to MS, but it does not explain the whole heritability of the disease. To find other non-human leukocyte antigen loci associated with the disease, high-throughput genotyping, sequencing, and gene-expression studies have been performed, producing a valuable quantity of information. An overview of the genomic and expression studies is provided in this review, as well as microRNA-expression studies, highlighting the importance of combining all the layers of information in order to elucidate the causes or pathological mechanisms occurring in the disease. Genetics in MS is a promising field that is presumably going to be very productive in the next decade understanding the cross talk between all the factors contributing to the development of MS. Keywords: multiple sclerosis, genetics, gene expression, microRNA

  18. Linear Mixed Models in Statistical Genetics

    R. de Vlaming (Ronald)

    2017-01-01

    markdownabstractOne of the goals of statistical genetics is to elucidate the genetic architecture of phenotypes (i.e., observable individual characteristics) that are affected by many genetic variants (e.g., single-nucleotide polymorphisms; SNPs). A particular aim is to identify specific SNPs that

  19. Genetic screens in Caenorhabditis elegans models for neurodegenerative diseases

    Alvarenga Fernandes Sin, Olga; Michels, Helen; Nollen, Ellen A. A.

    2014-01-01

    Caenorhabditis elegans comprises unique features that make it an attractive model organism in diverse fields of biology. Genetic screens are powerful to identify genes and C. elegans can be customized to forward or reverse genetic screens and to establish gene function. These genetic screens can be

  20. Genetic structuring of northern myotis (Myotis septentrionalis) at multiple spatial scales

    Johnson, Joshua B.; Roberts, James H.; King, Timothy L.; Edwards, John W.; Ford, W. Mark; Ray, David A.

    2014-01-01

    Although groups of bats may be genetically distinguishable at large spatial scales, the effects of forest disturbances, particularly permanent land use conversions on fine-scale population structure and gene flow of summer aggregations of philopatric bat species are less clear. We genotyped and analyzed variation at 10 nuclear DNA microsatellite markers in 182 individuals of the forest-dwelling northern myotis (Myotis septentrionalis) at multiple spatial scales, from within first-order watersheds scaling up to larger regional areas in West Virginia and New York. Our results indicate that groups of northern myotis were genetically indistinguishable at any spatial scale we considered, and the collective population maintained high genetic diversity. It is likely that the ability to migrate, exploit small forest patches, and use networks of mating sites located throughout the Appalachian Mountains, Interior Highlands, and elsewhere in the hibernation range have allowed northern myotis to maintain high genetic diversity and gene flow regardless of forest disturbances at local and regional spatial scales. A consequence of maintaining high gene flow might be the potential to minimize genetic founder effects following population declines caused currently by the enzootic White-nose Syndrome.

  1. Phylogeographic and population genetic analyses reveal multiple species of Boa and independent origins of insular dwarfism.

    Card, Daren C; Schield, Drew R; Adams, Richard H; Corbin, Andrew B; Perry, Blair W; Andrew, Audra L; Pasquesi, Giulia I M; Smith, Eric N; Jezkova, Tereza; Boback, Scott M; Booth, Warren; Castoe, Todd A

    2016-09-01

    Boa is a Neotropical genus of snakes historically recognized as monotypic despite its expansive distribution. The distinct morphological traits and color patterns exhibited by these snakes, together with the wide diversity of ecosystems they inhabit, collectively suggest that the genus may represent multiple species. Morphological variation within Boa also includes instances of dwarfism observed in multiple offshore island populations. Despite this substantial diversity, the systematics of the genus Boa has received little attention until very recently. In this study we examined the genetic structure and phylogenetic relationships of Boa populations using mitochondrial sequences and genome-wide SNP data obtained from RADseq. We analyzed these data at multiple geographic scales using a combination of phylogenetic inference (including coalescent-based species delimitation) and population genetic analyses. We identified extensive population structure across the range of the genus Boa and multiple lines of evidence for three widely-distributed clades roughly corresponding with the three primary land masses of the Western Hemisphere. We also find both mitochondrial and nuclear support for independent origins and parallel evolution of dwarfism on offshore island clusters in Belize and Cayos Cochinos Menor, Honduras. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Helicobacter pylori genetic diversification in the Mongolian gerbil model.

    Beckett, Amber C; Loh, John T; Chopra, Abha; Leary, Shay; Lin, Aung Soe; McDonnell, Wyatt J; Dixon, Beverly R E A; Noto, Jennifer M; Israel, Dawn A; Peek, Richard M; Mallal, Simon; Algood, Holly M Scott; Cover, Timothy L

    2018-01-01

    Helicobacter pylori requires genetic agility to infect new hosts and establish long-term colonization of changing gastric environments. In this study, we analyzed H. pylori genetic adaptation in the Mongolian gerbil model. This model is of particular interest because H. pylori -infected gerbils develop a high level of gastric inflammation and often develop gastric adenocarcinoma or gastric ulceration. We analyzed the whole genome sequences of H. pylori strains cultured from experimentally infected gerbils, in comparison to the genome sequence of the input strain. The mean annualized single nucleotide polymorphism (SNP) rate per site was 1.5e -5 , which is similar to the rates detected previously in H. pylori- infected humans. Many of the mutations occurred within or upstream of genes associated with iron-related functions ( fur , tonB1 , fecA2 , fecA3 , and frpB3 ) or encoding outer membrane proteins ( alpA, oipA, fecA2, fecA3, frpB3 and cagY ). Most of the SNPs within coding regions (86%) were non-synonymous mutations. Several deletion or insertion mutations led to disruption of open reading frames, suggesting that the corresponding gene products are not required or are deleterious during chronic H. pylori colonization of the gerbil stomach. Five variants (three SNPs and two deletions) were detected in isolates from multiple animals, which suggests that these mutations conferred a selective advantage. One of the mutations (FurR88H) detected in isolates from multiple animals was previously shown to confer increased resistance to oxidative stress, and we now show that this SNP also confers a survival advantage when H. pylori is co-cultured with neutrophils. Collectively, these analyses allow the identification of mutations that are positively selected during H. pylori colonization of the gerbil model.

  3. Genetic variants are major determinants of CSF antibody levels in multiple sclerosis

    Goris, An; Pauwels, Ine; Gustavsen, Marte W

    2015-01-01

    Immunological hallmarks of multiple sclerosis include the production of antibodies in the central nervous system, expressed as presence of oligoclonal bands and/or an increased immunoglobulin G index-the level of immunoglobulin G in the cerebrospinal fluid compared to serum. However, the underlying...... differences between oligoclonal band-positive and -negative patients with multiple sclerosis and reasons for variability in immunoglobulin G index are not known. To identify genetic factors influencing the variation in the antibody levels in the cerebrospinal fluid in multiple sclerosis, we have performed...... a genome-wide association screen in patients collected from nine countries for two traits, presence or absence of oligoclonal bands (n = 3026) and immunoglobulin G index levels (n = 938), followed by a replication in 3891 additional patients. We replicate previously suggested association signals...

  4. Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

    Li, Muxingzi

    2017-01-01

    of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous

  5. The intergenerational multiple deficit model and the case of dyslexia

    Elsje evan Bergen

    2014-06-01

    Full Text Available Which children go on to develop dyslexia? Since dyslexia has a multifactorial aetiology, this question can be restated as: What are the factors that put children at high risk for developing dyslexia? It is argued that a useful theoretical framework to address this question is Pennington’s (2006 multiple deficit model (MDM. This model replaces models that attribute dyslexia to a single underlying cause. Subsequently, the generalist genes hypothesis for learning (disabilities (Plomin & Kovas, 2005 is described and integrated with the MDM. Finally, findings are presented from a longitudinal study with children at family risk for dyslexia. Such studies can contribute to testing and specifying the MDM. In this study, risk factors at both the child and family level were investigated. This led to the proposed intergenerational MDM, in which both parents confer liability via intertwined genetic and environmental pathways. Future scientific directions are discussed to investigate parent-offspring resemblance and transmission patterns, which will shed new light on disorder aetiology.

  6. Preimplantation genetic diagnosis for a patient with multiple endocrine neoplasia type 1: case report.

    Lima, Aline Dt; Alves, Vanessa R; Rocha, Andressa R; Martinhago, Ana C; Martinhago, Ciro; Donadio, Nilka; Dzik, Artur; Cavagna, Mario; Gebrim, Luiz H

    2018-03-01

    Preimplantation genetic diagnosis was carried out for embryonic analysis in a patient with multiple endocrine neoplasia type 1 (MEN1). This is a rare autosomal-dominant cancer syndrome and the patients with MEN1 are characterized by the occurrence of tumors in multiple endocrine tissues, associated with germline and somatic inactivating mutations in the MEN1 gene. This case report documents a successful preimplantation genetic diagnosis (PGD) involving a couple at-risk for MEN1 syndrome, with a birth of a healthy infant. The couple underwent a cycle of controlled ovarian stimulation and intracytoplasmic sperm injection (ICSI). Embryos were biopsied at the blastocyst stage and cryopreserved; we used PCR-based DNA analysis for PGD testing. Only one of the five embryos analyzed for MEN1 syndrome was unaffected. This embryo was thawed and transferred following endometrial preparation. After positive βHCG test; clinical pregnancy was confirmed by ultrasound, and a healthy infant was born. PGD for single gene disorders has been an emerging therapeutic tool for couples who are at risk of passing a genetic disease on to their offspring.

  7. Analysis of the genetic variation in Mycobacterium tuberculosis strains by multiple genome alignments

    Morales Juan

    2008-11-01

    Full Text Available Abstract Background The recent determination of the complete nucleotide sequence of several Mycobacterium tuberculosis (MTB genomes allows the use of comparative genomics as a tool for dissecting the nature and consequence of genetic variability within this species. The multiple alignment of the genomes of clinical strains (CDC1551, F11, Haarlem and C, along with the genomes of laboratory strains (H37Rv and H37Ra, provides new insights on the mechanisms of adaptation of this bacterium to the human host. Findings The genetic variation found in six M. tuberculosis strains does not involve significant genomic rearrangements. Most of the variation results from deletion and transposition events preferentially associated with insertion sequences and genes of the PE/PPE family but not with genes implicated in virulence. Using a Perl-based software islandsanalyser, which creates a representation of the genetic variation in the genome, we identified differences in the patterns of distribution and frequency of the polymorphisms across the genome. The identification of genes displaying strain-specific polymorphisms and the extrapolation of the number of strain-specific polymorphisms to an unlimited number of genomes indicates that the different strains contain a limited number of unique polymorphisms. Conclusion The comparison of multiple genomes demonstrates that the M. tuberculosis genome is currently undergoing an active process of gene decay, analogous to the adaptation process of obligate bacterial symbionts. This observation opens new perspectives into the evolution and the understanding of the pathogenesis of this bacterium.

  8. Cisplatin resistance: a cellular self-defense mechanism resulting from multiple epigenetic and genetic changes.

    Shen, Ding-Wu; Pouliot, Lynn M; Hall, Matthew D; Gottesman, Michael M

    2012-07-01

    Cisplatin is one of the most effective broad-spectrum anticancer drugs. Its effectiveness seems to be due to the unique properties of cisplatin, which enters cells via multiple pathways and forms multiple different DNA-platinum adducts while initiating a cellular self-defense system by activating or silencing a variety of different genes, resulting in dramatic epigenetic and/or genetic alternations. As a result, the development of cisplatin resistance in human cancer cells in vivo and in vitro by necessity stems from bewilderingly complex genetic and epigenetic changes in gene expression and alterations in protein localization. Extensive published evidence has demonstrated that pleiotropic alterations are frequently detected during development of resistance to this toxic metal compound. Changes occur in almost every mechanism supporting cell survival, including cell growth-promoting pathways, apoptosis, developmental pathways, DNA damage repair, and endocytosis. In general, dozens of genes are affected in cisplatin-resistant cells, including pathways involved in copper metabolism as well as transcription pathways that alter the cytoskeleton, change cell surface presentation of proteins, and regulate epithelial-to-mesenchymal transition. Decreased accumulation is one of the most common features resulting in cisplatin resistance. This seems to be a consequence of numerous epigenetic and genetic changes leading to the loss of cell-surface binding sites and/or transporters for cisplatin, and decreased fluid phase endocytosis.

  9. Multiple Models for Rosaceae Genomics[OA

    Shulaev, Vladimir; Korban, Schuyler S.; Sosinski, Bryon; Abbott, Albert G.; Aldwinckle, Herb S.; Folta, Kevin M.; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M.; Lewers, Kim; Brown, Susan K.; Davis, Thomas M.; Gardiner, Susan E.; Potter, Daniel; Veilleux, Richard E.

    2008-01-01

    The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement. PMID:18487361

  10. Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

    Woods, Carol M.; Grimm, Kevin J.

    2011-01-01

    In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

  11. Multiplicity distributions in the dual parton model

    Batunin, A.V.; Tolstenkov, A.N.

    1985-01-01

    Multiplicity distributions are calculated by means of a new mechanism of production of hadrons in a string, which was proposed previously by the authors and takes into account explicitly the valence character of the ends of the string. It is shown that allowance for this greatly improves the description of the low-energy multiplicity distributions. At superhigh energies, the contribution of the ends of the strings becomes negligibly small, but in this case multi-Pomeron contributions must be taken into account

  12. Multiple genetic variants associated with primary biliary cirrhosis in a Han Chinese population.

    Dong, Ming; Li, Jinxin; Tang, Ruqi; Zhu, Ping; Qiu, Fang; Wang, Chan; Qiu, Jie; Wang, Lan; Dai, Yaping; Xu, Ping; Gao, Yueqiu; Han, Chongxu; Wang, Yongzhong; Wu, Jian; Wu, Xudong; Zhang, Kui; Dai, Na; Sun, Weihao; Zhou, Jianpo; Hu, Zhigang; Liu, Lei; Jiang, Yuzhang; Nie, Jinshan; Zhao, Yi; Gong, Yuhua; Tian, Ye; Ji, Hualiang; Jiao, Zhijun; Jiang, Po; Shi, Xingjuan; Jawed, Rohil; Zhang, Yu; Huang, Qinghai; Li, Enling; Wei, Yiran; Xie, Wei; Zhao, Weifeng; Liu, Xiang; Zhu, Xiang; Qiu, Hong; He, Gengsheng; Chen, Weichang; Seldin, Michael F; Gershwin, M Eric; Liu, Xiangdong; Ma, Xiong

    2015-06-01

    Multiple genome-wide association studies of primary biliary cirrhosis (PBC) in both European and Japanese ancestries have shown significant associations of many genetic loci contributing to the susceptibility to PBC. Major differences in susceptibility loci between these two population groups were observed. In this study, we examined whether the most significant loci observed in either European and/or Japanese cohorts are associated with PBC in a Han Chinese population. In 1070 PBC patients and 1198 controls, we observed highly significant associations at CD80 (rs2293370, P = 2.67 × 10(-8)) and TNFSF15 (rs4979462, P = 3.86 × 10(-8)) and significant associations at 17q12-21 (rs9303277), PDGFB (rs715505), NF-κB1 (rs7665090), IL12RB2 (rs11209050), and STAT4 (rs7574865; all corrected P values rs7574865) was strongly associated after additional control samples were analyzed. Our study is the first large-scale genetic analysis in a Han Chinese PBC cohort. These results do not only reflect that Han Chinese PBC patients share common genetic susceptibility genes with both their Japanese and European counterparts but also suggest a distinctly different genetic susceptibility profile.

  13. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    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...

  14. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    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...

  15. The genetics of multiple sclerosis: review of current and emerging candidates

    Muñoz-Culla, Maider; Irizar, Haritz; Otaegui, David

    2013-01-01

    Multiple sclerosis (MS) is a complex disease in which environmental, genetic, and epigenetic factors determine the risk of developing the disease. The human leukocyte antigen region is the strongest susceptibility locus linked to MS, but it does not explain the whole heritability of the disease. To find other non-human leukocyte antigen loci associated with the disease, high-throughput genotyping, sequencing, and gene-expression studies have been performed, producing a valuable quantity of information. An overview of the genomic and expression studies is provided in this review, as well as microRNA-expression studies, highlighting the importance of combining all the layers of information in order to elucidate the causes or pathological mechanisms occurring in the disease. Genetics in MS is a promising field that is presumably going to be very productive in the next decade understanding the cross talk between all the factors contributing to the development of MS. PMID:24019748

  16. Evolving Four Part Harmony Using a Multiple Worlds Model

    Scirea, Marco; Brown, Joseph Alexander

    2015-01-01

    This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...

  17. Explaining clinical behaviors using multiple theoretical models

    Eccles Martin P

    2012-10-01

    the five surveys. For the predictor variables, the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. Conclusions We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

  18. Explaining clinical behaviors using multiple theoretical models.

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-10-17

    , the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

  19. Animal models for human genetic diseases | Sharif | African Journal ...

    The study of human genetic diseases can be greatly aided by animal models because of their similarity to humans in terms of genetics. In addition to understand diverse aspects of basic biology, model organisms are extensively used in applied research in agriculture, industry, and also in medicine, where they are used to ...

  20. An Efficient Stepwise Statistical Test to Identify Multiple Linked Human Genetic Variants Associated with Specific Phenotypic Traits.

    Iksoo Huh

    Full Text Available Recent advances in genotyping methodologies have allowed genome-wide association studies (GWAS to accurately identify genetic variants that associate with common or pathological complex traits. Although most GWAS have focused on associations with single genetic variants, joint identification of multiple genetic variants, and how they interact, is essential for understanding the genetic architecture of complex phenotypic traits. Here, we propose an efficient stepwise method based on the Cochran-Mantel-Haenszel test (for stratified categorical data to identify causal joint multiple genetic variants in GWAS. This method combines the CMH statistic with a stepwise procedure to detect multiple genetic variants associated with specific categorical traits, using a series of associated I × J contingency tables and a null hypothesis of no phenotype association. Through a new stratification scheme based on the sum of minor allele count criteria, we make the method more feasible for GWAS data having sample sizes of several thousands. We also examine the properties of the proposed stepwise method via simulation studies, and show that the stepwise CMH test performs better than other existing methods (e.g., logistic regression and detection of associations by Markov blanket for identifying multiple genetic variants. Finally, we apply the proposed approach to two genomic sequencing datasets to detect linked genetic variants associated with bipolar disorder and obesity, respectively.

  1. Teaching Genetic Counseling Skills: Incorporating a Genetic Counseling Adaptation Continuum Model to Address Psychosocial Complexity.

    Shugar, Andrea

    2017-04-01

    Genetic counselors are trained health care professionals who effectively integrate both psychosocial counseling and information-giving into their practice. Preparing genetic counseling students for clinical practice is a challenging task, particularly when helping them develop effective and active counseling skills. Resistance to incorporating these skills may stem from decreased confidence, fear of causing harm or a lack of clarity of psycho-social goals. The author reflects on the personal challenges experienced in teaching genetic counselling students to work with psychological and social complexity, and proposes a Genetic Counseling Adaptation Continuum model and methodology to guide students in the use of advanced counseling skills.

  2. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

    Sawcer, Stephen; Hellenthal, Garrett; Pirinen, Matti

    2011-01-01

    Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown...... the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture...... underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working...

  3. A genetic algorithm for multiple relay selection in two-way relaying cognitive radio networks

    Alsharoa, Ahmad M.

    2013-09-01

    In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplifyand- Forward (AF) protocol are optimally selected to maximize the sum rate of the secondary users without degrading the Quality of Service (QoS) of the primary users by respecting a tolerated interference threshold. A strong optimization tool based on genetic algorithm is employed to solve our formulated optimization problem where discrete relay power levels are considered. Our simulation results show that the practical heuristic approach achieves almost the same performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions. Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.

  4. Integration of multiple, excess, backup, and expected covering models

    M S Daskin; K Hogan; C ReVelle

    1988-01-01

    The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multi-state covering models. An expected covering model with multiple time standards is also presented.

  5. Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors.

    Gianfrancesco, Milena A; Acuna, Brigid; Shen, Ling; Briggs, Farren B S; Quach, Hong; Bellesis, Kalliope H; Bernstein, Allan; Hedstrom, Anna K; Kockum, Ingrid; Alfredsson, Lars; Olsson, Tomas; Schaefer, Catherine; Barcellos, Lisa F

    2014-01-01

    To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. In analyses stratified by gender, being overweight at ages 10 and 20 were associated with MS in females (pchildhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

  6. Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors

    Gianfrancesco, Milena A.; Acuna, Brigid; Shen, Ling; Briggs, Farren B.S.; Quach, Hong; Bellesis, Kalliope H.; Bernstein, Allan; Hedstrom, Anna K.; Kockum, Ingrid; Alfredsson, Lars; Olsson, Tomas; Schaefer, Catherine; Barcellos, Lisa F.

    2014-01-01

    Objective To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Methods Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1,235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. Results In analyses stratified by gender, being overweight at age 10 and 20 were associated with MS in females (prisk of MS for females with a BMI ≥ 30 kg/m2 was observed (OR = 2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20’s and MS in males were not observed. Multivariate modeling demonstrated that significant associations between BMI or body size with MS in females persisted after adjusting for history of infectious mononucleosis and genetic risk factors, including HLA-DRB1*15:01 and established non-HLA risk alleles. Interpretation Results show that childhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20’s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors. PMID:25263833

  7. One Novel Multiple-Target Plasmid Reference Molecule Targeting Eight Genetically Modified Canola Events for Genetically Modified Canola Detection.

    Li, Zhuqing; Li, Xiang; Wang, Canhua; Song, Guiwen; Pi, Liqun; Zheng, Lan; Zhang, Dabing; Yang, Litao

    2017-09-27

    Multiple-target plasmid DNA reference materials have been generated and utilized as good substitutes of matrix-based reference materials in the analysis of genetically modified organisms (GMOs). Herein, we report the construction of one multiple-target plasmid reference molecule, pCAN, which harbors eight GM canola event-specific sequences (RF1, RF2, MS1, MS8, Topas 19/2, Oxy235, RT73, and T45) and a partial sequence of the canola endogenous reference gene PEP. The applicability of this plasmid reference material in qualitative and quantitative PCR assays of the eight GM canola events was evaluated, including the analysis of specificity, limit of detection (LOD), limit of quantification (LOQ), and performance of pCAN in the analysis of various canola samples, etc. The LODs are 15 copies for RF2, MS1, and RT73 assays using pCAN as the calibrator and 10 genome copies for the other events. The LOQ in each event-specific real-time PCR assay is 20 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and PEP assays are between 91% and 97%, and the squared regression coefficients (R 2 ) are all higher than 0.99. The quantification bias values varied from 0.47% to 20.68% with relative standard deviation (RSD) from 1.06% to 24.61% in the quantification of simulated samples. Furthermore, 10 practical canola samples sampled from imported shipments in the port of Shanghai, China, were analyzed employing pCAN as the calibrator, and the results were comparable with those assays using commercial certified materials as the calibrator. Concluding from these results, we believe that this newly developed pCAN plasmid is one good candidate for being a plasmid DNA reference material in the detection and quantification of the eight GM canola events in routine analysis.

  8. Core neuropathological abnormalities in progranulin-deficient mice are penetrant on multiple genetic backgrounds.

    Petkau, T L; Hill, A; Leavitt, B R

    2016-02-19

    Loss-of-function mutations in the progranulin gene (GRN) are a common cause of familial frontotemporal lobar degeneration (FTLD). A high degree of heterogeneity in the age-of-onset, duration of disease, and clinical presentation of FTLD, even among families carrying the same GRN mutation, suggests that additional modifying genes may be important to pathogenesis. Progranulin-knockout mice display subtle behavioral abnormalities and progressive neuropathological changes, as well as altered dendritic morphology and synaptic deficits in the hippocampus. In this study we evaluated multiple neuropathological endpoints in aged progranulin knockout mice and their wild-type littermates on two different genetic backgrounds: C57Bl/6 and 129/SvImJ. We find that in most brain regions, both strains are susceptible to progranulin-mediated neuropathological phenotypes, including astrogliosis, microgliosis, and highly accelerated deposition of the aging pigment lipofuscin. Neuroinflammation due to progranulin deficiency is exaggerated in the B6 strain and present, but less pronounced, in the 129 strain. Differences between the strains in hippocampal neuron counts and neuronal morphology suggest a complex role for progranulin in the hippocampus. We conclude that core progranulin-mediated neurodegenerative phenotypes are penetrant on multiple inbred mouse strains, but that genetic background modulates progranulin's role in neuroinflammation and hippocampal biology. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. Progranulin genetic polymorphisms influence progression of disability and relapse recovery in multiple sclerosis.

    Vercellino, Marco; Fenoglio, Chiara; Galimberti, Daniela; Mattioda, Alessandra; Chiavazza, Carlotta; Binello, Eleonora; Pinessi, Lorenzo; Giobbe, Dario; Scarpini, Elio; Cavalla, Paola

    2016-07-01

    Progranulin (GRN) is a multifunctional protein involved in inflammation and repair, and also a neurotrophic factor critical for neuronal survival. Progranulin is strongly expressed in multiple sclerosis (MS) brains by macrophages and microglia. In this study we evaluated GRN genetic variability in 400 MS patients, in correlation with clinical variables such as disease severity and relapse recovery. We also evaluated serum progranulin levels in the different groups of GRN variants carriers. We found that incomplete recovery after a relapse is correlated with an increased frequency of the rs9897526 A allele (odds ratio (OR) 4.367, p = 0.005). A more severe disease course (Multiple Sclerosis Severity Score > 5) is correlated with an increased frequency of the rs9897526 A allele (OR 1.886, p = 0.002) and of the rs5848 T allele (OR 1.580, p = 0.019). Carriers of the variants associated with a more severe disease course (rs9897526 A, rs5848 T) have significantly lower levels of circulating progranulin (80.5 ± 9.1 ng/mL vs. 165.7 ng/mL, p = 0.01). GRN genetic polymorphisms likely influence disease course and relapse recovery in MS. © The Author(s), 2015.

  10. Maternal Smoking During Pregnancy and Offspring Birth Weight: A Genetically-Informed Approach Comparing Multiple Raters

    Knopik, Valerie S.; Marceau, Kristine; Palmer, Rohan H. C.; Smith, Taylor F.; Heath, Andrew C.

    2016-01-01

    Maternal smoking during pregnancy (SDP) is a significant public health concern with adverse consequences to the health and well-being of the fetus. There is considerable debate about the best method of assessing SDP, including birth/medical records, timeline follow-back approaches, multiple reporters, and biological verification (e.g., cotinine). This is particularly salient for genetically-informed approaches where it is not always possible or practical to do a prospective study starting during the prenatal period when concurrent biological specimen samples can be collected with ease. In a sample of families (N = 173) specifically selected for sibling pairs discordant for prenatal smoking exposure, we: (1) compare rates of agreement across different types of report—maternal report of SDP, paternal report of maternal SDP, and SDP contained on birth records from the Department of Vital Statistics; (2) examine whether SDP is predictive of birth weight outcomes using our best SDP report as identified via step (1); and (3) use a sibling-comparison approach that controls for genetic and familial influences that siblings share in order to assess the effects of SDP on birth weight. Results show high agreement between reporters and support the utility of retrospective report of SDP. Further, we replicate a causal association between SDP and birth weight, wherein SDP results in reduced birth weight even when accounting for genetic and familial confounding factors via a sibling comparison approach. PMID:26494459

  11. A test for the parameters of multiple linear regression models ...

    A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

  12. Genetic variants of the alpha-synuclein gene SNCA are associated with multiple system atrophy.

    Ammar Al-Chalabi

    Full Text Available BACKGROUND: Multiple system atrophy (MSA is a progressive neurodegenerative disorder characterized by parkinsonism, cerebellar ataxia and autonomic dysfunction. Pathogenic mechanisms remain obscure but the neuropathological hallmark is the presence of alpha-synuclein-immunoreactive glial cytoplasmic inclusions. Genetic variants of the alpha-synuclein gene, SNCA, are thus strong candidates for genetic association with MSA. One follow-up to a genome-wide association of Parkinson's disease has identified association of a SNP in SNCA with MSA. METHODOLOGY/FINDINGS: We evaluated 32 SNPs in the SNCA gene in a European population of 239 cases and 617 controls recruited as part of the Neuroprotection and Natural History in Parkinson Plus Syndromes (NNIPPS study. We used 161 independently collected samples for replication. Two SNCA SNPs showed association with MSA: rs3822086 (P = 0.0044, and rs3775444 (P = 0.012, although only the first survived correction for multiple testing. In the MSA-C subgroup the association strengthened despite more than halving the number of cases: rs3822086 P = 0.0024, OR 2.153, (95% CI 1.3-3.6; rs3775444 P = 0.0017, OR 4.386 (95% CI 1.6-11.7. A 7-SNP haplotype incorporating three SNPs either side of rs3822086 strengthened the association with MSA-C further (best haplotype, P = 8.7 x 10(-4. The association with rs3822086 was replicated in the independent samples (P = 0.035. CONCLUSIONS/SIGNIFICANCE: We report a genetic association between MSA and alpha-synuclein which has replicated in independent samples. The strongest association is with the cerebellar subtype of MSA. TRIAL REGISTRATION: ClinicalTrials.gov NCT00211224.

  13. Genetic Factors Associated with Risk and Disability Progression of Multiple Sclerosis in Slovak Population

    Hanysova Sandra

    2017-08-01

    Full Text Available Objective: The aim of our study was to determine the relation of particular genetic variants in selected genes (GSTM1, GSTT1 null genotypes; rs1695 GSTP1; rs10735781 EVI5 to the risk of multiple sclerosis (MS development and find out the possible association with disease disability progression rate. Material and methods: Our study included 202 MS patients and 174 healthy control volunteers. MS patients were divided according to disability progression rate to three groups - slowly progressing, mid-rate progressing and rapidly progressing. All DNA samples were isolated from venous blood. Genotyping was performed by PCR-RFLP and multiplex PCR. Results: Our analysis showed that GSTT1 null genotype (OR 0.56; 95%CI 0.33 -0.95; p=0.04 and GSTM1, GSTT1 double null genotype (OR 0.32; 95%CI 0.14 - 0.74; p=0.006 are potentially protective in relation to MS. We observed similar result in GSTT1 null genotype in association with mid-rate progression (OR 0.48; 95%CI 0.24 - 0.97; p=0.05. Frequency of GSTM1 and GSTT1 double null genotype is significantly lower in subgroup of MS patients with progression rate defined as slow (OR 0.22; 95%CI 0.05 - 0.98; p=0.05 and middle (OR 0.33; 95%CI 0.11 - 0.99; p=0.045. We did not show any significant association of genetic changes rs1695 in GSTP1 and rs10735781 in EVI5 with MS or rate of disease progression. Conclusions: Genetic basis of multiple sclerosis is still not fully elucidated. Further research may clarify our results and confirm the value of studied factors for clinical practice.

  14. Genetic variants are major determinants of CSF antibody levels in multiple sclerosis.

    Goris, An; Pauwels, Ine; Gustavsen, Marte W; van Son, Brechtje; Hilven, Kelly; Bos, Steffan D; Celius, Elisabeth Gulowsen; Berg-Hansen, Pål; Aarseth, Jan; Myhr, Kjell-Morten; D'Alfonso, Sandra; Barizzone, Nadia; Leone, Maurizio A; Martinelli Boneschi, Filippo; Sorosina, Melissa; Liberatore, Giuseppe; Kockum, Ingrid; Olsson, Tomas; Hillert, Jan; Alfredsson, Lars; Bedri, Sahl Khalid; Hemmer, Bernhard; Buck, Dorothea; Berthele, Achim; Knier, Benjamin; Biberacher, Viola; van Pesch, Vincent; Sindic, Christian; Bang Oturai, Annette; Søndergaard, Helle Bach; Sellebjerg, Finn; Jensen, Poul Erik H; Comabella, Manuel; Montalban, Xavier; Pérez-Boza, Jennifer; Malhotra, Sunny; Lechner-Scott, Jeannette; Broadley, Simon; Slee, Mark; Taylor, Bruce; Kermode, Allan G; Gourraud, Pierre-Antoine; Sawcer, Stephen J; Andreassen, Bettina Kullle; Dubois, Bénédicte; Harbo, Hanne F

    2015-03-01

    Immunological hallmarks of multiple sclerosis include the production of antibodies in the central nervous system, expressed as presence of oligoclonal bands and/or an increased immunoglobulin G index-the level of immunoglobulin G in the cerebrospinal fluid compared to serum. However, the underlying differences between oligoclonal band-positive and -negative patients with multiple sclerosis and reasons for variability in immunoglobulin G index are not known. To identify genetic factors influencing the variation in the antibody levels in the cerebrospinal fluid in multiple sclerosis, we have performed a genome-wide association screen in patients collected from nine countries for two traits, presence or absence of oligoclonal bands (n = 3026) and immunoglobulin G index levels (n = 938), followed by a replication in 3891 additional patients. We replicate previously suggested association signals for oligoclonal band status in the major histocompatibility complex region for the rs9271640*A-rs6457617*G haplotype, correlated with HLA-DRB1*1501, and rs34083746*G, correlated with HLA-DQA1*0301 (P comparing two haplotypes = 8.88 × 10(-16)). Furthermore, we identify a novel association signal of rs9807334, near the ELAC1/SMAD4 genes, for oligoclonal band status (P = 8.45 × 10(-7)). The previously reported association of the immunoglobulin heavy chain locus with immunoglobulin G index reaches strong evidence for association in this data set (P = 3.79 × 10(-37)). We identify two novel associations in the major histocompatibility complex region with immunoglobulin G index: the rs9271640*A-rs6457617*G haplotype (P = 1.59 × 10(-22)), shared with oligoclonal band status, and an additional independent effect of rs6457617*G (P = 3.68 × 10(-6)). Variants identified in this study account for up to 2-fold differences in the odds of being oligoclonal band positive and 7.75% of the variation in immunoglobulin G index. Both traits are associated with clinical features of disease such

  15. Genetic variants are major determinants of CSF antibody levels in multiple sclerosis

    Pauwels, Ine; Gustavsen, Marte W.; van Son, Brechtje; Hilven, Kelly; Bos, Steffan D.; Celius, Elisabeth Gulowsen; Berg-Hansen, Pål; Aarseth, Jan; Myhr, Kjell-Morten; D’Alfonso, Sandra; Barizzone, Nadia; Leone, Maurizio A.; Martinelli Boneschi, Filippo; Sorosina, Melissa; Liberatore, Giuseppe; Kockum, Ingrid; Olsson, Tomas; Hillert, Jan; Alfredsson, Lars; Bedri, Sahl Khalid; Hemmer, Bernhard; Buck, Dorothea; Berthele, Achim; Knier, Benjamin; Biberacher, Viola; van Pesch, Vincent; Sindic, Christian; Bang Oturai, Annette; Søndergaard, Helle Bach; Sellebjerg, Finn; Jensen, Poul Erik H.; Comabella, Manuel; Montalban, Xavier; Pérez-Boza, Jennifer; Malhotra, Sunny; Lechner-Scott, Jeannette; Broadley, Simon; Slee, Mark; Taylor, Bruce; Kermode, Allan G.; Gourraud, Pierre-Antoine; Sawcer, Stephen J.; Andreassen, Bettina Kullle; Dubois, Bénédicte; Harbo, Hanne F.

    2015-01-01

    Immunological hallmarks of multiple sclerosis include the production of antibodies in the central nervous system, expressed as presence of oligoclonal bands and/or an increased immunoglobulin G index—the level of immunoglobulin G in the cerebrospinal fluid compared to serum. However, the underlying differences between oligoclonal band-positive and -negative patients with multiple sclerosis and reasons for variability in immunoglobulin G index are not known. To identify genetic factors influencing the variation in the antibody levels in the cerebrospinal fluid in multiple sclerosis, we have performed a genome-wide association screen in patients collected from nine countries for two traits, presence or absence of oligoclonal bands (n = 3026) and immunoglobulin G index levels (n = 938), followed by a replication in 3891 additional patients. We replicate previously suggested association signals for oligoclonal band status in the major histocompatibility complex region for the rs9271640*A-rs6457617*G haplotype, correlated with HLA-DRB1*1501, and rs34083746*G, correlated with HLA-DQA1*0301 (P comparing two haplotypes = 8.88 × 10−16). Furthermore, we identify a novel association signal of rs9807334, near the ELAC1/SMAD4 genes, for oligoclonal band status (P = 8.45 × 10−7). The previously reported association of the immunoglobulin heavy chain locus with immunoglobulin G index reaches strong evidence for association in this data set (P = 3.79 × 10−37). We identify two novel associations in the major histocompatibility complex region with immunoglobulin G index: the rs9271640*A-rs6457617*G haplotype (P = 1.59 × 10−22), shared with oligoclonal band status, and an additional independent effect of rs6457617*G (P = 3.68 × 10−6). Variants identified in this study account for up to 2-fold differences in the odds of being oligoclonal band positive and 7.75% of the variation in immunoglobulin G index. Both traits are associated with clinical features of disease such

  16. [Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

    Li, J; Qiu, J; Tang, Z; Shen, L

    1992-01-01

    According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

  17. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction.

    Yiming Hu

    2017-06-01

    Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.

  18. Medicare capitation model, functional status, and multiple comorbidities: model accuracy

    Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

    2012-01-01

    Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

  19. A rapid and efficient protocol for in vitro multiplication of genetically uniform Stevia rebaudiana (Bertoni).

    Khan, A; Jayanthi, M; Gantasala, Nagavara Prasad; Bhooshan, N; Rao, Uma

    2016-07-01

    Stevia rebaudiana (Bertoni), commonly called candy leaf or sweet leaf, endemic to South America, is an important medicinal plant. As a source of low calorie natural sweetener 'stevoside', it is used in obesity, diabetes, treatment of heartburn and tooth decay, and also serves as a food supplement. Large scale commercial propagation of S. rebaudiana demands a suitable protocol. Here, we propose an improved protocol for in vitro multiplication of S. rebaudiana from nodal explants. In this protocol, the effect of laboratory grade urea on multiple shoot induction from nodal explants was studied. The nodal explants were initially cultured on Murashige and Skoog (MS) basal media for 2 weeks which facilitated the axillary bud break. Further, culturing of these explants on MS medium fortified with 6 benzyl amninopurine (BAP) (2 mg/L) and Naphthalene acetic acid (NAA) (1 mg/L) with and .without urea (5 mg/L) for a period of 40 days revealed maximum shoot production of 44.56 from a single nodal explant in media supplemented with urea as compared to 22.44 without urea. The differences in the number of shoots produced were significant and these shoots readily rooted in MS media with NAA (4 mg/L). Primary and secondary hardening was successful in these plants. There were no visible morphological abnormalities observed in the micropropagated plantlets. Genetic analysis from random samples also revealed that these plants are genetically uniform. The advantage of the present protocol is that the complete process of multiple shoot induction, rooting and hardening could be completed within a period of 6 months as compared to the existing protocols.

  20. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

    Sawcer, Stephen; Hellenthal, Garrett; Pirinen, Matti; Spencer, Chris C.A.; Patsopoulos, Nikolaos A.; Moutsianas, Loukas; Dilthey, Alexander; Su, Zhan; Freeman, Colin; Hunt, Sarah E.; Edkins, Sarah; Gray, Emma; Booth, David R.; Potter, Simon C.; Goris, An; Band, Gavin; Oturai, Annette Bang; Strange, Amy; Saarela, Janna; Bellenguez, Céline; Fontaine, Bertrand; Gillman, Matthew; Hemmer, Bernhard; Gwilliam, Rhian; Zipp, Frauke; Jayakumar, Alagurevathi; Martin, Roland; Leslie, Stephen; Hawkins, Stanley; Giannoulatou, Eleni; D’alfonso, Sandra; Blackburn, Hannah; Boneschi, Filippo Martinelli; Liddle, Jennifer; Harbo, Hanne F.; Perez, Marc L.; Spurkland, Anne; Waller, Matthew J; Mycko, Marcin P.; Ricketts, Michelle; Comabella, Manuel; Hammond, Naomi; Kockum, Ingrid; McCann, Owen T.; Ban, Maria; Whittaker, Pamela; Kemppinen, Anu; Weston, Paul; Hawkins, Clive; Widaa, Sara; Zajicek, John; Dronov, Serge; Robertson, Neil; Bumpstead, Suzannah J.; Barcellos, Lisa F.; Ravindrarajah, Rathi; Abraham, Roby; Alfredsson, Lars; Ardlie, Kristin; Aubin, Cristin; Baker, Amie; Baker, Katharine; Baranzini, Sergio E.; Bergamaschi, Laura; Bergamaschi, Roberto; Bernstein, Allan; Berthele, Achim; Boggild, Mike; Bradfield, Jonathan P.; Brassat, David; Broadley, Simon A.; Buck, Dorothea; Butzkueven, Helmut; Capra, Ruggero; Carroll, William M.; Cavalla, Paola; Celius, Elisabeth G.; Cepok, Sabine; Chiavacci, Rosetta; Clerget-Darpoux, Françoise; Clysters, Katleen; Comi, Giancarlo; Cossburn, Mark; Cournu-Rebeix, Isabelle; Cox, Mathew B.; Cozen, Wendy; Cree, Bruce A.C.; Cross, Anne H.; Cusi, Daniele; Daly, Mark J.; Davis, Emma; de Bakker, Paul I.W.; Debouverie, Marc; D’hooghe, Marie Beatrice; Dixon, Katherine; Dobosi, Rita; Dubois, Bénédicte; Ellinghaus, David; Elovaara, Irina; Esposito, Federica; Fontenille, Claire; Foote, Simon; Franke, Andre; Galimberti, Daniela; Ghezzi, Angelo; Glessner, Joseph; Gomez, Refujia; Gout, Olivier; Graham, Colin; Grant, Struan F.A.; Guerini, Franca Rosa; Hakonarson, Hakon; Hall, Per; Hamsten, Anders; Hartung, Hans-Peter; Heard, Rob N.; Heath, Simon; Hobart, Jeremy; Hoshi, Muna; Infante-Duarte, Carmen; Ingram, Gillian; Ingram, Wendy; Islam, Talat; Jagodic, Maja; Kabesch, Michael; Kermode, Allan G.; Kilpatrick, Trevor J.; Kim, Cecilia; Klopp, Norman; Koivisto, Keijo; Larsson, Malin; Lathrop, Mark; Lechner-Scott, Jeannette S.; Leone, Maurizio A.; Leppä, Virpi; Liljedahl, Ulrika; Bomfim, Izaura Lima; Lincoln, Robin R.; Link, Jenny; Liu, Jianjun; Lorentzen, Åslaug R.; Lupoli, Sara; Macciardi, Fabio; Mack, Thomas; Marriott, Mark; Martinelli, Vittorio; Mason, Deborah; McCauley, Jacob L.; Mentch, Frank; Mero, Inger-Lise; Mihalova, Tania; Montalban, Xavier; Mottershead, John; Myhr, Kjell-Morten; Naldi, Paola; Ollier, William; Page, Alison; Palotie, Aarno; Pelletier, Jean; Piccio, Laura; Pickersgill, Trevor; Piehl, Fredrik; Pobywajlo, Susan; Quach, Hong L.; Ramsay, Patricia P.; Reunanen, Mauri; Reynolds, Richard; Rioux, John D.; Rodegher, Mariaemma; Roesner, Sabine; Rubio, Justin P.; Rückert, Ina-Maria; Salvetti, Marco; Salvi, Erika; Santaniello, Adam; Schaefer, Catherine A.; Schreiber, Stefan; Schulze, Christian; Scott, Rodney J.; Sellebjerg, Finn; Selmaj, Krzysztof W.; Sexton, David; Shen, Ling; Simms-Acuna, Brigid; Skidmore, Sheila; Sleiman, Patrick M.A.; Smestad, Cathrine; Sørensen, Per Soelberg; Søndergaard, Helle Bach; Stankovich, Jim; Strange, Richard C.; Sulonen, Anna-Maija; Sundqvist, Emilie; Syvänen, Ann-Christine; Taddeo, Francesca; Taylor, Bruce; Blackwell, Jenefer M.; Tienari, Pentti; Bramon, Elvira; Tourbah, Ayman; Brown, Matthew A.; Tronczynska, Ewa; Casas, Juan P.; Tubridy, Niall; Corvin, Aiden; Vickery, Jane; Jankowski, Janusz; Villoslada, Pablo; Markus, Hugh S.; Wang, Kai; Mathew, Christopher G.; Wason, James; Palmer, Colin N.A.; Wichmann, H-Erich; Plomin, Robert; Willoughby, Ernest; Rautanen, Anna; Winkelmann, Juliane; Wittig, Michael; Trembath, Richard C.; Yaouanq, Jacqueline; Viswanathan, Ananth C.; Zhang, Haitao; Wood, Nicholas W.; Zuvich, Rebecca; Deloukas, Panos; Langford, Cordelia; Duncanson, Audrey; Oksenberg, Jorge R.; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Olsson, Tomas; Hillert, Jan; Ivinson, Adrian J.; De Jager, Philip L.; Peltonen, Leena; Stewart, Graeme J.; Hafler, David A.; Hauser, Stephen L.; McVean, Gil; Donnelly, Peter; Compston, Alastair

    2011-01-01

    Multiple sclerosis (OMIM 126200) is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability.1 Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals;2,3 and systematic attempts to identify linkage in multiplex families have confirmed that variation within the Major Histocompatibility Complex (MHC) exerts the greatest individual effect on risk.4 Modestly powered Genome-Wide Association Studies (GWAS)5-10 have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects play a key role in disease susceptibility.11 Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the Class I region. Immunologically relevant genes are significantly over-represented amongst those mapping close to the identified loci and particularly implicate T helper cell differentiation in the pathogenesis of multiple sclerosis. PMID:21833088

  1. Simulating pattern-process relationships to validate landscape genetic models

    A. J. Shirk; S. A. Cushman; E. L. Landguth

    2012-01-01

    Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

  2. Multiple Scenario Generation of Subsurface Models

    Cordua, Knud Skou

    of information is obeyed such that no unknown assumptions and biases influence the solution to the inverse problem. This involves a definition of the probabilistically formulated inverse problem, a discussion about how prior models can be established based on statistical information from sample models...... of the probabilistic formulation of the inverse problem. This function is based on an uncertainty model that describes the uncertainties related to the observed data. In a similar way, a formulation of the prior probability distribution that takes into account uncertainties related to the sample model statistics...... similar to observation uncertainties. We refer to the effect of these approximations as modeling errors. Examples that show how the modeling error is estimated are provided. Moreover, it is shown how these effects can be taken into account in the formulation of the posterior probability distribution...

  3. Multiple system modelling of waste management

    Eriksson, Ola; Bisaillon, Mattias

    2011-01-01

    Highlights: → Linking of models will provide a more complete, correct and credible picture of the systems. → The linking procedure is easy to perform and also leads to activation of project partners. → The simulation procedure is a bit more complicated and calls for the ability to run both models. - Abstract: Due to increased environmental awareness, planning and performance of waste management has become more and more complex. Therefore waste management has early been subject to different types of modelling. Another field with long experience of modelling and systems perspective is energy systems. The two modelling traditions have developed side by side, but so far there are very few attempts to combine them. Waste management systems can be linked together with energy systems through incineration plants. The models for waste management can be modelled on a quite detailed level whereas surrounding systems are modelled in a more simplistic way. This is a problem, as previous studies have shown that assumptions on the surrounding system often tend to be important for the conclusions. In this paper it is shown how two models, one for the district heating system (MARTES) and another one for the waste management system (ORWARE), can be linked together. The strengths and weaknesses with model linking are discussed when compared to simplistic assumptions on effects in the energy and waste management systems. It is concluded that the linking of models will provide a more complete, correct and credible picture of the consequences of different simultaneous changes in the systems. The linking procedure is easy to perform and also leads to activation of project partners. However, the simulation procedure is a bit more complicated and calls for the ability to run both models.

  4. Mean multiplicity in the Regge models with rising cross sections

    Chikovani, Z.E.; Kobylisky, N.A.; Martynov, E.S.

    1979-01-01

    Behaviour of the mean multiplicity and the total cross section σsub(t) of hadron-hadron interactions is considered in the framework of the Regge models at high energies. Generating function was plotted for models of dipole and froissaron, and the mean multiplicity and multiplicity moments were calculated. It is shown that approximately ln 2 S (energy square) in the dipole model, which is in good agreement with the experiment. It is also found that in various Regge models approximately σsub(t)lnS

  5. Comparing ESC and iPSC?Based Models for Human Genetic Disorders

    Halevy, Tomer; Urbach, Achia

    2014-01-01

    Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients’ somatic cells, and the ne...

  6. Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

    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.

  7. Discrete choice models with multiplicative error terms

    Fosgerau, Mogens; Bierlaire, Michel

    2009-01-01

    The conditional indirect utility of many random utility maximization (RUM) discrete choice models is specified as a sum of an index V depending on observables and an independent random term ε. In general, the universe of RUM consistent models is much larger, even fixing some specification of V due...

  8. Comparing estimates of genetic variance across different relationship models.

    Legarra, Andres

    2016-02-01

    Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Multiple-lesion track-structure model

    Wilson, J.W.; Cucinotta, F.A.; Shinn, J.L.

    1992-03-01

    A multilesion cell kinetic model is derived, and radiation kinetic coefficients are related to the Katz track structure model. The repair-related coefficients are determined from the delayed plating experiments of Yang et al. for the C3H10T1/2 cell system. The model agrees well with the x ray and heavy ion experiments of Yang et al. for the immediate plating, delaying plating, and fractionated exposure protocols employed by Yang. A study is made of the effects of target fragments in energetic proton exposures and of the repair-deficient target-fragment-induced lesions

  10. Affine LIBOR Models with Multiple Curves

    Grbac, Zorana; Papapantoleon, Antonis; Schoenmakers, John

    2015-01-01

    are specified following the methodology of the affine LIBOR models and are driven by the wide and flexible class of affine processes. The affine property is preserved under forward measures, which allows us to derive Fourier pricing formulas for caps, swaptions, and basis swaptions. A model specification...... with dependent LIBOR rates is developed that allows for an efficient and accurate calibration to a system of caplet prices....

  11. Non-linear nuclear engineering models as genetic programming application

    Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

    1997-01-01

    This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

  12. Numeral eddy current sensor modelling based on genetic neural network

    Yu Along

    2008-01-01

    This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method

  13. PM Synchronous Motor Dynamic Modeling with Genetic Algorithm ...

    Adel

    This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous ... Simulations are implemented using MATLAB with its genetic algorithm toolbox. .... selection, the process that drives biological evolution.

  14. SDG and qualitative trend based model multiple scale validation

    Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

    2017-09-01

    Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

  15. Modelling of rate effects at multiple scales

    Pedersen, R.R.; Simone, A.; Sluys, L. J.

    2008-01-01

    , the length scale in the meso-model and the macro-model can be coupled. In this fashion, a bridging of length scales can be established. A computational analysis of  a Split Hopkinson bar test at medium and high impact load is carried out at macro-scale and meso-scale including information from  the micro-scale.......At the macro- and meso-scales a rate dependent constitutive model is used in which visco-elasticity is coupled to visco-plasticity and damage. A viscous length scale effect is introduced to control the size of the fracture process zone. By comparison of the widths of the fracture process zone...

  16. TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis

    Gregory, Adam P; Dendrou, Calliope A; Attfield, Kathrine E

    2012-01-01

    ), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further...... make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS...... substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases...

  17. Genetic educational needs and the role of genetics in primary care: a focus group study with multiple perspectives

    van der Vleuten Cees

    2011-02-01

    Full Text Available Abstract Background Available evidence suggests that improvements in genetics education are needed to prepare primary care providers for the impact of ongoing rapid advances in genomics. Postgraduate (physician training and master (midwifery training programmes in primary care and public health are failing to meet these perceived educational needs. The aim of this study was to explore the role of genetics in primary care (i.e. family medicine and midwifery care and the need for education in this area as perceived by primary care providers, patient advocacy groups and clinical genetics professionals. Methods Forty-four participants took part in three types of focus groups: mono-disciplinary groups of general practitioners and midwives, respectively and multidisciplinary groups composed of a diverse set of experts. The focus group sessions were audio-taped, transcribed verbatim and analysed using content analysis. Recurrent themes were identified. Results Four themes emerged regarding the educational needs and the role of genetics in primary care: (1 genetics knowledge, (2 family history, (3 ethical dilemmas and psychosocial effects in relation to genetics and (4 insight into the organisation and role of clinical genetics services. These themes reflect a shift in the role of genetics in primary care with implications for education. Although all focus group participants acknowledged the importance of genetics education, general practitioners felt this need more urgently than midwives and more strongly emphasized their perceived knowledge deficiencies. Conclusion The responsibilities of primary care providers with regard to genetics require further study. The results of this study will help to develop effective genetics education strategies to improve primary care providers' competencies in this area. More research into the educational priorities in genetics is needed to design courses that are suitable for postgraduate and master programmes for

  18. Parametric optimization of multiple quality characteristics in laser cutting of Inconel-718 by using hybrid approach of multiple regression analysis and genetic algorithm

    Shrivastava, Prashant Kumar; Pandey, Arun Kumar

    2018-06-01

    Inconel-718 has found high demand in different industries due to their superior mechanical properties. The traditional cutting methods are facing difficulties for cutting these alloys due to their low thermal potential, lower elasticity and high chemical compatibility at inflated temperature. The challenges of machining and/or finishing of unusual shapes and/or sizes in these materials have also faced by traditional machining. Laser beam cutting may be applied for the miniaturization and ultra-precision cutting and/or finishing by appropriate control of different process parameter. This paper present multi-objective optimization the kerf deviation, kerf width and kerf taper in the laser cutting of Incone-718 sheet. The second order regression models have been developed for different quality characteristics by using the experimental data obtained through experimentation. The regression models have been used as objective function for multi-objective optimization based on the hybrid approach of multiple regression analysis and genetic algorithm. The comparison of optimization results to experimental results shows an improvement of 88%, 10.63% and 42.15% in kerf deviation, kerf width and kerf taper, respectively. Finally, the effects of different process parameters on quality characteristics have also been discussed.

  19. Common genetic variants in the 9p21 region and their associations with multiple tumours.

    Gu, F; Pfeiffer, R M; Bhattacharjee, S; Han, S S; Taylor, P R; Berndt, S; Yang, H; Sigurdson, A J; Toro, J; Mirabello, L; Greene, M H; Freedman, N D; Abnet, C C; Dawsey, S M; Hu, N; Qiao, Y-L; Ding, T; Brenner, A V; Garcia-Closas, M; Hayes, R; Brinton, L A; Lissowska, J; Wentzensen, N; Kratz, C; Moore, L E; Ziegler, R G; Chow, W-H; Savage, S A; Burdette, L; Yeager, M; Chanock, S J; Chatterjee, N; Tucker, M A; Goldstein, A M; Yang, X R

    2013-04-02

    The chromosome 9p21.3 region has been implicated in the pathogenesis of multiple cancers. We systematically examined up to 203 tagging SNPs of 22 genes on 9p21.3 (19.9-32.8 Mb) in eight case-control studies: thyroid cancer, endometrial cancer (EC), renal cell carcinoma, colorectal cancer (CRC), colorectal adenoma (CA), oesophageal squamous cell carcinoma (ESCC), gastric cardia adenocarcinoma and osteosarcoma (OS). We used logistic regression to perform single SNP analyses for each study separately, adjusting for study-specific covariates. We combined SNP results across studies by fixed-effect meta-analyses and a newly developed subset-based statistical approach (ASSET). Gene-based P-values were obtained by the minP method using the Adaptive Rank Truncated Product program. We adjusted for multiple comparisons by Bonferroni correction. Rs3731239 in cyclin-dependent kinase inhibitors 2A (CDKN2A) was significantly associated with ESCC (P=7 × 10(-6)). The CDKN2A-ESCC association was further supported by gene-based analyses (Pgene=0.0001). In the meta-analyses by ASSET, four SNPs (rs3731239 in CDKN2A, rs615552 and rs573687 in CDKN2B and rs564398 in CDKN2BAS) showed significant associations with ESCC and EC (PASSET (P=0.007). Our data indicate that genetic variants in CDKN2A, and possibly nearby genes, may be associated with ESCC and several other tumours, further highlighting the importance of 9p21.3 genetic variants in carcinogenesis.

  20. New experimental model of multiple myeloma.

    Telegin, G B; Kalinina, A R; Ponomarenko, N A; Ovsepyan, A A; Smirnov, S V; Tsybenko, V V; Homeriki, S G

    2001-06-01

    NSO/1 (P3x63Ay 8Ut) and SP20 myeloma cells were inoculated to BALB/c OlaHsd mice. NSO/1 cells allowed adequate stage-by-stage monitoring of tumor development. The adequacy of this model was confirmed in experiments with conventional cytostatics: prospidium and cytarabine caused necrosis of tumor cells and reduced animal mortality.

  1. Animal model of human disease. Multiple myeloma

    Radl, J.; Croese, J.W.; Zurcher, C.; Enden-Vieveen, M.H.M. van den; Leeuw, A.M. de

    1988-01-01

    Animal models of spontaneous and induced plasmacytomas in some inbred strains of mice have proven to be useful tools for different studies on tumorigenesis and immunoregulation. Their wide applicability and the fact that after their intravenous transplantation, the recipient mice developed bone

  2. Genetic and demographic responses of mosquitofish (Gambusia holbrooki) populations exposed to mercury for multiple generations

    Tatara, C.P.; Mulvey, M.; Newman, M.C.

    1999-12-01

    Genetic and demographic responses of mosquitofish were examined after multiple generations of exposure to mercury. Previous studies of acute lethal exposures of mosquitofish to either mercury or arsenic demonstrated a consistent correlation between time to death and genotype at the glucosephosphate isomerase-2 (Gpi-2) locus. A mesocosm study involving mosquitofish populations exposed to mercury for 111 d showed significant female sexual selection and fecundity selection at the Gpi-2 locus. Here the mesocosm study was extended to populations exposed to mercury for several (approx. four) generations. After 2 years, control and mercury-exposed populations met Hardy-Weinberg expectations and showed no evidence of genetic bottlenecks. The mean number of heterozygous loci did not differ significantly between the mercury-exposed and control populations. Significant differences in allele frequencies at the Gpi-2 locus were observed between the mercury-exposed and control populations. Relative to the initial and control allele frequencies, the GPI-2{sup 100} allele frequency was lower, the Gpi-2{sup 66} allele frequency increased, but the Gpi-2{sup 38} allele frequency did not change in mercury-exposed populations. No significant differences were found in standard length, weight, sex ratio, or age class ratio between the control and mercury-exposed populations. Allele frequency changes at the Gpi-2 locus suggest population-level response to chronic mercury exposure. Changes in allele frequency may be useful as indicators of population response to contaminants, provided that the population in question is well understood.

  3. Multiple Social Networks, Data Models and Measures for

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  4. Modeling Rabbit Responses to Single and Multiple Aerosol ...

    Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

  5. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

    Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

    2016-01-01

    Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

  6. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

    Shiori Yabe

    Full Text Available Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS, which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the

  7. Explaining clinical behaviors using multiple theoretical models

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-01-01

    Abstract Background In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of...

  8. Airport choice model in multiple airport regions

    Claudia Muñoz

    2017-02-01

    Full Text Available Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory. Design/methodology/approach: This research generates a Multinomial Logit Model (MNL, which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia. This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH Airport and José María Córdova (JMC Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport. Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

  9. Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

    Dechow, C D; Rogers, G W

    2018-05-01

    Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  10. Multiple simultaneous event model for radiation carcinogenesis

    Baum, J.W.

    1976-01-01

    A mathematical model is proposed which postulates that cancer induction is a multi-event process, that these events occur naturally, usually one at a time in any cell, and that radiation frequently causes two of these events to occur simultaneously. Microdosimetric considerations dictate that for high LET radiations the simultaneous events are associated with a single particle or track. The model predicts: (a) linear dose-effect relations for early times after irradiation with small doses, (b) approximate power functions of dose (i.e. Dsup(x)) having exponent less than one for populations of mixed age examined at short times after irradiation with small doses, (c) saturation of effect at either long times after irradiation with small doses or for all times after irradiation with large doses, and (d) a net increase in incidence which is dependent on age of observation but independent of age at irradiation. Data of Vogel, for neutron induced mammary tumors in rats, are used to illustrate the validity of the formulation. This model provides a quantitative framework to explain several unexpected results obtained by Vogel. It also provides a logical framework to explain the dose-effect relations observed in the Japanese survivors of the atomic bombs. (author)

  11. Genetic Resources in the “Calabaza Pipiana” Squash (Cucurbita argyrosperma) in Mexico: Genetic Diversity, Genetic Differentiation and Distribution Models

    Sánchez-de la Vega, Guillermo; Castellanos-Morales, Gabriela; Gámez, Niza; Hernández-Rosales, Helena S.; Vázquez-Lobo, Alejandra; Aguirre-Planter, Erika; Jaramillo-Correa, Juan P.; Montes-Hernández, Salvador; Lira-Saade, Rafael; Eguiarte, Luis E.

    2018-01-01

    Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites) to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs) for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago) to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma). Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST) among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango). We detected low levels of gene

  12. Genetic Resources in the “Calabaza Pipiana” Squash (Cucurbita argyrosperma in Mexico: Genetic Diversity, Genetic Differentiation and Distribution Models

    Guillermo Sánchez-de la Vega

    2018-03-01

    Full Text Available Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma. Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango. We detected low

  13. Multiple Imputation of Predictor Variables Using Generalized Additive Models

    de Jong, Roel; van Buuren, Stef; Spiess, Martin

    2016-01-01

    The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

  14. The genetic analysis of repeated measures I: Simplex models

    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,

  15. Entrepreneurial intention modeling using hierarchical multiple regression

    Marina Jeger

    2014-12-01

    Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

  16. Characterization of recombination features and the genetic basis in multiple cattle breeds.

    Shen, Botong; Jiang, Jicai; Seroussi, Eyal; Liu, George E; Ma, Li

    2018-04-27

    Crossover generated by meiotic recombination is a fundamental event that facilitates meiosis and sexual reproduction. Comparative studies have shown wide variation in recombination rate among species, but the characterization of recombination features between cattle breeds has not yet been performed. Cattle populations in North America count millions, and the dairy industry has genotyped millions of individuals with pedigree information that provide a unique opportunity to study breed-level variations in recombination. Based on large pedigrees of Jersey, Ayrshire and Brown Swiss cattle with genotype data, we identified over 3.4 million maternal and paternal crossover events from 161,309 three-generation families. We constructed six breed- and sex-specific genome-wide recombination maps using 58,982 autosomal SNPs for two sexes in the three dairy cattle breeds. A comparative analysis of the six recombination maps revealed similar global recombination patterns between cattle breeds but with significant differences between sexes. We confirmed that male recombination map is 10% longer than the female map in all three cattle breeds, consistent with previously reported results in Holstein cattle. When comparing recombination hotspot regions between cattle breeds, we found that 30% and 10% of the hotspots were shared between breeds in males and females, respectively, with each breed exhibiting some breed-specific hotspots. Finally, our multiple-breed GWAS found that SNPs in eight loci affected recombination rate and that the PRDM9 gene associated with hotspot usage in multiple cattle breeds, indicating a shared genetic basis for recombination across dairy cattle breeds. Collectively, our results generated breed- and sex-specific recombination maps for multiple cattle breeds, provided a comprehensive characterization and comparison of recombination patterns between breeds, and expanded our understanding of the breed-level variations in recombination features within an

  17. Multiple Time Series Ising Model for Financial Market Simulations

    Takaishi, Tetsuya

    2015-01-01

    In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated

  18. Genetic and non-genetic animal models for autism spectrum disorders (ASD).

    Ergaz, Zivanit; Weinstein-Fudim, Liza; Ornoy, Asher

    2016-09-01

    Autism spectrum disorder (ASD) is associated, in addition to complex genetic factors, with a variety of prenatal, perinatal and postnatal etiologies. We discuss the known animal models, mostly in mice and rats, of ASD that helps us to understand the etiology, pathogenesis and treatment of human ASD. We describe only models where behavioral testing has shown autistic like behaviors. Some genetic models mimic known human syndromes like fragile X where ASD is part of the clinical picture, and others are without defined human syndromes. Among the environmentally induced ASD models in rodents, the most common model is the one induced by valproic acid (VPA) either prenatally or early postnatally. VPA induces autism-like behaviors following single exposure during different phases of brain development, implying that the mechanism of action is via a general biological mechanism like epigenetic changes. Maternal infection and inflammation are also associated with ASD in man and animal models. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Invited review: Genetic and genomic mouse models for livestock research

    D. Arends

    2018-02-01

    Full Text Available Knowledge about the function and functioning of single or multiple interacting genes is of the utmost significance for understanding the organism as a whole and for accurate livestock improvement through genomic selection. This includes, but is not limited to, understanding the ontogenetic and environmentally driven regulation of gene action contributing to simple and complex traits. Genetically modified mice, in which the functions of single genes are annotated; mice with reduced genetic complexity; and simplified structured populations are tools to gain fundamental knowledge of inheritance patterns and whole system genetics and genomics. In this review, we briefly describe existing mouse resources and discuss their value for fundamental and applied research in livestock.

  20. Population genetics of Setaria viridis, a new model system.

    Huang, Pu; Feldman, Maximilian; Schroder, Stephan; Bahri, Bochra A; Diao, Xianmin; Zhi, Hui; Estep, Matt; Baxter, Ivan; Devos, Katrien M; Kellogg, Elizabeth A

    2014-10-01

    An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a worldwide sample of more than 200 S. viridis accessions, using the genotyping-by-sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modelled demographic history and show signal of recent population decline in one subgroup. Finally, we show linkage disequilibrium decay is rapid (<45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genomewide association studies. © 2014 John Wiley & Sons Ltd.

  1. Correlations in multiple production on nuclei and Glauber model of multiple scattering

    Zoller, V.R.; Nikolaev, N.N.

    1982-01-01

    Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei

  2. Genetic complexity and multiple infections with more Parvovirus species in naturally infected cats

    Battilani Mara

    2011-03-01

    Full Text Available Abstract Parvoviruses of carnivores include three closely related autonomous parvoviruses: canine parvovirus (CPV, feline panleukopenia virus (FPV and mink enteritis virus (MEV. These viruses cause a variety of serious diseases, especially in young patients, since they have a remarkable predilection for replication in rapidly dividing cells. FPV is not the only parvovirus species which infects cats; in addition to MEV, the new variants of canine parvovirus, CPV-2a, 2b and 2c have also penetrated the feline host-range, and they are able to infect and replicate in cats, causing diseases indistinguishable from feline panleukopenia. Furthermore, as cats are susceptible to both CPV-2 and FPV viruses, superinfection and co-infection with multiple parvovirus strains may occur, potentially facilitating recombination and high genetic heterogeneity. In the light of the importance of cats as a potential source of genetic diversity for parvoviruses and, since feline panleukopenia virus has re-emerged as a major cause of mortality in felines, the present study has explored the molecular characteristics of parvovirus strains circulating in cat populations. The most significant findings reported in this study were (a the detection of mixed infection FPV/CPV with the presence of one parvovirus variant which is a true intermediate between FPV/CPV and (b the quasispecies cloud size of one CPV sample variant 2c. In conclusion, this study provides new important results about the evolutionary dynamics of CPV infections in cats, showing that CPV has presumably started a new process of readaptation in feline hosts.

  3. Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients

    James, Tojo

    2018-01-06

    Despite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as Multiple Sclerosis (MS). Since a large proportion of expression quantitative trait loci (eQTLs) are context-specific, we performed RNA-Seq in peripheral blood mononuclear cells (PBMCs) from MS patients (n=145) to identify eQTLs in regions centered on 109 MS risk SNPs and seven associated HLA variants. We identified 77 statistically significant eQTL associations, including pseudogenes and non-coding RNAs. Thirty-eight out of 40 testable eQTL effects were colocalised with the disease association signal. Since many eQTLs are tissue specific, we aimed to detail their significance in different cell types. Approximately 70% of the eQTLs were replicated and characterized in at least one major PBMC derived cell type. Furthermore, 40% of eQTLs were found to be more pronounced in MS patients compared to noninflammatory neurological diseases patients. In addition, we found two SNPs to be significantly associated with the proportions of three different cell types. Mapping to enhancer histone marks and predicted transcription factor binding sites added additional functional evidence for eight eQTL regions. As an example, we found that rs71624119, shared with three other autoimmune diseases and located in a primed enhancer (H3K4me1) with potential binding for STAT transcription factors, significantly associates with ANKRD55 expression. This study provides many novel and validated targets for future functional characterization of MS and other diseases.

  4. QSAR study of HCV NS5B polymerase inhibitors using the genetic algorithm-multiple linear regression (GA-MLR).

    Rafiei, Hamid; Khanzadeh, Marziyeh; Mozaffari, Shahla; Bostanifar, Mohammad Hassan; Avval, Zhila Mohajeri; Aalizadeh, Reza; Pourbasheer, Eslam

    2016-01-01

    Quantitative structure-activity relationship (QSAR) study has been employed for predicting the inhibitory activities of the Hepatitis C virus (HCV) NS5B polymerase inhibitors . A data set consisted of 72 compounds was selected, and then different types of molecular descriptors were calculated. The whole data set was split into a training set (80 % of the dataset) and a test set (20 % of the dataset) using principle component analysis. The stepwise (SW) and the genetic algorithm (GA) techniques were used as variable selection tools. Multiple linear regression method was then used to linearly correlate the selected descriptors with inhibitory activities. Several validation technique including leave-one-out and leave-group-out cross-validation, Y-randomization method were used to evaluate the internal capability of the derived models. The external prediction ability of the derived models was further analyzed using modified r(2), concordance correlation coefficient values and Golbraikh and Tropsha acceptable model criteria's. Based on the derived results (GA-MLR), some new insights toward molecular structural requirements for obtaining better inhibitory activity were obtained.

  5. Multiple Response Regression for Gaussian Mixture Models with Known Labels.

    Lee, Wonyul; Du, Ying; Sun, Wei; Hayes, D Neil; Liu, Yufeng

    2012-12-01

    Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data. In many applications, however, one may have heterogeneous data where the samples are divided into multiple groups. Our motivating example is a cancer dataset where the samples belong to multiple cancer subtypes. In this paper, we consider modeling the data coming from a mixture of several Gaussian distributions with known group labels. A naive approach is to split the data into several groups according to the labels and model each group separately. Although it is simple, this approach ignores potential common structures across different groups. We propose new penalized methods to model all groups jointly in which the common and unique structures can be identified. The proposed methods estimate the regression coefficient matrix, as well as the conditional inverse covariance matrix of response variables. Asymptotic properties of the proposed methods are explored. Through numerical examples, we demonstrate that both estimation and prediction can be improved by modeling all groups jointly using the proposed methods. An application to a glioblastoma cancer dataset reveals some interesting common and unique gene relationships across different cancer subtypes.

  6. Genetics of traffic assignment models for strategic transport planning

    Bliemer, M.C.J.; Raadsen, M.P.H.; Brederode, L.J.N.; Bell, M.G.H.; Wismans, Luc Johannes Josephus; Smith, M.J.

    2016-01-01

    This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic

  7. Genetic models of absence epilepsy: New concepts and insights

    Luijtelaar, E.L.J.M. van; Coenen, A.M.L.; Schwartzkroin, P.A.

    2009-01-01

    The discovery, development, and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures. A focal zone has been identified in the peri-oral region of the somatosensory cortex in WAG/Rij and GAERS – the two most commonly used models – from which

  8. CRISPR/Cas9 : A molecular Swiss army knife for simultaneous introduction of multiple genetic modifications in Saccharomyces cerevisiae

    Mans, R.; Van Rossum, H.M.; Wijsman, M.; Backx, A.; Kuijpers, N.G.A.; van den Broek, M.; Daran-Lapujade, P.A.S.; Pronk, J.T.; Van Maris, A.J.A.; Daran, J.G.

    2015-01-01

    A variety of techniques for strain engineering in Saccharomyces cerevisiae have recently been developed. However, especially when multiple genetic manipulations are required, strain construction is still a time-consuming process. This study describes new CRISPR/Cas9-based approaches for easy, fast

  9. Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

    Quanzhen Huang

    2017-01-01

    Full Text Available Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

  10. Efficient Adoption and Assessment of Multiple Process Improvement Reference Models

    Simona Jeners

    2013-06-01

    Full Text Available A variety of reference models such as CMMI, COBIT or ITIL support IT organizations to improve their processes. These process improvement reference models (IRMs cover different domains such as IT development, IT Services or IT Governance but also share some similarities. As there are organizations that address multiple domains and need to coordinate their processes in their improvement we present MoSaIC, an approach to support organizations to efficiently adopt and conform to multiple IRMs. Our solution realizes a semantic integration of IRMs based on common meta-models. The resulting IRM integration model enables organizations to efficiently implement and asses multiple IRMs and to benefit from synergy effects.

  11. Applicability of genetic algorithms to parameter estimation of economic models

    Marcel Ševela

    2004-01-01

    Full Text Available The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear economic models. In the paper we test the ability of genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for parameters of genetic algorithm that lead to maximum effectiveness of the computation algorithm. The genetic algorithms connect deterministic iterative computation methods with stochastic methods. In the genteic aůgorithm approach each possible solution is represented by one individual, those life and lifes of all generations of individuals run under a few parameter of genetic algorithm. Our simulations resulted in optimal mutation rate of 15% of all bits in chromosomes, optimal elitism rate 20%. We can not set the optimal extend of generation, because it proves positive correlation with effectiveness of genetic algorithm in all range under research, but its impact is degreasing. The used genetic algorithm was sensitive to mutation rate at most, than to extend of generation. The sensitivity to elitism rate is not so strong.

  12. Drag reduction of a car model by linear genetic programming control

    Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

    2017-08-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

  13. A simple method for combining genetic mapping data from multiple crosses and experimental designs.

    Jeremy L Peirce

    Full Text Available BACKGROUND: Over the past decade many linkage studies have defined chromosomal intervals containing polymorphisms that modulate a variety of traits. Many phenotypes are now associated with enough mapping data that meta-analysis could help refine locations of known QTLs and detect many novel QTLs. METHODOLOGY/PRINCIPAL FINDINGS: We describe a simple approach to combining QTL mapping results for multiple studies and demonstrate its utility using two hippocampus weight loci. Using data taken from two populations, a recombinant inbred strain set and an advanced intercross population we demonstrate considerable improvements in significance and resolution for both loci. 1-LOD support intervals were improved 51% for Hipp1a and 37% for Hipp9a. We first generate locus-wise permuted P-values for association with the phenotype from multiple maps, which can be done using a permutation method appropriate to each population. These results are then assigned to defined physical positions by interpolation between markers with known physical and genetic positions. We then use Fisher's combination test to combine position-by-position probabilities among experiments. Finally, we calculate genome-wide combined P-values by generating locus-specific P-values for each permuted map for each experiment. These permuted maps are then sampled with replacement and combined. The distribution of best locus-specific P-values for each combined map is the null distribution of genome-wide adjusted P-values. CONCLUSIONS/SIGNIFICANCE: Our approach is applicable to a wide variety of segregating and non-segregating mapping populations, facilitates rapid refinement of physical QTL position, is complementary to other QTL fine mapping methods, and provides an appropriate genome-wide criterion of significance for combined mapping results.

  14. A Next-Generation Sequencing Strategy for Evaluating the Most Common Genetic Abnormalities in Multiple Myeloma.

    Jiménez, Cristina; Jara-Acevedo, María; Corchete, Luis A; Castillo, David; Ordóñez, Gonzalo R; Sarasquete, María E; Puig, Noemí; Martínez-López, Joaquín; Prieto-Conde, María I; García-Álvarez, María; Chillón, María C; Balanzategui, Ana; Alcoceba, Miguel; Oriol, Albert; Rosiñol, Laura; Palomera, Luis; Teruel, Ana I; Lahuerta, Juan J; Bladé, Joan; Mateos, María V; Orfão, Alberto; San Miguel, Jesús F; González, Marcos; Gutiérrez, Norma C; García-Sanz, Ramón

    2017-01-01

    Identification and characterization of genetic alterations are essential for diagnosis of multiple myeloma and may guide therapeutic decisions. Currently, genomic analysis of myeloma to cover the diverse range of alterations with prognostic impact requires fluorescence in situ hybridization (FISH), single nucleotide polymorphism arrays, and sequencing techniques, which are costly and labor intensive and require large numbers of plasma cells. To overcome these limitations, we designed a targeted-capture next-generation sequencing approach for one-step identification of IGH translocations, V(D)J clonal rearrangements, the IgH isotype, and somatic mutations to rapidly identify risk groups and specific targetable molecular lesions. Forty-eight newly diagnosed myeloma patients were tested with the panel, which included IGH and six genes that are recurrently mutated in myeloma: NRAS, KRAS, HRAS, TP53, MYC, and BRAF. We identified 14 of 17 IGH translocations previously detected by FISH and three confirmed translocations not detected by FISH, with the additional advantage of breakpoint identification, which can be used as a target for evaluating minimal residual disease. IgH subclass and V(D)J rearrangements were identified in 77% and 65% of patients, respectively. Mutation analysis revealed the presence of missense protein-coding alterations in at least one of the evaluating genes in 16 of 48 patients (33%). This method may represent a time- and cost-effective diagnostic method for the molecular characterization of multiple myeloma. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  15. Model Seleksi Premi Asuransi Jiwa Dwiguna untuk Kasus Multiple Decrement

    Cita, Devi Ramana; Pane, Rolan; ', Harison

    2015-01-01

    This article discusses a select survival model for the case of multiple decrements in evaluating endowment life insurance premium for person currently aged ( + ) years, who is selected at age with ℎ years selection period. The case of multiple decrements in this case is limited to two cases. The calculation of the annual premium is done by prior evaluating of the single premium, and the present value of annuity depends on theconstant force assumption.

  16. Model selection with multiple regression on distance matrices leads to incorrect inferences.

    Ryan P Franckowiak

    Full Text Available In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC, its small-sample correction (AICc, and the Bayesian information criterion (BIC to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

  17. Genetic heterogeneity in type 1 Gaucher disease: Multiple genotypes in Ashkenazic and non-Ashkenazic individuals

    Tsuji, Shoji; Martin, B.M.; Stubblefield, B.K.; LaMarca, M.E.; Ginns, E.I.; Barranger, J.A.

    1988-01-01

    Nucleotide sequence analysis of a genomic clone from an Ashkenazic Jewish patient with type 1 Gaucher disease revealed a single-base mutation (adenosine to guanosine transition) in exon 9 of the glucocerebrosidase gene. This change results in the amino acid substitution of serine for asparagine. Transient expression studies following oligonucleotide-directed mutagenesis of the normal cDNA confirmed that the mutation results in loss of glucocerebrosidase activity. Allele-specific hybridization with oligonucleotide probes demonstrated that this mutation was found exclusively in type 1 phenotype. None of the 6 type 2 patients, 11 type 3 patients, or 12 normal controls had this allele. In contrast, 15 of 24 type 1 patients had one allele with this mutation, and 3 others were homozygous for the mutation. Furthermore, some of the Ashkenazic Jewish type 1 patients had only one allele with this mutation, suggesting that even in this population there is allelic heterozygosity. These findings indicate that there are multiple allelic mutations responsible for type 1 Gaucher disease in both the Jewish and non-Jewish populations. Allelic-specific hybridization demonstrating this mutation in exon 9, used in conjunction with the Nci I restriction fragment length polymorphism described as a marker for neuronopathic Gaucher disease, provides a tool for diagnosis and genetic counseling that is ∼80% informative in all Gaucher patients studied

  18. Genetic heterogeneity in type 1 Gaucher disease: Multiple genotypes in Ashkenazic and non-Ashkenazic individuals

    Tsuji, Shoji; Martin, B.M.; Stubblefield, B.K.; LaMarca, M.E.; Ginns, E.I. (National Institute of Mental Health, Bethesda, MD (USA)); Barranger, J.A. (Childrens Hospital of Los Angeles, CA (USA))

    1988-04-01

    Nucleotide sequence analysis of a genomic clone from an Ashkenazic Jewish patient with type 1 Gaucher disease revealed a single-base mutation (adenosine to guanosine transition) in exon 9 of the glucocerebrosidase gene. This change results in the amino acid substitution of serine for asparagine. Transient expression studies following oligonucleotide-directed mutagenesis of the normal cDNA confirmed that the mutation results in loss of glucocerebrosidase activity. Allele-specific hybridization with oligonucleotide probes demonstrated that this mutation was found exclusively in type 1 phenotype. None of the 6 type 2 patients, 11 type 3 patients, or 12 normal controls had this allele. In contrast, 15 of 24 type 1 patients had one allele with this mutation, and 3 others were homozygous for the mutation. Furthermore, some of the Ashkenazic Jewish type 1 patients had only one allele with this mutation, suggesting that even in this population there is allelic heterozygosity. These findings indicate that there are multiple allelic mutations responsible for type 1 Gaucher disease in both the Jewish and non-Jewish populations. Allelic-specific hybridization demonstrating this mutation in exon 9, used in conjunction with the Nci I restriction fragment length polymorphism described as a marker for neuronopathic Gaucher disease, provides a tool for diagnosis and genetic counseling that is {approx}80% informative in all Gaucher patients studied.

  19. Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

    Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

    2018-04-01

    In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

  20. Preimplantation genetic diagnosis for Duchenne muscular dystrophy by multiple displacement amplification.

    Ren, Zi; Zeng, Hai-tao; Xu, Yan-wen; Zhuang, Guang-lun; Deng, Jie; Zhang, Cheng; Zhou, Can-quan

    2009-02-01

    To evaluate the use of multiple displacement amplification (MDA) in preimplantation genetic diagnosis (PGD) for female carriers with Duchenne muscular dystrophy (DMD). MDA was used to amplify a whole genome of single cells. Following the setup on single cells, the test was applied in two clinical cases of PGD. One mutant exon, six short tandem repeats (STR) markers within the dystrophin gene, and amelogenin were incorporated into singleplex polymerase chain reaction (PCR) assays on MDA products of single blastomeres. Center for reproductive medicine in First Affiliated Hospital, Sun Yat-sen University, China. Two female carriers with a duplication of exons 3-11 and a deletion of exons 47-50, respectively. The MDA of single cells and fluorescent PCR assays for PGD. The ability to analyze single blastomeres for DMD using MDA. The protocol setup previously allowed for the accurate diagnosis of each embryo. Two clinical cases resulted in a healthy girl, which was the first successful clinical application of MDA in PGD for DMD. We suggest that this protocol is reliable to increase the accuracy of the PGD for DMD.

  1. Visual detection of multiple genetically modified organisms in a capillary array.

    Shao, Ning; Chen, Jianwei; Hu, Jiaying; Li, Rong; Zhang, Dabing; Guo, Shujuan; Hui, Junhou; Liu, Peng; Yang, Litao; Tao, Sheng-Ce

    2017-01-31

    There is an urgent need for rapid, low-cost multiplex methodologies for the monitoring of genetically modified organisms (GMOs). Here, we report a C[combining low line]apillary A[combining low line]rray-based L[combining low line]oop-mediated isothermal amplification for M[combining low line]ultiplex visual detection of nucleic acids (CALM) platform for the simple and rapid monitoring of GMOs. In CALM, loop-mediated isothermal amplification (LAMP) primer sets are pre-fixed to the inner surface of capillaries. The surface of the capillary array is hydrophobic while the capillaries are hydrophilic, enabling the simultaneous loading and separation of the LAMP reaction mixtures into each capillary by capillary forces. LAMP reactions in the capillaries are then performed in parallel, and the results are visually detected by illumination with a hand-held UV device. Using CALM, we successfully detected seven frequently used transgenic genes/elements and five plant endogenous reference genes with high specificity and sensitivity. Moreover, we found that measurements of real-world blind samples by CALM are consistent with results obtained by independent real-time PCRs. Thus, with an ability to detect multiple nucleic acids in a single easy-to-operate test, we believe that CALM will become a widely applied technology in GMO monitoring.

  2. Multiple system atrophy: genetic risks and alpha-synuclein mutations [version 1; referees: 2 approved

    Heather T Whittaker

    2017-11-01

    Full Text Available Multiple system atrophy (MSA is one of the few neurodegenerative disorders where we have a significant understanding of the clinical and pathological manifestations but where the aetiology remains almost completely unknown. Research to overcome this hurdle is gaining momentum through international research collaboration and a series of genetic and molecular discoveries in the last few years, which have advanced our knowledge of this rare synucleinopathy. In MSA, the discovery of α-synuclein pathology and glial cytoplasmic inclusions remain the most significant findings. Families with certain types of α-synuclein mutations develop diseases that mimic MSA, and the spectrum of clinical and pathological features in these families suggests a spectrum of severity, from late-onset Parkinson’s disease to MSA. Nonetheless, controversies persist, such as the role of common α-synuclein variants in MSA and whether this disorder shares a common mechanism of spreading pathology with other protein misfolding neurodegenerative diseases. Here, we review these issues, specifically focusing on α-synuclein mutations.

  3. Genetic analysis of the isolated Faroe Islands reveals SORCS3 as a potential multiple sclerosis risk gene

    Binzer, Stefanie; Stenager, Egon; Binzer, Michael

    2016-01-01

    BACKGROUND: In search of the missing heritability in multiple sclerosis (MS), additional approaches adding to the genetic discoveries of large genome-wide association studies are warranted. OBJECTIVE: The objective of this research paper is to search for rare genetic MS risk variants...... in the genetically homogenous population of the isolated Faroe Islands. METHODS: Twenty-nine Faroese MS cases and 28 controls were genotyped with the HumanOmniExpressExome-chip. The individuals make up 1596 pair-combinations in which we searched for identical-by-descent shared segments using the PLINK...... of neurotrophin factors and involvement in glutamate homeostasis. Although additional work is needed to scrutinise the genetic effect of the SORCS3-covering haplotype, this study suggests that SORCS3 may also be important in MS pathogenesis....

  4. The Effect of Multiple Paternity on Genetic Diversity of Small Populations during and after Colonisation

    Rafajlović, Marina; Eriksson, Anders; Rimark, Anna; Hintz-Saltin, Sara; Charrier, Gré gory; Panova, Marina; André , Carl; Johannesson, Kerstin; Mehlig, Bernhard

    2013-01-01

    Genetic variation within and among populations is influenced by the genetic content of the founders and the migrants following establishment. This is particularly true if populations are small, migration rate low and habitats arranged in a stepping

  5. Genetic pathways to Neurodegeneration Models and mechanisms ...

    Paige Rudich

    Models and mechanisms of repeat expansion disorders: a worm's eye view ..... retardation 1 gene FMR1 gives rise to a spectrum of neurological disorders (Saul and Tarleton ... autism. Shorter repeat expansion lengths from 55-200 cause the.

  6. Multiplicative interaction of functional inflammasome genetic variants in determining the risk of gout.

    McKinney, Cushla; Stamp, Lisa K; Dalbeth, Nicola; Topless, Ruth K; Day, Richard O; Kannangara, Diluk Rw; Williams, Kenneth M; Janssen, Matthijs; Jansen, Timothy L; Joosten, Leo A; Radstake, Timothy R; Riches, Philip L; Tausche, Anne-Kathrin; Lioté, Frederic; So, Alexander; Merriman, Tony R

    2015-10-13

    The acute gout flare results from a localised self-limiting innate immune response to monosodium urate (MSU) crystals deposited in joints in hyperuricaemic individuals. Activation of the caspase recruitment domain-containing protein 8 (CARD8) NOD-like receptor pyrin-containing 3 (NLRP3) inflammasome by MSU crystals and production of mature interleukin-1β (IL-1β) is central to acute gouty arthritis. However very little is known about genetic control of the innate immune response involved in acute gouty arthritis. Therefore our aim was to test functional single nucleotide polymorphism (SNP) variants in the toll-like receptor (TLR)-inflammasome-IL-1β axis for association with gout. 1,494 gout cases of European and 863 gout cases of New Zealand (NZ) Polynesian (Māori and Pacific Island) ancestry were included. Gout was diagnosed by the 1977 ARA gout classification criteria. There were 1,030 Polynesian controls and 10,942 European controls including from the publicly-available Atherosclerosis Risk in Communities (ARIC) and Framingham Heart (FHS) studies. The ten SNPs were either genotyped by Sequenom MassArray or by Affymetrix SNP array or imputed in the ARIC and FHS datasets. Allelic association was done by logistic regression adjusting by age and sex with European and Polynesian data combined by meta-analysis. Sample sets were pooled for multiplicative interaction analysis, which was also adjusted by sample set. Eleven SNPs were tested in the TLR2, CD14, IL1B, CARD8, NLRP3, MYD88, P2RX7, DAPK1 and TNXIP genes. Nominally significant (P gout were detected at CARD8 rs2043211 (OR = 1.12, P = 0.007), IL1B rs1143623 (OR = 1.10, P = 0.020) and CD14 rs2569190 (OR = 1.08; P = 0.036). There was significant multiplicative interaction between CARD8 and IL1B (P = 0.005), with the IL1B risk genotype amplifying the risk effect of CARD8. There is evidence for association of gout with functional variants in CARD8, IL1B and CD14. The gout-associated allele of IL1B increases

  7. AgMIP Training in Multiple Crop Models and Tools

    Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

    2015-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

  8. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

    Lewei Duan

    2013-01-01

    Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

  9. ENU mutagenesis to generate genetically modified rat models.

    van Boxtel, Ruben; Gould, Michael N; Cuppen, Edwin; Smits, Bart M G

    2010-01-01

    The rat is one of the most preferred model organisms in biomedical research and has been extremely useful for linking physiology and pathology to the genome. However, approaches to genetically modify specific genes in the rat germ line remain relatively scarce. To date, the most efficient approach for generating genetically modified rats has been the target-selected N-ethyl-N-nitrosourea (ENU) mutagenesis-based technology. Here, we describe the detailed protocols for ENU mutagenesis and mutant retrieval in the rat model organism.

  10. Introduction to genetic algorithms as a modeling tool

    Wildberger, A.M.; Hickok, K.A.

    1990-01-01

    Genetic algorithms are search and classification techniques modeled on natural adaptive systems. This is an introduction to their use as a modeling tool with emphasis on prospects for their application in the power industry. It is intended to provide enough background information for its audience to begin to follow technical developments in genetic algorithms and to recognize those which might impact on electric power engineering. Beginning with a discussion of genetic algorithms and their origin as a model of biological adaptation, their advantages and disadvantages are described in comparison with other modeling tools such as simulation and neural networks in order to provide guidance in selecting appropriate applications. In particular, their use is described for improving expert systems from actual data and they are suggested as an aid in building mathematical models. Using the Thermal Performance Advisor as an example, it is suggested how genetic algorithms might be used to make a conventional expert system and mathematical model of a power plant adapt automatically to changes in the plant's characteristics

  11. Parametric modeling for damped sinusoids from multiple channels

    Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll

    2013-01-01

    frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....

  12. A Multiple Model Prediction Algorithm for CNC Machine Wear PHM

    Huimin Chen

    2011-01-01

    Full Text Available The 2010 PHM data challenge focuses on the remaining useful life (RUL estimation for cutters of a high speed CNC milling machine using measurements from dynamometer, accelerometer, and acoustic emission sensors. We present a multiple model approach for wear depth estimation of milling machine cutters using the provided data. The feature selection, initial wear estimation and multiple model fusion components of the proposed algorithm are explained in details and compared with several alternative methods using the training data. The final submission ranked #2 among professional and student participants and the method is applicable to other data driven PHM problems.

  13. Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

    Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

    2013-09-01

    Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

  14. Sleep and Development in Genetically Tractable Model Organisms.

    Kayser, Matthew S; Biron, David

    2016-05-01

    Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. Copyright © 2016 by the Genetics Society of America.

  15. The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity.

    Distel, Marijn A; Trull, Timothy J; Willemsen, Gonneke; Vink, Jacqueline M; Derom, Catherine A; Lynskey, Michael; Martin, Nicholas G; Boomsma, Dorret I

    2009-12-15

    Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, is one of the proposed models to conceptualize personality disorders as maladaptive variants of continuously distributed personality traits. The present study examined the phenotypic and genetic association between borderline personality and FFM personality traits. Data were available for 4403 monozygotic twins, 4425 dizygotic twins, and 1661 siblings from 6140 Dutch, Belgian, and Australian families. Broad-sense heritability estimates for neuroticism, agreeableness, conscientiousness, extraversion, openness to experience, and borderline personality were 43%, 36%, 43%, 47%, 54%, and 45%, respectively. Phenotypic correlations between borderline personality and the FFM personality traits ranged from .06 for openness to experience to .68 for neuroticism. Multiple regression analyses showed that a combination of high neuroticism and low agreeableness best predicted borderline personality. Multivariate genetic analyses showed the genetic factors that influence individual differences in neuroticism, agreeableness, conscientiousness, and extraversion account for all genetic liability to borderline personality. Unique environmental effects on borderline personality, however, were not completely shared with those for the FFM traits (33% is unique to borderline personality). Borderline personality shares all genetic variation with neuroticism, agreeableness, conscientiousness, and extraversion. The unique environmental influences specific to borderline personality may cause individuals with a specific pattern of personality traits to cross a threshold and develop borderline personality.

  16. Genetic and infectious profiles influence cerebrospinal fluid IgG abnormality in Japanese multiple sclerosis patients.

    Satoshi Yoshimura

    Full Text Available BACKGROUND: Abnormal intrathecal synthesis of IgG, reflected by cerebrospinal fluid (CSF oligoclonal IgG bands (OBs and increased IgG index, is much less frequently observed in Japanese multiple sclerosis (MS cohorts compared with Western cohorts. We aimed to clarify whether genetic and common infectious backgrounds influence CSF IgG abnormality in Japanese MS patients. METHODOLOGY: We analyzed HLA-DRB1 alleles, and IgG antibodies against Chlamydia pneumoniae, Helicobacter pylori, Epstein-Barr virus nuclear antigen (EBNA, and varicella zoster virus (VZV in 94 patients with MS and 367 unrelated healthy controls (HCs. We defined CSF IgG abnormality as the presence of CSF OBs and/or increased IgG index (>0.658. PRINCIPAL FINDINGS: CSF IgG abnormality was found in 59 of 94 (62.8% MS patients. CSF IgG abnormality-positive patients had a significantly higher frequency of brain MRI lesions meeting the Barkhof criteria compared with abnormality-negative patients. Compared with HCs, CSF IgG abnormality-positive MS patients showed a significantly higher frequency of DRB1 1501, whereas CSF IgG abnormality-negative patients had a significantly higher frequency of DRB1 0405. CSF IgG abnormality-positive MS patients had a significantly higher frequency of anti-C. pneumoniae IgG antibodies compared with CSF IgG abnormality-negative MS patients, although there was no difference in the frequency of anti-C. pneumoniae IgG antibodies between HCs and total MS patients. Compared with HCs, anti-H. pylori IgG antibodies were detected significantly less frequently in the total MS patients, especially in CSF IgG abnormality-negative MS patients. The frequencies of antibodies against EBNA and VZV did not differ significantly among the groups. CONCLUSIONS: CSF IgG abnormality is associated with Western MS-like brain MRI features. DRB1 1501 and C. pneumoniae infection confer CSF IgG abnormality, while DRB1 0405 and H. pylori infection are positively and negatively

  17. Genetic engineering in nonhuman primates for human disease modeling.

    Sato, Kenya; Sasaki, Erika

    2018-02-01

    Nonhuman primate (NHP) experimental models have contributed greatly to human health research by assessing the safety and efficacy of newly developed drugs, due to their physiological and anatomical similarities to humans. To generate NHP disease models, drug-inducible methods, and surgical treatment methods have been employed. Recent developments in genetic and developmental engineering in NHPs offer new options for producing genetically modified disease models. Moreover, in recent years, genome-editing technology has emerged to further promote this trend and the generation of disease model NHPs has entered a new era. In this review, we summarize the generation of conventional disease model NHPs and discuss new solutions to the problem of mosaicism in genome-editing technology.

  18. Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

    Fisz, Jacek J

    2006-12-07

    The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi

  19. Multiple regression and beyond an introduction to multiple regression and structural equation modeling

    Keith, Timothy Z

    2014-01-01

    Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

  20. A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

    Li, Guo; Lv, Fei; Guan, Xu

    2014-01-01

    This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

  1. A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

    Guo Li

    2014-01-01

    Full Text Available This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

  2. A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

    Lv, Fei; Guan, Xu

    2014-01-01

    This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

  3. An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication

    Madsen Per

    2007-07-01

    Full Text Available Abstract In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.

  4. MicroRNA expression in multiple myeloma is associated with genetic subtype, isotype and survival

    Pezzella Francesco

    2011-05-01

    Full Text Available Abstract Background MicroRNAs are small RNA species that regulate gene expression post-transcriptionally and are aberrantly expressed in many cancers including hematological malignancies. However, the role of microRNAs in the pathogenesis of multiple myeloma (MM is only poorly understood. We therefore used microarray analysis to elucidate the complete miRNome (miRBase version 13.0 of purified tumor (CD138+ cells from 33 patients with MM, 5 patients with monoclonal gammopathy of undetermined significance (MGUS and 9 controls. Results Unsupervised cluster analysis revealed that MM and MGUS samples have a distinct microRNA expression profile from control CD138+ cells. The majority of microRNAs aberrantly expressed in MM (109/129 were up-regulated. A comparison of these microRNAs with those aberrantly expressed in other B-cell and T-cell malignancies revealed a surprising degree of similarity (~40% suggesting the existence of a common lymphoma microRNA signature. We identified 39 microRNAs associated with the pre-malignant condition MGUS. Twenty-three (59% of these were also aberrantly expressed in MM suggesting common microRNA expression events in MM progression. MM is characterized by multiple chromosomal abnormalities of varying prognostic significance. We identified specific microRNA signatures associated with the most common IgH translocations (t(4;14 and t(11;14 and del(13q. Expression levels of these microRNAs were distinct between the genetic subtypes (by cluster analysis and correctly predicted these abnormalities in > 85% of cases using the support vector machine algorithm. Additionally, we identified microRNAs associated with light chain only myeloma, as well as IgG and IgA-type MM. Finally, we identified 32 microRNAs associated with event-free survival (EFS in MM, ten of which were significant by univariate (logrank survival analysis. Conclusions In summary, this work has identified aberrantly expressed microRNAs associated with the

  5. Disease modeling in genetic kidney diseases: zebrafish.

    Schenk, Heiko; Müller-Deile, Janina; Kinast, Mark; Schiffer, Mario

    2017-07-01

    Growing numbers of translational genomics studies are based on the highly efficient and versatile zebrafish (Danio rerio) vertebrate model. The increasing types of zebrafish models have improved our understanding of inherited kidney diseases, since they not only display pathophysiological changes but also give us the opportunity to develop and test novel treatment options in a high-throughput manner. New paradigms in inherited kidney diseases have been developed on the basis of the distinct genome conservation of approximately 70 % between zebrafish and humans in terms of existing gene orthologs. Several options are available to determine the functional role of a specific gene or gene sets. Permanent genome editing can be induced via complete gene knockout by using the CRISPR/Cas-system, among others, or via transient modification by using various morpholino techniques. Cross-species rescues succeeding knockdown techniques are employed to determine the functional significance of a target gene or a specific mutation. This article summarizes the current techniques and discusses their perspectives.

  6. Double-multiple streamtube model for Darrieus in turbines

    Paraschivoiu, I.

    1981-01-01

    An analytical model is proposed for calculating the rotor performance and aerodynamic blade forces for Darrieus wind turbines with curved blades. The method of analysis uses a multiple-streamtube model, divided into two parts: one modeling the upstream half-cycle of the rotor and the other, the downstream half-cycle. The upwind and downwind components of the induced velocities at each level of the rotor were obtained using the principle of two actuator disks in tandem. Variation of the induced velocities in the two parts of the rotor produces larger forces in the upstream zone and smaller forces in the downstream zone. Comparisons of the overall rotor performance with previous methods and field test data show the important improvement obtained with the present model. The calculations were made using the computer code CARDAA developed at IREQ. The double-multiple streamtube model presented has two major advantages: it requires a much shorter computer time than the three-dimensional vortex model and is more accurate than multiple-streamtube model in predicting the aerodynamic blade loads.

  7. Genetic Evaluation and Ranking of Different Animal Models Using ...

    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 ...

  8. Revised models and genetic parameter estimates for production and ...

    Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...

  9. Use of Genetic Models to Study the Urinary Concentrating Mechanism

    Olesen, Emma Tina Bisgaard; Kortenoeven, Marleen L.A.; Fenton, Robert A.

    2015-01-01

    technology is providing critical new information about urinary concentrating processes and thus mechanisms for maintaining body water homeostasis. In this chapter we provide a brief overview of genetic mouse model generation, and then summarize findings in transgenic and knockout mice pertinent to our...

  10. Genetic models of absence epilepsy: New concepts and insights

    Luijtelaar, E.L.J.M. van; Stein, J.

    2017-01-01

    The discovery, development and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures, which has gained impact within the international epilepsy community. A focal zone has been identified in the perioral region of the somatosensory cortex in

  11. ENU mutagenesis to generate genetically modified rat models

    van Boxtel, R.; Gould, M.; Cuppen, E.; Smits, B.M.

    2010-01-01

    The rat is one of the most preferred model organisms in biomedical research and has been extremely useful for linking physiology and pathology to the genome. However, approaches to genetically modify specific genes in the rat germ line remain relatively scarce. To date, the most efficient approach

  12. Genetic Process Mining: Alignment-based Process Model Mutation

    Eck, van M.L.; Buijs, J.C.A.M.; Dongen, van B.F.; Fournier, F.; Mendling, J.

    2015-01-01

    The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses

  13. Genetic insight into yield-associated traits of wheat grown in multiple rain-fed environments.

    Xianshan Wu

    Full Text Available BACKGROUND: Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14. METHODOLOGY/PRINCIPAL FINDINGS: Ten yield-associated traits, including yield per plant (YP, number of spikes per plant (NSP, number of grains per spike (NGS, one-thousand grain weight (TGW, total number of spikelets per spike (TNSS, number of sterile spikelets per spike (NSSS, proportion of fertile spikelets per spike (PFSS, spike length (SL, density of spikelets per spike (DSS and plant height (PH, were assessed across 14 (for YP to 23 (for TGW year × location × water regime environments in China. Then, the genetic effects were partitioned into additive main effects (a, epistatic main effects (aa and their environment interaction effects (ae and aae by using composite interval mapping in a mixed linear model. CONCLUSIONS/SIGNIFICANCE: Twelve (YP to 33 (PH QTLs were identified on all 21 chromosomes except 6D. QTLs were more frequently observed on chromosomes 1B, 2B, 2D, 5A and 6B, and were concentrated in a few regions on individual chromosomes, exemplified by three striking yield-related QTL clusters on chromosomes 2B, 1B and 4B that explained the correlations between YP and other traits. The additive main-effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. Consistent with agronomic analyses, a group of progeny derived by selecting TGW and NGS, with higher grain yield, had an increased frequency of QTL for high YP, NGS, TGW, TNSS, PFSS, SL, PH and fewer NSSS, when compared to low yielding progeny. This indicated that it is feasible by marker-assisted selection to facilitate wheat production.

  14. Genetic factors and multiple sclerosis in the Moroccan population: a role for HLA class II.

    Ouadghiri, S; El Alaoui Toussi, K; Brick, C; Ait Benhaddou, E H; Benseffaj, N; Benomar, A; El Yahyaoui, M; Essakalli, M

    2013-12-01

    Multiple sclerosis (MS) is an autoimmune inflammatory demyelinating disease of the central nervous system that mainly affects young adults. The association between susceptibility to MS and HLA class II genes, in particular the DRB1*15 allele, has been reported in diverse ethnic groups. The aim of our study was to investigate the distribution of HLA-DRB1* and -DQB1* alleles in Moroccan population and their implication in the susceptibility to the disease. Fifty-seven MS patients were compared to 172 healthy controls unrelated to one another and matched by age, sex and ethnic origin. HLA class II (DRB1* and DQB1*) typing was performed by PCR-SSP and/or Luminex (PCR-SSO). Allelic and haplotypic frequencies, P-values, odds ratio (OR) and 95% confidence interval (CI) were calculated using the software SPSS. A significant increase of DRB1*15 allele frequency (17.6% vs 8.4%, OR=2.67, 95% CI=1.36-5.23, P=0.004) and HLA-DRB1*15-DQB1*06 haplotype (8.8% vs 4.08%, OR=2.78, 95% CI=1.41-5.48, P=0.002) were observed in Moroccan MS patients. No association of the DR15 allele with sex or age at onset was appreciated. Concerning HLA-DQB1* alleles, no significant difference between patients and controls was found. Our results reveal a role for HLA-DRB1*15 allele molecules in the predisposition of Moroccan patients to MS. Although this study should be confirmed on a larger sample size, it analyzes for the first time the possible role of a genetic marker for susceptibility to MS in Moroccan population. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  15. Clinical and Genetic Analysis of Multiple Endocrine Neoplasia Type 1-Related Primary Hyperparathyroidism in Chinese.

    Jing Kong

    Full Text Available Multiple endocrine neoplasia type 1-related primary hyperparathyroidism (MHPT differs in many aspects from sporadic PHPT (SHPT. The aims of this study were to summarize the clinical features and genetic background of Chinese MHPT patients and compare the severity of the disease with those of SHPT.A total of 40 MHPT (27 sporadic, 7 families and 169 SHPT cases of Chinese descent were retrospectively analyzed. X-rays and ultrasound were used to assess the bone and urinary system. Dual energy x-ray absorptiometry (DXA were performed to measure bone mineral density (BMD. Besides direct sequencing of the MEN1 and CDKN1B genes, multiplex ligation-dependent probe amplification (MLPA was used to screen gross deletion for the MEN1 gene.Compared with SHPT patients, MHPT patients showed lower prevalence of typical X-ray changes related to PHPT (26.3% vs. 55.7%, P = 0.001 but higher prevalence of urolithiasis/renal calcification (40.2% vs. 60.0%, P = 0.024. MHPT patients showed higher phosphate level (0.84 vs. 0.73mmol/L, P<0.05 but lower ALP (103.0 vs. 174.0U/L, P<0.001 and PTH (4.0 vs. 9.8×upper limit, P<0.001 levels than SHPT patients. There were no significant differences in BMD Z-scores at the lumbar spine and femoral neck between the two groups. Mutations in the MEN1 gene were detected in 27 MHPT cases. Among the nine novel mutations were novel, one of them involved the deletion of exon 5 and 6.MHPT patients experienced more common kidney complications but less skeletal issues, and a milder biochemical manifestation compared with SHPT patients. MEN1 mutation detection rate was 79.4% and 9 of the identified mutations were novel.

  16. Multiple commodities in statistical microeconomics: Model and market

    Baaquie, Belal E.; Yu, Miao; Du, Xin

    2016-11-01

    A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

  17. Risk Prediction Models for Other Cancers or Multiple Sites

    Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. An extension of the multiple-trapping model

    Shkilev, V. P.

    2012-01-01

    The hopping charge transport in disordered semiconductors is considered. Using the concept of the transport energy level, macroscopic equations are derived that extend a multiple-trapping model to the case of semiconductors with both energy and spatial disorders. It is shown that, although both types of disorder can cause dispersive transport, the frequency dependence of conductivity is determined exclusively by the spatial disorder.

  19. Selecting Tools to Model Integer and Binomial Multiplication

    Pratt, Sarah Smitherman; Eddy, Colleen M.

    2017-01-01

    Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

  20. Modeling single versus multiple systems in implicit and explicit memory.

    Starns, Jeffrey J; Ratcliff, Roger; McKoon, Gail

    2012-04-01

    It is currently controversial whether priming on implicit tasks and discrimination on explicit recognition tests are supported by a single memory system or by multiple, independent systems. In a Psychological Review article, Berry and colleagues used mathematical modeling to address this question and provide compelling evidence against the independent-systems approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Genetic differentiation across multiple spatial scales of the Red Sea of the corals Stylophora pistillata and Pocillopora verrucosa

    Monroe, Alison

    2015-12-01

    Observing populations at different spatial scales gives greater insight into the specific processes driving genetic differentiation and population structure. Here we determined population connectivity across multiple spatial scales in the Red Sea to determine the population structures of two reef building corals Stylophora pistillata and Pocillopora verrucosa. The Red sea is a 2,250 km long body of water with extremely variable latitudinal environmental gradients. Mitochondrial and microsatellite markers were used to determine distinct lineages and to look for genetic differentiation among sampling sites. No distinctive population structure across the latitudinal gradient was discovered within this study suggesting a phenotypic plasticity of both these species to various environments. Stylophora pistillata displayed a heterogeneous distribution of three distinct genetic populations on both a fine and large scale. Fst, Gst, and Dest were all significant (p-value<0.05) and showed moderate genetic differentiation between all sampling sites. However this seems to be byproduct of the heterogeneous distribution, as no distinct genetic population breaks were found. Stylophora pistillata showed greater population structure on a fine scale suggesting genetic selection based on fine scale environmental variations. However, further environmental and oceanographic data is needed to make more inferences on this structure at small spatial scales. This study highlights the deficits of knowledge of both the Red Sea and coral plasticity in regards to local environmental conditions.

  2. Green communication: The enabler to multiple business models

    Lindgren, Peter; Clemmensen, Suberia; Taran, Yariv

    2010-01-01

    Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...... possibility to enable lower energy consumption. This paper shows how green communication enables innovation of green business models and multiple business models running simultaneously in different markets to different customers.......Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...

  3. Infinite Multiple Membership Relational Modeling for Complex Networks

    Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

    Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

  4. Genetic profiling of a rare condition: co-occurrence of albinism and multiple primary melanoma in a Caucasian family.

    De Summa, Simona; Guida, Michele; Tommasi, Stefania; Strippoli, Sabino; Pellegrini, Cristina; Fargnoli, Maria Concetta; Pilato, Brunella; Natalicchio, Iole; Guida, Gabriella; Pinto, Rosamaria

    2017-05-02

    Multiple primary melanoma (MPM) is a rare condition, whose genetic basis has not yet been clarified. Only 8-12% of MPM are due to germline mutations of CDKN2A. However, other genes (POT1, BRCA1/2, MC1R, MGMT) have been demonstrated to be involved in predisposition to this pathology.To our knowledge, this is the first family study based on two siblings with the rare coexistence of MPM and oculocutaneous albinism (OCA), an autosomal recessive disease characterized by the absence or decrease in pigmentation in the skin, hair, and eyes.In this study, we evaluated genes involved in melanoma predisposition (CDKN2A, CDK4, MC1R, MITF, POT1, RB1, MGMT, BRCA1, BRCA2), pathogenesis (BRAF, NRAS, PIK3CA, KIT, PTEN), skin/hair pigmentation (MC1R, MITF) and in immune pathways (CTLA4) to individuate alterations able to explain the rare onset of MPM and OCA in indexes and the transmission in their pedigree.From the analysis of the pedigree, we were able to identify a "protective" haplotype with respect to MPM, including MGMT p.I174V alteration. The second generation offspring is under strict follow up as some of them have a higher risk of developing MPM according to our model.

  5. Application of genetic algorithm in radio ecological models parameter determination

    Pantelic, G. [Institute of Occupatioanl Health and Radiological Protection ' Dr Dragomir Karajovic' , Belgrade (Serbia)

    2006-07-01

    The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 {+-} 3) days and transfer coefficient from grass to milk is (0.019 {+-} 0.005). (authors)

  6. Application of genetic algorithm in radio ecological models parameter determination

    Pantelic, G.

    2006-01-01

    The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 ± 3) days and transfer coefficient from grass to milk is (0.019 ± 0.005). (authors)

  7. A genetic algorithm for solving supply chain network design model

    Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.

    2013-09-01

    Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.

  8. Vehicle coordinated transportation dispatching model base on multiple crisis locations

    Tian, Ran; Li, Shanwei; Yang, Guoying

    2018-05-01

    Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

  9. Using Workflow Modeling to Identify Areas to Improve Genetic Test Processes in the University of Maryland Translational Pharmacogenomics Project.

    Cutting, Elizabeth M; Overby, Casey L; Banchero, Meghan; Pollin, Toni; Kelemen, Mark; Shuldiner, Alan R; Beitelshees, Amber L

    Delivering genetic test results to clinicians is a complex process. It involves many actors and multiple steps, requiring all of these to work together in order to create an optimal course of treatment for the patient. We used information gained from focus groups in order to illustrate the current process of delivering genetic test results to clinicians. We propose a business process model and notation (BPMN) representation of this process for a Translational Pharmacogenomics Project being implemented at the University of Maryland Medical Center, so that personalized medicine program implementers can identify areas to improve genetic testing processes. We found that the current process could be improved to reduce input errors, better inform and notify clinicians about the implications of certain genetic tests, and make results more easily understood. We demonstrate our use of BPMN to improve this important clinical process for CYP2C19 genetic testing in patients undergoing invasive treatment of coronary heart disease.

  10. Directional genetic selection by pulp mill effluent on multiple natural populations of three-spined stickleback (Gasterosteus aculeatus).

    Lind, Emma E; Grahn, Mats

    2011-05-01

    Contamination can cause a rapid environmental change which may require populations to respond with evolutionary changes. To evaluate the effects of pulp mill effluents on population genetics, we sampled three-spined sticklebacks (Gasterosteus aculeatus) near four pulp mills and four adjacent reference sites and analyzed Amplified Fragment Length Polymorphism (AFLP) to compare genetic variability. A fine scale genetic structure was detected and samples from polluted sites separated from reference sites in multidimensional scaling plots (Pselection. When removing 13 F(ST)-outlier loci, significant at the Pselective agent on natural populations of G. aculeatus, causing a convergence in genotype composition change at multiple sites in an open environment. © The Author(s) 2011. This article is published with open access at Springerlink.com

  11. Defining conservation units in a stocking-induced genetic melting pot: unraveling native and multiple exotic genetic imprints of recent and historical secondary contact in Adriatic grayling.

    Meraner, Andreas; Cornetti, Luca; Gandolfi, Andrea

    2014-04-01

    The definition of conservation units is crucial for the sustainable management of endangered species, though particularly challenging when recent and past anthropogenic and natural gene flow might have played a role. The conservation of the European grayling, Thymallus thymallus, is particularly complex in its southern distribution area, where the Adriatic evolutionary lineage is endangered by a long history of anthropogenic disturbance, intensive stocking and potentially widespread genetic introgression. We provide mtDNA sequence and microsatellite data of 683 grayling from 30 sites of Adriatic as well as Danubian and Atlantic origin. We apply Bayesian clustering and Approximate Bayesian Computation (ABC) to detect microgeographic population structure and to infer the demographic history of the Adriatic populations, to define appropriate conservation units. Varying frequencies of indigenous genetic signatures of the Adriatic grayling were revealed, spanning from marginal genetic introgression to the collapse of native gene pools. Genetic introgression involved multiple exotic source populations of Danubian and Atlantic origin, thus evidencing the negative impact of few decades of stocking. Within the Adige River system, a contact zone of western Adriatic and eastern Danubian populations was detected, with ABC analyses suggesting a historical anthropogenic origin of eastern Adige populations, most likely founded by medieval translocations. Substantial river-specific population substructure within the Adriatic grayling Evolutionary Significant Unit points to the definition of different conservation units. We finally propose a catalog of management measures, including the legal prohibition of stocking exotic grayling and the use of molecular markers in supportive- and captive-breeding programs.

  12. Multiple Surrogate Modeling for Wire-Wrapped Fuel Assembly Optimization

    Raza, Wasim; Kim, Kwang-Yong

    2007-01-01

    In this work, shape optimization of seven pin wire wrapped fuel assembly has been carried out in conjunction with RANS analysis in order to evaluate the performances of surrogate models. Previously, Ahmad and Kim performed the flow and heat transfer analysis based on the three-dimensional RANS analysis. But numerical optimization has not been applied to the design of wire-wrapped fuel assembly, yet. Surrogate models are being widely used in multidisciplinary optimization. Queipo et al. reviewed various surrogates based models used in aerospace applications. Goel et al. developed weighted average surrogate model based on response surface approximation (RSA), radial basis neural network (RBNN) and Krigging (KRG) models. In addition to the three basic models, RSA, RBNN and KRG, the multiple surrogate model, PBA also has been employed. Two geometric design variables and a multi-objective function with a weighting factor have been considered for this problem

  13. Genetic demixing and evolution in linear stepping stone models

    Korolev, K. S.; Avlund, Mikkel; Hallatschek, Oskar; Nelson, David R.

    2010-04-01

    Results for mutation, selection, genetic drift, and migration in a one-dimensional continuous population are reviewed and extended. The population is described by a continuous limit of the stepping stone model, which leads to the stochastic Fisher-Kolmogorov-Petrovsky-Piscounov equation with additional terms describing mutations. Although the stepping stone model was first proposed for population genetics, it is closely related to “voter models” of interest in nonequilibrium statistical mechanics. The stepping stone model can also be regarded as an approximation to the dynamics of a thin layer of actively growing pioneers at the frontier of a colony of micro-organisms undergoing a range expansion on a Petri dish. The population tends to segregate into monoallelic domains. This segregation slows down genetic drift and selection because these two evolutionary forces can only act at the boundaries between the domains; the effects of mutation, however, are not significantly affected by the segregation. Although fixation in the neutral well-mixed (or “zero-dimensional”) model occurs exponentially in time, it occurs only algebraically fast in the one-dimensional model. An unusual sublinear increase is also found in the variance of the spatially averaged allele frequency with time. If selection is weak, selective sweeps occur exponentially fast in both well-mixed and one-dimensional populations, but the time constants are different. The relatively unexplored problem of evolutionary dynamics at the edge of an expanding circular colony is studied as well. Also reviewed are how the observed patterns of genetic diversity can be used for statistical inference and the differences are highlighted between the well-mixed and one-dimensional models. Although the focus is on two alleles or variants, q -allele Potts-like models of gene segregation are considered as well. Most of the analytical results are checked with simulations and could be tested against recent spatial

  14. Central Ukraine Uranium Province: The genetic model

    Emetz, A.; Cuney, M.

    2014-01-01

    ramifications or intersections. In such places albitites are often altered by superimposed calcic and potassic metasomatism resulting in the replacement of aegirine and riebeckite by garnet, epidote, actinolite, calcite and lamellar phlogopite accompanying U-mineralization. All types of the metasomatic alterations gradually pinch out with depth. U-mineralized metasomatites are enriched in a complex of elements typically accumulated in the crust during regional metamorphism, and partial melting as indicated by pegmatite dike swarms in the Ingul Megablock. From seismic data interpretation, all U deposits in the CUUP are located over latitudinal mantle “deeps” or in the zones where the base of the lithosphere contrastingly subsides. In conclusion, Na-metasomatism is interpreted as a regional process resulting from the deep penetration of marine waters down along crustal scale shear zones during an extensional tectonic regime causing the regional collapse of the Ingul Megablock. Calcic and potassic alterations and U-mineralization are possibly connected with the crust dehydration and probable hotspot partial melting in the mantle initiated by the most unstable P-T conditions within zones of contrasting thickness of the lithosphere. The proposed models of Na-metasomatism and U-accumulation are useful for delineation of prospective territories having the potential to host U deposits associated with Na-metasomatites in Proterozoic terrains. (author)

  15. A model for diagnosing and explaining multiple disorders.

    Jamieson, P W

    1991-08-01

    The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.

  16. Genetic Risk by Experience Interaction for Childhood Internalizing Problems: Converging Evidence across Multiple Methods

    Vendlinski, Matthew K.; Lemery-Chalfant, Kathryn; Essex, Marilyn J.; Goldsmith, H. Hill

    2011-01-01

    Background: Identifying how genetic risk interacts with experience to predict psychopathology is an important step toward understanding the etiology of mental health problems. Few studies have examined genetic risk by experience interaction (GxE) in the development of childhood psychopathology. Methods: We used both co-twin and parent mental…

  17. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

    Tuta, Jure; Juric, Matjaz B

    2018-03-24

    This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  18. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

    Jure Tuta

    2018-03-01

    Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  19. Genetic enhancement of macroautophagy in vertebrate models of neurodegenerative diseases.

    Ejlerskov, Patrick; Ashkenazi, Avraham; Rubinsztein, David C

    2018-04-03

    Most of the neurodegenerative diseases that afflict humans manifest with the intraneuronal accumulation of toxic proteins that are aggregate-prone. Extensive data in cell and neuronal models support the concept that such proteins, like mutant huntingtin or alpha-synuclein, are substrates for macroautophagy (hereafter autophagy). Furthermore, autophagy-inducing compounds lower the levels of such proteins and ameliorate their toxicity in diverse animal models of neurodegenerative diseases. However, most of these compounds also have autophagy-independent effects and it is important to understand if similar benefits are seen with genetic strategies that upregulate autophagy, as this strengthens the validity of this strategy in such diseases. Here we review studies in vertebrate models using genetic manipulations of core autophagy genes and describe how these improve pathology and neurodegeneration, supporting the validity of autophagy upregulation as a target for certain neurodegenerative diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. [The emphases and basic procedures of genetic counseling in psychotherapeutic model].

    Zhang, Yuan-Zhi; Zhong, Nanbert

    2006-11-01

    The emphases and basic procedures of genetic counseling are all different with those in old models. In the psychotherapeutic model, genetic counseling will not only focus on counselees' genetic disorders and birth defects, but also their psychological problems. "Client-centered therapy" termed by Carl Rogers plays an important role in genetic counseling process. The basic procedures of psychotherapeutic model of genetic counseling include 7 steps: initial contact, introduction, agendas, inquiry of family history, presenting information, closing the session and follow-up.

  1. An animal model of differential genetic risk for methamphetamine intake

    Tamara ePhillips

    2015-09-01

    Full Text Available The question of whether genetic factors contribute to risk for methamphetamine (MA use and dependence has not been intensively investigated. Compared to human populations, genetic animal models offer the advantages of control over genetic family history and drug exposure. Using selective breeding, we created lines of mice that differ in genetic risk for voluntary MA intake and identified the chromosomal addresses of contributory genes. A quantitative trait locus was identified on chromosome 10 that accounts for more than 50% of the genetic variance in MA intake in the selected mouse lines. In addition, behavioral and physiological screening identified differences corresponding with risk for MA intake that have generated hypotheses that are testable in humans. Heightened sensitivity to aversive and certain physiological effects of MA, such as MA-induced reduction in body temperature, are hallmarks of mice bred for low MA intake. Furthermore, unlike MA-avoiding mice, MA-preferring mice are sensitive to rewarding and reinforcing MA effects, and to MA-induced increases in brain extracellular dopamine levels. Gene expression analyses implicate the importance of a network enriched in transcription factor genes, some of which regulate the mu opioid receptor gene, Oprm1, in risk for MA use. Neuroimmune factors appear to play a role in differential response to MA between the mice bred for high and low intake. In addition, chromosome 10 candidate gene studies provide strong support for a trace amine associated receptor 1 gene, Taar1, polymorphism in risk for MA intake. MA is a trace amine-associated receptor 1 (TAAR1 agonist, and a non-functional Taar1 allele segregates with high MA consumption. Thus, reduced TAAR1 function has the potential to increase risk for MA use. Overall, existing findings support the MA drinking lines as a powerful model for identifying genetic factors involved in determining risk for harmful MA use. Future directions include the

  2. A PDP model of the simultaneous perception of multiple objects

    Henderson, Cynthia M.; McClelland, James L.

    2011-06-01

    Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

  3. Supersymmetric U(1)' model with multiple dark matters

    Hur, Taeil; Lee, Hye-Sung; Nasri, Salah

    2008-01-01

    We consider a scenario where a supersymmetric model has multiple dark matter particles. Adding a U(1) ' gauge symmetry is a well-motivated extension of the minimal supersymmetric standard model (MSSM). It can cure the problems of the MSSM such as the μ problem or the proton decay problem with high-dimensional lepton number and baryon number violating operators which R parity allows. An extra parity (U parity) may arise as a residual discrete symmetry after U(1) ' gauge symmetry is spontaneously broken. The lightest U-parity particle (LUP) is stable under the new parity becoming a new dark matter candidate. Up to three massive particles can be stable in the presence of the R parity and the U parity. We numerically illustrate that multiple stable particles in our model can satisfy both constraints from the relic density and the direct detection, thus providing a specific scenario where a supersymmetric model has well-motivated multiple dark matters consistent with experimental constraints. The scenario provides new possibilities in the present and upcoming dark matter searches in the direct detection and collider experiments

  4. A Tri-Part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning about Authentic Genetics Dilemmas

    Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

    2015-01-01

    Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational…

  5. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    Sastry, Kumara Narasimha

    2007-03-01

    Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

  6. Challenges in LCA modelling of multiple loops for aluminium cans

    Niero, Monia; Olsen, Stig Irving

    considered the case of closed-loop recycling for aluminium cans, where body and lid are different alloys, and discussed the abovementioned challenge. The Life Cycle Inventory (LCI) modelling of aluminium processes is traditionally based on a pure aluminium flow, therefore neglecting the presence of alloying...... elements. We included the effect of alloying elements on the LCA modelling of aluminium can recycling. First, we performed a mass balance of the main alloying elements (Mn, Fe, Si, Cu) in aluminium can recycling at increasing levels of recycling rate. The analysis distinguished between different aluminium...... packaging scrap sources (i.e. used beverage can and mixed aluminium packaging) to understand the limiting factors for multiple loop aluminium can recycling. Secondly, we performed a comparative LCA of aluminium can production and recycling in multiple loops considering the two aluminium packaging scrap...

  7. Stable coexistence of genetically divergent Atlantic cod ecotypes at multiple spatial scales

    Knutsen, Halvor; Jorde, Per Erik; Hutchings, Jeffrey A.

    2018-01-01

    Coexistence in the same habitat of closely related yet genetically different populations is a phenomenon that challenges our understanding of local population structure and adaptation. Identifying the underlying mechanisms for such coexistence can yield new insight into adaptive evolution...

  8. lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals.

    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 .

  9. Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

    Beltz, Adriene M; Molenaar, Peter C M

    2016-01-01

    Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

  10. Genetic algorithms and experimental discrimination of SUSY models

    Allanach, B.C.; Quevedo, F.; Grellscheid, D.

    2004-01-01

    We introduce genetic algorithms as a means to estimate the accuracy required to discriminate among different models using experimental observables. We exemplify the technique in the context of the minimal supersymmetric standard model. If supersymmetric particles are discovered, models of supersymmetry breaking will be fit to the observed spectrum and it is beneficial to ask beforehand: what accuracy is required to always allow the discrimination of two particular models and which are the most important masses to observe? Each model predicts a bounded patch in the space of observables once unknown parameters are scanned over. The questions can be answered by minimising a 'distance' measure between the two hypersurfaces. We construct a distance measure that scales like a constant fraction of an observable, since that is how the experimental errors are expected to scale. Genetic algorithms, including concepts such as natural selection, fitness and mutations, provide a solution to the minimisation problem. We illustrate the efficiency of the method by comparing three different classes of string models for which the above questions could not be answered with previous techniques. The required accuracy is in the range accessible to the Large Hadron Collider (LHC) when combined with a future linear collider (LC) facility. The technique presented here can be applied to more general classes of models or observables. (author)

  11. Genetic History of Xinjiang's Uyghurs Suggests Bronze Age Multiple-Way Contacts in Eurasia.

    Feng, Qidi; Lu, Yan; Ni, Xumin; Yuan, Kai; Yang, Yajun; Yang, Xiong; Liu, Chang; Lou, Haiyi; Ning, Zhilin; Wang, Yuchen; Lu, Dongsheng; Zhang, Chao; Zhou, Ying; Shi, Meng; Tian, Lei; Wang, Xiaoji; Zhang, Xi; Li, Jing; Khan, Asifullah; Guan, Yaqun; Tang, Kun; Wang, Sijia; Xu, Shuhua

    2017-10-01

    The Uyghur people residing in Xinjiang, a territory located in the far west of China and crossed by the Silk Road, are a key ethnic group for understanding the history of human dispersion in Eurasia. Here we assessed the genetic structure and ancestry of 951 Xinjiang's Uyghurs (XJU) representing 14 geographical subpopulations. We observed a southwest and northeast differentiation within XJU, which was likely shaped jointly by the Tianshan Mountains, which traverses from east to west as a natural barrier, and gene flow from both east and west directions. In XJU, we identified four major ancestral components that were potentially derived from two earlier admixed groups: one from the West, harboring European (25-37%) and South Asian ancestries (12-20%), and the other from the East, with Siberian (15-17%) and East Asian (29-47%) ancestries. By using a newly developed method, MultiWaver, the complex admixture history of XJU was modeled as a two-wave admixture. An ancient wave was dated back to ∼3,750 years ago (ya), which is much earlier than that estimated by previous studies, but fits within the range of dating of mummies that exhibited European features that were discovered in the Tarim basin, which is situated in southern Xinjiang (4,000-2,000 ya); a more recent wave occurred around 750 ya, which is in agreement with the estimate from a recent study using other methods. We unveiled a more complex scenario of ancestral origins and admixture history in XJU than previously reported, which further suggests Bronze Age massive migrations in Eurasia and East-West contacts across the Silk Road. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Automatic Generation of 3D Building Models with Multiple Roofs

    Kenichi Sugihara; Yoshitugu Hayashi

    2008-01-01

    Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

  13. A tactical supply chain planning model with multiple flexibility options

    Esmaeilikia, Masoud; Fahimnia, Behnam; Sarkis, Joeseph

    2016-01-01

    Supply chain flexibility is widely recognized as an approach to manage uncertainty. Uncertainty in the supply chain may arise from a number of sources such as demand and supply interruptions and lead time variability. A tactical supply chain planning model with multiple flexibility options...... incorporated in sourcing, manufacturing and logistics functions can be used for the analysis of flexibility adjustment in an existing supply chain. This paper develops such a tactical supply chain planning model incorporating a realistic range of flexibility options. A novel solution method is designed...

  14. Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

    Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

    2009-01-01

    Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

  15. Dynamic modeling of genetic networks using genetic algorithm and S-system.

    Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru

    2003-03-22

    The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

  16. Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

    Lane, Peter C. R.; Gobet, Fernand

    2013-03-01

    Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

  17. Feedback structure based entropy approach for multiple-model estimation

    Shen-tu Han; Xue Anke; Guo Yunfei

    2013-01-01

    The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

  18. Dynamics of radioecological and genetic processes in populations of mammalian model species at contamination of ecosystems

    Ryabokon', N.I.; Goncharova, R.I.

    2008-01-01

    A short review of data on the time course of radiobiological and genetic processes in natural populations of mammalian model species inhabiting radiocontaminated ecosystems over many generations is presented here. The described time-courses of biological end-points in these populations do not reflect the time course of the whole-body dose rates, but do the outcome of multiple processes, including the direct response to individual irradiation, the transgeneration transmission and accumulation of induced damages and the development of adaptation. (authors)

  19. Model parameters estimation and sensitivity by genetic algorithms

    Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

    2003-01-01

    In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

  20. A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds.

    Kato, Shin; Sayama, Takashi; Fujii, Kenichiro; Yumoto, Setsuzo; Kono, Yuhi; Hwang, Tae-Young; Kikuchi, Akio; Takada, Yoshitake; Tanaka, Yu; Shiraiwa, Tatsuhiko; Ishimoto, Masao

    2014-06-01

    We detected a QTL for single seed weight in soybean that was stable across multiple environments and genetic backgrounds with the use of two recombinant inbred line populations. Single seed weight (SSW) in soybean is a key determinant of both seed yield and the quality of soy food products, and it exhibits wide variation. SSW is under genetic control, but the molecular mechanisms of such control remain unclear. We have now investigated quantitative trait loci (QTLs) for SSW in soybean and have identified such a QTL that is stable across multiple environments and genetic backgrounds. Two populations of 225 and 250 recombinant inbred lines were developed from crosses between Japanese and US cultivars of soybean that differ in SSW by a factor of ~2, and these populations were grown in at least three different environments. A whole-genome panel comprising 304 simple sequence repeat (SSR) loci was applied to mapping in each population. We identified 15 significant QTLs for SSW dispersed among 11 chromosomes in the two populations. One QTL located between Sat_284 and Sat_292 on chromosome 17 was detected (3.6 soybean.

  1. Modelling of diffuse solar fraction with multiple predictors

    Ridley, Barbara; Boland, John [Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095 (Australia); Lauret, Philippe [Laboratoire de Physique du Batiment et des Systemes, University of La Reunion, Reunion (France)

    2010-02-15

    For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia. Boland et al. developed a validated model for Australian conditions. Boland et al. detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model. (author)

  2. Genetic algorithm as a variable selection procedure for the simulation of 13C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression.

    Ghavami, Raoof; Najafi, Amir; Sajadi, Mohammad; Djannaty, Farhad

    2008-09-01

    In order to accurately simulate (13)C NMR spectra of hydroxy, polyhydroxy and methoxy substituted flavonoid a quantitative structure-property relationship (QSPR) model, relating atom-based calculated descriptors to (13)C NMR chemical shifts (ppm, TMS=0), is developed. A dataset consisting of 50 flavonoid derivatives was employed for the present analysis. A set of 417 topological, geometrical, and electronic descriptors representing various structural characteristics was calculated and separate multilinear QSPR models were developed between each carbon atom of flavonoid and the calculated descriptors. Genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models. Analysis of the results revealed a correlation coefficient and root mean square error (RMSE) of 0.994 and 2.53ppm, respectively, for the prediction set.

  3. Multiple organ histopathological changes in broiler chickens fed on genetically modified organism.

    Cîrnatu, Daniela; Jompan, A; Sin, Anca Ileana; Zugravu, Cornelia Aurelia

    2011-01-01

    Diet can influence the structural characteristics of internal organs. An experiment involving 130 meat broilers was conducted during 42 days (life term for a meat broiler) to study the effect of feed with protein from genetically modified soy. The 1-day-old birds were randomly allocated to five study groups, fed with soy, sunflower, wheat, fish flour, PC starter. In the diet of each group, an amount of protein from soy was replaced with genetically modified soy (I - 0%, II - 25%, III - 50%, IV - 75%, V - 100% protein from genetically modified soy). The level of protein in soy, either modified, or non-modified, was the same. Organs and carcass weights were measured at about 42 days of age of the birds and histopathology exams were performed during May-June 2009. No statistically significant differences were observed in mortality, growth performance variables or carcass and organ yields between broilers consuming diets produced with genetically modified soybean fractions and those consuming diets produced with near-isoline control soybean fractions. Inflammatory and degenerative liver lesions, muscle hypertrophy, hemorrhagic necrosis of bursa, kidney focal tubular necrosis, necrosis and superficial ulceration of bowel and pancreatic dystrophies were found in tissues from broilers fed on protein from genetically modified soy. Different types of lesions found in our study might be due to other causes (parasites, viral) superimposed but their presence exclusively in groups fed with modified soy raises some serious questions about the consequences of use of this type of feed.

  4. Genetic architecture of carbon isotope composition and growth in Eucalyptus across multiple environments.

    Bartholomé, Jérôme; Mabiala, André; Savelli, Bruno; Bert, Didier; Brendel, Oliver; Plomion, Christophe; Gion, Jean-Marc

    2015-06-01

    In the context of climate change, the water-use efficiency (WUE) of highly productive tree varieties, such as eucalypts, has become a major issue for breeding programmes. This study set out to dissect the genetic architecture of carbon isotope composition (δ(13) C), a proxy of WUE, across several environments. A family of Eucalyptus urophylla × E. grandis was planted in three trials and phenotyped for δ(13) C and growth traits. High-resolution genetic maps enabled us to target genomic regions underlying δ(13) C quantitative trait loci (QTLs) on the E. grandis genome. Of the 15 QTLs identified for δ(13) C, nine were stable across the environments and three displayed significant QTL-by-environment interaction, suggesting medium to high genetic determinism for this trait. Only one colocalization was found between growth and δ(13) C. Gene ontology (GO) term enrichment analysis suggested candidate genes related to foliar δ(13) C, including two involved in the regulation of stomatal movements. This study provides the first report of the genetic architecture of δ(13) C and its relation to growth in Eucalyptus. The low correlations found between the two traits at phenotypic and genetic levels suggest the possibility of improving the WUE of Eucalyptus varieties without having an impact on breeding for growth. © 2015 CIRAD. New Phytologist © 2015 New Phytologist Trust.

  5. Chemical event chain model of coupled genetic oscillators.

    Jörg, David J; Morelli, Luis G; Jülicher, Frank

    2018-03-01

    We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

  6. Chemical event chain model of coupled genetic oscillators

    Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

    2018-03-01

    We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

  7. Rapidity correlations at fixed multiplicity in cluster emission models

    Berger, M C

    1975-01-01

    Rapidity correlations in the central region among hadrons produced in proton-proton collisions of fixed final state multiplicity n at NAL and ISR energies are investigated in a two-step framework in which clusters of hadrons are emitted essentially independently, via a multiperipheral-like model, and decay isotropically. For n>or approximately=/sup 1///sub 2/(n), these semi-inclusive distributions are controlled by the reaction mechanism which dominates production in the central region. Thus, data offer cleaner insight into the properties of this mechanism than can be obtained from fully inclusive spectra. A method of experimental analysis is suggested to facilitate the extraction of new dynamical information. It is shown that the n independence of the magnitude of semi-inclusive correlation functions reflects directly the structure of the internal cluster multiplicity distribution. This conclusion is independent of certain assumptions concerning the form of the single cluster density in rapidity space. (23 r...

  8. Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure

    Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu

    2006-01-01

    Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.

  9. Natural selection affects multiple aspects of genetic variation at putatively peutral sites across the human genome

    Lohmueller, Kirk E; Albrechtsen, Anders; Li, Yingrui

    2011-01-01

    A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries...... these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination...... and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations...

  10. Genetic Aspects of Autism Spectrum Disorders: Insights from Animal Models

    Swati eBanerjee

    2014-02-01

    Full Text Available Autism spectrum disorders (ASD are a complex neurodevelopmental disorder that display a triad of core behavioral deficits including restricted interests, often accompanied by repetitive behavior, deficits in language and communication, and an inability to engage in reciprocal social interactions. ASD is among the most heritable disorders but is not a simple disorder with a singular pathology and has a rather complex etiology. It is interesting to note that perturbations in synaptic growth, development and stability underlie a variety of neuropsychiatric disorders, including ASD, schizophrenia, epilepsy and intellectual disability. Biological characterization of an increasing repertoire of synaptic mutants in various model organisms indicates synaptic dysfunction as causal in the pathophysiology of ASD. Our understanding of the genes and genetic pathways that contribute towards the formation, stabilization and maintenance of functional synapses coupled with an in-depth phenotypic analysis of the cellular and behavioral characteristics is therefore essential to unraveling the pathogenesis of these disorders. In this review, we discuss the genetic aspects of ASD emphasizing on the well conserved set of genes and genetic pathways implicated in this disorder, many of which contribute to synapse assembly and maintenance across species. We also review how fundamental research using animal models is providing key insights into the various facets of human ASD.

  11. The evolution of menstruation: A new model for genetic assimilation

    Emera, D.; Romero, R.; Wagner, G.

    2012-01-01

    Why do humans menstruate while most mammals do not? Here, we present our answer to this long-debated question, arguing that (i) menstruation occurs as a mechanistic consequence of hormone-induced differentiation of the endometrium (referred to as spontaneous decidualization, or SD); (ii) SD evolved because of maternal-fetal conflict; and (iii) SD evolved by genetic assimilation of the decidualization reaction, which is induced by the fetus in non-menstruating species. The idea that menstruation occurs as a consequence of SD has been proposed in the past, but here we present a novel hypothesis on how SD evolved. We argue that decidualization became genetically stabilized in menstruating lineages, allowing females to prepare for pregnancy without any signal from the fetus. We present three models for the evolution of SD by genetic assimilation, based on recent advances in our understanding of the mechanisms of endometrial differentiation and implantation. Testing these models will ultimately shed light on the evolutionary significance of menstruation, as well as on the etiology of human reproductive disorders like endometriosis and recurrent pregnancy loss. PMID:22057551

  12. Association of Multiple Genetic Variants with the Extension and Severity of Coronary Artery Disease

    Simone Cristina Pinto Matheus Fischer

    2018-02-01

    Full Text Available Abstract Background: Metabolic syndrome (MS is a condition that, when associated with ischemic heart disease and cardiovascular events, can be influenced by genetic variants and determine more severe coronary atherosclerosis. Objectives: To examine the contribution of genetic polymorphisms to the extension and severity of coronary disease in subjects with MS and recent acute coronary syndrome (ACS. Methods: Patients (n = 116, 68% males aged 56 (9 years, with criteria for MS, were prospectively enrolled to the study during the hospitalization period after an ACS. Clinical and laboratory parameters, high-sensitivity C-reactive protein, thiobarbituric acid reactive substances, adiponectin, endothelial function, and the Gensini score were assessed. Polymorphisms of paraoxonase-1 (PON-1, methylenotetrahydrofolate reductase (MTHFR, endothelial nitric oxide synthase (ENOS, angiotensin-converting enzyme (ACE, angiotensin II type 1 receptor (AT1R, apolipoprotein C3 (APOC3, lipoprotein lipase (LPL were analysed by polymerase chain reaction (PCR technique, followed by the identification of restriction fragment length polymorphisms (RFLP, and a genetic score was calculated. Parametric and non-parametric tests were used, as appropriate. Significance was set at p < 0.05. Results: Polymorphisms of PON-1, MTHFR and ENOS were not in the Hardy-Weinberg equilibrium. The DD genotype of LPL was associated with higher severity and greater extension of coronary lesions. Genetic score tended to be higher in patients with Gensini score < P50 (13.7 ± 1.5 vs. 13.0 ± 1.6, p = 0.066, with an inverse correlation between genetic and Gensini scores (R = -0.194, p = 0.078. Conclusions: The LPL polymorphism contributed to the severity of coronary disease in patients with MS and recent ACS. Combined polymorphisms were associated with the extension of coronary disease, and the lower the genetic score the more severe the disease.

  13. Multiplicative Attribute Graph Model of Real-World Networks

    Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

    2010-10-20

    Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

  14. Genetic modelling in schizophrenia according to HLA typing.

    Smeraldi, E; Macciardi, F; Gasperini, M; Orsini, A; Bellodi, L; Fabio, G; Morabito, A

    1986-09-01

    Studying families of schizophrenic patients, we observed that the risk of developing the overt form of the illness could be enhanced by some factors. Among these various factors we focused our attention on a biological variable, namely the presence or the absence of particular HLA antigens: partitioning our schizophrenic patients according to their HLA structure (i.e. those with HLA-A1 or CRAG-A1 antigens and those with HLA-non-CRAG-A1 antigens, respectively), revealed different illness distribution in the two groups. From a genetic point of view, this finding suggests the presence of heterogeneity in the hypothetical liability system related to schizophrenia and we evaluated the heterogeneity hypothesis by applying alternative genetic models to our data, trying to detect more biologically homogeneous subgroups of the disease.

  15. Could age modify the effect of genetic variants in IL6 and TNF-α genes in multiple myeloma?

    Martino, Alessandro; Buda, Gabriele; Maggini, Valentina; Lapi, Francesco; Lupia, Antonella; Di Bello, Domenica; Orciuolo, Enrico; Galimberti, Sara; Barale, Roberto; Petrini, Mario; Rossi, Anna Maria

    2012-05-01

    Cytokines play a central role in multiple myeloma (MM) pathogenesis thus genetic variations within cytokines coding genes could influence MM susceptibility and therapy outcome. We investigated the impact of 8 SNPs in these genes in 202 MM cases and 235 controls also evaluating their impact on therapy outcome in a subset of 91 patients. Despite the overall negative findings, we found a significant age-modified effect of IL6 and TNF-α SNPs, on MM risk and therapy outcome, respectively. Therefore, this observation suggests that genetic variation in inflammation-related genes could be an important mediator of the complex interplay between ageing and cancer. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Genetic mouse models of brain ageing and Alzheimer's disease.

    Bilkei-Gorzo, Andras

    2014-05-01

    Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. Modelling the genetic risk in age-related macular degeneration.

    Felix Grassmann

    Full Text Available Late-stage age-related macular degeneration (AMD is a common sight-threatening disease of the central retina affecting approximately 1 in 30 Caucasians. Besides age and smoking, genetic variants from several gene loci have reproducibly been associated with this condition and likely explain a large proportion of disease. Here, we developed a genetic risk score (GRS for AMD based on 13 risk variants from eight gene loci. The model exhibited good discriminative accuracy, area-under-curve (AUC of the receiver-operating characteristic of 0.820, which was confirmed in a cross-validation approach. Noteworthy, younger AMD patients aged below 75 had a significantly higher mean GRS (1.87, 95% CI: 1.69-2.05 than patients aged 75 and above (1.45, 95% CI: 1.36-1.54. Based on five equally sized GRS intervals, we present a risk classification with a relative AMD risk of 64.0 (95% CI: 14.11-1131.96 for individuals in the highest category (GRS 3.44-5.18, 0.5% of the general population compared to subjects with the most common genetic background (GRS -0.05-1.70, 40.2% of general population. The highest GRS category identifies AMD patients with a sensitivity of 7.9% and a specificity of 99.9% when compared to the four lower categories. Modeling a general population around 85 years of age, 87.4% of individuals in the highest GRS category would be expected to develop AMD by that age. In contrast, only 2.2% of individuals in the two lowest GRS categories which represent almost 50% of the general population are expected to manifest AMD. Our findings underscore the large proportion of AMD cases explained by genetics particularly for younger AMD patients. The five-category risk classification could be useful for therapeutic stratification or for diagnostic testing purposes once preventive treatment is available.

  18. Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

    Han, Lide; Yang, Jian; Zhu, Jun

    2007-06-01

    A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

  19. Dynamic coordinated control laws in multiple agent models

    Morgan, David S.; Schwartz, Ira B.

    2005-01-01

    We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in [Systems Control Lett. 52 (2004) 25], gives rise to spontaneous collective organization of agents into a unified coherent swarm, via steering controls and utilizing long-range attractive and short-range repulsive interactions. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously

  20. Laplace transform analysis of a multiplicative asset transfer model

    Sokolov, Andrey; Melatos, Andrew; Kieu, Tien

    2010-07-01

    We analyze a simple asset transfer model in which the transfer amount is a fixed fraction f of the giver’s wealth. The model is analyzed in a new way by Laplace transforming the master equation, solving it analytically and numerically for the steady-state distribution, and exploring the solutions for various values of f∈(0,1). The Laplace transform analysis is superior to agent-based simulations as it does not depend on the number of agents, enabling us to study entropy and inequality in regimes that are costly to address with simulations. We demonstrate that Boltzmann entropy is not a suitable (e.g. non-monotonic) measure of disorder in a multiplicative asset transfer system and suggest an asymmetric stochastic process that is equivalent to the asset transfer model.

  1. GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

    Wang Kai

    2011-05-01

    Full Text Available Abstract Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs have multiple cores, whereas Graphics Processing Units (GPUs also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1 the interaction of SNPs within it in parallel, and 2 the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. Conclusions GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/.

  2. Genetic patterns across multiple introductions of the globally invasive crab genus Carcinus

    The European green crab Carcinus maenas is one of the world's most successful aquatic invaders, having established populations on every continent with temperate shores. Here we describe patterns of genetic diversity across both the native and introduced ranges of C. maenas and it...

  3. Study on validation method for femur finite element model under multiple loading conditions

    Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu

    2018-03-01

    Acquisition of accurate and reliable constitutive parameters related to bio-tissue materials was beneficial to improve biological fidelity of a Finite Element (FE) model and predict impact damages more effectively. In this paper, a femur FE model was established under multiple loading conditions with diverse impact positions. Then, based on sequential response surface method and genetic algorithms, the material parameters identification was transformed to a multi-response optimization problem. Finally, the simulation results successfully coincided with force-displacement curves obtained by numerous experiments. Thus, computational accuracy and efficiency of the entire inverse calculation process were enhanced. This method was able to effectively reduce the computation time in the inverse process of material parameters. Meanwhile, the material parameters obtained by the proposed method achieved higher accuracy.

  4. Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2018-03-01

    Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

  5. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    Najibi, Seyed Morteza

    2017-02-08

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  6. A multiple relevance feedback strategy with positive and negative models.

    Yunlong Ma

    Full Text Available A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are very poor, it is impossible to extract enough useful terms from a few positive documents. Therefore, the positive feedback strategy is incapable to improve retrieval in this situation. Contrarily, there is a relatively large number of negative documents in the top of the result list, and it has been confirmed that negative feedback strategy is an important and useful way for adapting this scenario by several recent studies. In this paper, we consider a scenario when the search results are so poor that there are at most three relevant documents in the top twenty documents. Then, we conduct a novel study of multiple strategies for relevance feedback using both positive and negative examples from the first-pass retrieval to improve retrieval accuracy for such difficult queries. Experimental results on these TREC collections show that the proposed language model based multiple model feedback method which is generally more effective than both the baseline method and the methods using only positive or negative model.

  7. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

    2017-01-01

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  8. Behavioral phenotypes of genetic mouse models of autism.

    Kazdoba, T M; Leach, P T; Crawley, J N

    2016-01-01

    More than a hundred de novo single gene mutations and copy-number variants have been implicated in autism, each occurring in a small subset of cases. Mutant mouse models with syntenic mutations offer research tools to gain an understanding of the role of each gene in modulating biological and behavioral phenotypes relevant to autism. Knockout, knockin and transgenic mice incorporating risk gene mutations detected in autism spectrum disorder and comorbid neurodevelopmental disorders are now widely available. At present, autism spectrum disorder is diagnosed solely by behavioral criteria. We developed a constellation of mouse behavioral assays designed to maximize face validity to the types of social deficits and repetitive behaviors that are central to an autism diagnosis. Mouse behavioral assays for associated symptoms of autism, which include cognitive inflexibility, anxiety, hyperactivity, and unusual reactivity to sensory stimuli, are frequently included in the phenotypic analyses. Over the past 10 years, we and many other laboratories around the world have employed these and additional behavioral tests to phenotype a large number of mutant mouse models of autism. In this review, we highlight mouse models with mutations in genes that have been identified as risk genes for autism, which work through synaptic mechanisms and through the mTOR signaling pathway. Robust, replicated autism-relevant behavioral outcomes in a genetic mouse model lend credence to a causal role for specific gene contributions and downstream biological mechanisms in the etiology of autism. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  9. Genetic evaluation of European quails by random regression models

    Flaviana Miranda Gonçalves

    2012-09-01

    Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.

  10. Research on Innovating, Applying Multiple Paths Routing Technique Based on Fuzzy Logic and Genetic Algorithm for Routing Messages in Service - Oriented Routing

    Nguyen Thanh Long

    2015-02-01

    Full Text Available MANET (short for Mobile Ad-Hoc Network consists of a set of mobile network nodes, network configuration changes very fast. In content based routing, data is transferred from source node to request nodes is not based on destination addresses. Therefore, it is very flexible and reliable, because source node does not need to know destination nodes. If We can find multiple paths that satisfies bandwidth requirement, split the original message into multiple smaller messages to transmit concurrently on these paths. On destination nodes, combine separated messages into the original message. Hence it can utilize better network resources, causes data transfer rate to be higher, load balancing, failover. Service Oriented Routing is inherited from the model of content based routing (CBR, combined with several advanced techniques such as Multicast, multiple path routing, Genetic algorithm to increase the data rate, and data encryption to ensure information security. Fuzzy logic is a logical field study evaluating the accuracy of the results based on the approximation of the components involved, make decisions based on many factors relative accuracy based on experimental or mathematical proof. This article presents some techniques to support multiple path routing from one network node to a set of nodes with guaranteed quality of service. By using these techniques can decrease the network load, congestion, use network resources efficiently.

  11. Risk factors for colorectal cancer in patients with multiple serrated polyps: a cross-sectional case series from genetics clinics.

    Daniel D Buchanan

    2010-07-01

    Full Text Available Patients with multiple serrated polyps are at an increased risk for developing colorectal cancer (CRC. Recent reports have linked cigarette smoking with the subset of CRC that develops from serrated polyps. The aim of this work therefore was to investigate the association between smoking and the risk of CRC in high-risk genetics clinic patients presenting with multiple serrated polyps.We identified 151 Caucasian individuals with multiple serrated polyps including at least 5 outside the rectum, and classified patients into non-smokers, current or former smokers at the time of initial diagnosis of polyposis. Cases were individuals with multiple serrated polyps who presented with CRC. Controls were individuals with multiple serrated polyps and no CRC. Multivariate logistic regression was performed to estimate associations between smoking and CRC with adjustment for age at first presentation, sex and co-existing traditional adenomas, a feature that has been consistently linked with CRC risk in patients with multiple serrated polyps. CRC was present in 56 (37% individuals at presentation. Patients with at least one adenoma were 4 times more likely to present with CRC compared with patients without adenomas (OR = 4.09; 95%CI 1.27 to 13.14; P = 0.02. For females, the odds of CRC decreased by 90% in current smokers as compared to never smokers (OR = 0.10; 95%CI 0.02 to 0.47; P = 0.004 after adjusting for age and adenomas. For males, there was no relationship between current smoking and CRC. There was no statistical evidence of an association between former smoking and CRC for both sexes.A decreased odds for CRC was identified in females with multiple serrated polyps who currently smoke, independent of age and the presence of a traditional adenoma. Investigations into the biological basis for these observations could lead to non-smoking-related therapies being developed to decrease the risk of CRC and colectomy in these patients.

  12. Many-electron model for multiple ionization in atomic collisions

    Archubi, C D; Montanari, C C; Miraglia, J E

    2007-01-01

    We have developed a many-electron model for multiple ionization of heavy atoms bombarded by bare ions. It is based on the transport equation for an ion in an inhomogeneous electronic density. Ionization probabilities are obtained by employing the shell-to-shell local plasma approximation with the Levine and Louie dielectric function to take into account the binding energy of each shell. Post-collisional contributions due to Auger-like processes are taken into account by employing recent photoemission data. Results for single-to-quadruple ionization of Ne, Ar, Kr and Xe by protons are presented showing a very good agreement with experimental data

  13. Many-electron model for multiple ionization in atomic collisions

    Archubi, C D [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina); Montanari, C C [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina); Miraglia, J E [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina)

    2007-03-14

    We have developed a many-electron model for multiple ionization of heavy atoms bombarded by bare ions. It is based on the transport equation for an ion in an inhomogeneous electronic density. Ionization probabilities are obtained by employing the shell-to-shell local plasma approximation with the Levine and Louie dielectric function to take into account the binding energy of each shell. Post-collisional contributions due to Auger-like processes are taken into account by employing recent photoemission data. Results for single-to-quadruple ionization of Ne, Ar, Kr and Xe by protons are presented showing a very good agreement with experimental data.

  14. A genetic algorithm for multiple relay selection in two-way relaying cognitive radio networks

    Alsharoa, Ahmad M.; Ghazzai, Hakim; Alouini, Mohamed-Slim

    2013-01-01

    In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplifyand- Forward

  15. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

    Sawcer, Stephen; Hellenthal, Garrett; Pirinen, Matti

    2011-01-01

    Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that g...

  16. Model selection in Bayesian segmentation of multiple DNA alignments.

    Oldmeadow, Christopher; Keith, Jonathan M

    2011-03-01

    The analysis of multiple sequence alignments is allowing researchers to glean valuable insights into evolution, as well as identify genomic regions that may be functional, or discover novel classes of functional elements. Understanding the distribution of conservation levels that constitutes the evolutionary landscape is crucial to distinguishing functional regions from non-functional. Recent evidence suggests that a binary classification of evolutionary rates is inappropriate for this purpose and finds only highly conserved functional elements. Given that the distribution of evolutionary rates is multi-modal, determining the number of modes is of paramount concern. Through simulation, we evaluate the performance of a number of information criterion approaches derived from MCMC simulations in determining the dimension of a model. We utilize a deviance information criterion (DIC) approximation that is more robust than the approximations from other information criteria, and show our information criteria approximations do not produce superfluous modes when estimating conservation distributions under a variety of circumstances. We analyse the distribution of conservation for a multiple alignment comprising four primate species and mouse, and repeat this on two additional multiple alignments of similar species. We find evidence of six distinct classes of evolutionary rates that appear to be robust to the species used. Source code and data are available at http://dl.dropbox.com/u/477240/changept.zip.

  17. A multiple-location model for natural gas forward curves

    Buffington, J.C.

    1999-06-01

    This thesis presents an approach for financial modelling of natural gas in which connections between locations are incorporated and the complexities of forward curves in natural gas are considered. Apart from electricity, natural gas is the most volatile commodity traded. Its price is often dependent on the weather and price shocks can be felt across several geographic locations. This modelling approach incorporates multiple risk factors that correspond to various locations. One of the objectives was to determine if the model could be used for closed-form option prices. It was suggested that an adequate model for natural gas must consider 3 statistical properties: volatility term structure, backwardation and contango, and stochastic basis. Data from gas forward prices at Chicago, NYMEX and AECO were empirically tested to better understand these 3 statistical properties at each location and to verify if the proposed model truly incorporates these properties. In addition, this study examined the time series property of the difference of two locations (the basis) and determines that these empirical properties are consistent with the model properties. Closed-form option solutions were also developed for call options of forward contracts and call options on forward basis. The options were calibrated and compared to other models. The proposed model is capable of pricing options, but the prices derived did not pass the test of economic reasonableness. However, the model was able to capture the effect of transportation as well as aspects of seasonality which is a benefit over other existing models. It was determined that modifications will be needed regarding the estimation of the convenience yields. 57 refs., 2 tabs., 7 figs., 1 append

  18. Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages.

    Peterman, William; Brocato, Emily R; Semlitsch, Raymond D; Eggert, Lori S

    2016-01-01

    In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (F ST and D C ) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using D C , the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis.

  19. Whole-genome sequencing of monozygotic twins discordant for schizophrenia indicates multiple genetic risk factors for schizophrenia.

    Tang, Jinsong; Fan, Yu; Li, Hong; Xiang, Qun; Zhang, Deng-Feng; Li, Zongchang; He, Ying; Liao, Yanhui; Wang, Ya; He, Fan; Zhang, Fengyu; Shugart, Yin Yao; Liu, Chunyu; Tang, Yanqing; Chan, Raymond C K; Wang, Chuan-Yue; Yao, Yong-Gang; Chen, Xiaogang

    2017-06-20

    Schizophrenia is a common disorder with a high heritability, but its genetic architecture is still elusive. We implemented whole-genome sequencing (WGS) analysis of 8 families with monozygotic (MZ) twin pairs discordant for schizophrenia to assess potential association of de novo mutations (DNMs) or inherited variants with susceptibility to schizophrenia. Eight non-synonymous DNMs (including one splicing site) were identified and shared by twins, which were either located in previously reported schizophrenia risk genes (p.V24689I mutation in TTN, p.S2506T mutation in GCN1L1, IVS3+1G > T in DOCK1) or had a benign to damaging effect according to in silico prediction analysis. By searching the inherited rare damaging or loss-of-function (LOF) variants and common susceptible alleles from three classes of schizophrenia candidate genes, we were able to distill genetic alterations in several schizophrenia risk genes, including GAD1, PLXNA2, RELN and FEZ1. Four inherited copy number variations (CNVs; including a large deletion at 16p13.11) implicated for schizophrenia were identified in four families, respectively. Most of families carried both missense DNMs and inherited risk variants, which might suggest that DNMs, inherited rare damaging variants and common risk alleles together conferred to schizophrenia susceptibility. Our results support that schizophrenia is caused by a combination of multiple genetic factors, with each DNM/variant showing a relatively small effect size. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. All rights reserved.

  20. Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages

    William Peterman

    2016-03-01

    Full Text Available In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (FST and DC and isolation-by-distance (IBD among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using DC, the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis.

  1. Nonlinear Modeling and Identification of an Aluminum Honeycomb Panel with Multiple Bolts

    Yongpeng Chu

    2016-01-01

    Full Text Available This paper focuses on the nonlinear dynamics modeling and parameter identification of an Aluminum Honeycomb Panel (AHP with multiple bolted joints. Finite element method using eight-node solid elements is exploited to model the panel and the bolted connection interface as a homogeneous, isotropic plate and as a thin layer of nonlinear elastic-plastic material, respectively. The material properties of a thin layer are defined by a bilinear elastic plastic model, which can describe the energy dissipation and softening phenomena in the bolted joints under nonlinear states. Experimental tests at low and high excitation levels are performed to reveal the dynamic characteristics of the bolted structure. In particular, the linear material parameters of the panel are identified via experimental tests at low excitation levels, whereas the nonlinear material parameters of the thin layer are updated by using the genetic algorithm to minimize the residual error between the measured and the simulation data at a high excitation level. It is demonstrated by comparing the frequency responses of the updated FEM and the experimental system that the thin layer of bilinear elastic-plastic material is very effective for modeling the nonlinear joint interface of the assembled structure with multiple bolts.

  2. Multiplicative point process as a model of trading activity

    Gontis, V.; Kaulakys, B.

    2004-11-01

    Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

  3. Guideline validation in multiple trauma care through business process modeling.

    Stausberg, Jürgen; Bilir, Hüseyin; Waydhas, Christian; Ruchholtz, Steffen

    2003-07-01

    Clinical guidelines can improve the quality of care in multiple trauma. In our Department of Trauma Surgery a specific guideline is available paper-based as a set of flowcharts. This format is appropriate for the use by experienced physicians but insufficient for electronic support of learning, workflow and process optimization. A formal and logically consistent version represented with a standardized meta-model is necessary for automatic processing. In our project we transferred the paper-based into an electronic format and analyzed the structure with respect to formal errors. Several errors were detected in seven error categories. The errors were corrected to reach a formally and logically consistent process model. In a second step the clinical content of the guideline was revised interactively using a process-modeling tool. Our study reveals that guideline development should be assisted by process modeling tools, which check the content in comparison to a meta-model. The meta-model itself could support the domain experts in formulating their knowledge systematically. To assure sustainability of guideline development a representation independent of specific applications or specific provider is necessary. Then, clinical guidelines could be used for eLearning, process optimization and workflow management additionally.

  4. Rank-based model selection for multiple ions quantum tomography

    Guţă, Mădălin; Kypraios, Theodore; Dryden, Ian

    2012-01-01

    The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the ‘sparsity’ properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods—the Akaike information criterion (AIC) and the Bayesian information criterion (BIC)—two models consisting of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of four ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a four ions experiment aimed at creating a Smolin state of rank 4. By applying the two methods together with the Pearson χ 2 test we conclude that the data can be suitably described with a model whose rank is between 7 and 9. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements. (paper)

  5. Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

    Yoshizaki, J.; Brownie, C.; Pollock, K.H.; Link, W.A.

    2011-01-01

    Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture-recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored. ?? 2009 Springer Science+Business Media, LLC.

  6. Modeling AEC—New Approaches to Study Rare Genetic Disorders

    Koch, Peter J.; Dinella, Jason; Fete, Mary; Siegfried, Elaine C.; Koster, Maranke I.

    2015-01-01

    Ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome is a rare monogenetic disorder that is characterized by severe abnormalities in ectoderm-derived tissues, such as skin and its appendages. A major cause of morbidity among affected infants is severe and chronic skin erosions. Currently, supportive care is the only available treatment option for AEC patients. Mutations in TP63, a gene that encodes key regulators of epidermal development, are the genetic cause of AEC. However, it is currently not clear how mutations in TP63 lead to the various defects seen in the patients’ skin. In this review, we will discuss current knowledge of the AEC disease mechanism obtained by studying patient tissue and genetically engineered mouse models designed to mimic aspects of the disorder. We will then focus on new approaches to model AEC, including the use of patient cells and stem cell technology to replicate the disease in a human tissue culture model. The latter approach will advance our understanding of the disease and will allow for the development of new in vitro systems to identify drugs for the treatment of skin erosions in AEC patients. Further, the use of stem cell technology, in particular induced pluripotent stem cells (iPSC), will enable researchers to develop new therapeutic approaches to treat the disease using the patient’s own cells (autologous keratinocyte transplantation) after correction of the disease-causing mutations. PMID:24665072

  7. Genetic fuzzy system modeling and simulation of vascular behaviour

    Tang, Jiaowei; Boonen, Harrie C.M.

    Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes in c...... the pressure change of different blood vessels. Conclusion: Genetic fuzzy system is one of potential modeling methods in modeling and simulation of vascular behavior.......Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes...... in cardiovascular disease and ultimately improve pharmacotherapy. For this purpose, novel computational approaches incorporating adaptive properties, auto-regulatory control and rule sets will be assessed, properties that are commonly lacking in deterministic models based on differential equations. We hypothesize...

  8. Genetic Programming and Standardization in Water Temperature Modelling

    Maritza Arganis

    2009-01-01

    Full Text Available An application of Genetic Programming (an evolutionary computational tool without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

  9. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Chung-Min Wu

    2013-01-01

    Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

  10. Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

    Li, Muxingzi

    2017-04-24

    Optical Coherence Tomography (OCT) is a coherence-gated, micrometer-resolution imaging technique that focuses a broadband near-infrared laser beam to penetrate into optical scattering media, e.g. biological tissues. The OCT resolution is split into two parts, with the axial resolution defined by half the coherence length, and the depth-dependent lateral resolution determined by the beam geometry, which is well described by a Gaussian beam model. The depth dependence of lateral resolution directly results in the defocusing effect outside the confocal region and restricts current OCT probes to small numerical aperture (NA) at the expense of lateral resolution near the focus. Another limitation on OCT development is the presence of a mixture of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous papers have adopted the first Born approximation with the assumption of small perturbation of the incident field in inhomogeneous media. The Rytov method of the same order with smooth phase perturbation assumption benefits from a wider spatial range of validity. A deconvolution method for solving the inverse problem associated with the first Rytov approximation is developed, significantly reducing the defocusing effect through depth and therefore extending the feasible range of NA.

  11. Resveratrol Neuroprotection in a Chronic Mouse Model of Multiple Sclerosis

    Zoe eFonseca-Kelly

    2012-05-01

    Full Text Available Resveratrol is a naturally-occurring polyphenol that activates SIRT1, an NAD-dependent deacetylase. SRT501, a pharmaceutical formulation of resveratrol with enhanced systemic absorption, prevents neuronal loss without suppressing inflammation in mice with relapsing experimental autoimmune encephalomyelitis (EAE, a model of multiple sclerosis. In contrast, resveratrol has been reported to suppress inflammation in chronic EAE, although neuroprotective effects were not evaluated. The current studies examine potential neuroprotective and immunomodulatory effects of resveratrol in chronic EAE induced by immunization with myelin oligodendroglial glycoprotein peptide in C57/Bl6 mice. Effects of two distinct formulations of resveratrol administered daily orally were compared. Resveratrol delayed the onset of EAE compared to vehicle-treated EAE mice, but did not prevent or alter the phenotype of inflammation in spinal cords or optic nerves. Significant neuroprotective effects were observed, with higher numbers of retinal ganglion cells found in eyes of resveratrol-treated EAE mice with optic nerve inflammation. Results demonstrate that resveratrol prevents neuronal loss in this chronic demyelinating disease model, similar to its effects in relapsing EAE. Differences in immunosuppression compared with prior studies suggest that immunomodulatory effects may be limited and may depend on specific immunization parameters or timing of treatment. Importantly, neuroprotective effects can occur without immunosuppression, suggesting a potential additive benefit of resveratrol in combination with anti-inflammatory therapies for multiple sclerosis.

  12. Clustering and Genetic Algorithm Based Hybrid Flowshop Scheduling with Multiple Operations

    Yingfeng Zhang

    2014-01-01

    Full Text Available This research is motivated by a flowshop scheduling problem of our collaborative manufacturing company for aeronautic products. The heat-treatment stage (HTS and precision forging stage (PFS of the case are selected as a two-stage hybrid flowshop system. In HTS, there are four parallel machines and each machine can process a batch of jobs simultaneously. In PFS, there are two machines. Each machine can install any module of the four modules for processing the workpeices with different sizes. The problem is characterized by many constraints, such as batching operation, blocking environment, and setup time and working time limitations of modules, and so forth. In order to deal with the above special characteristics, the clustering and genetic algorithm is used to calculate the good solution for the two-stage hybrid flowshop problem. The clustering is used to group the jobs according to the processing ranges of the different modules of PFS. The genetic algorithm is used to schedule the optimal sequence of the grouped jobs for the HTS and PFS. Finally, a case study is used to demonstrate the efficiency and effectiveness of the designed genetic algorithm.

  13. Using genetic algorithms to calibrate a water quality model.

    Liu, Shuming; Butler, David; Brazier, Richard; Heathwaite, Louise; Khu, Soon-Thiam

    2007-03-15

    With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.

  14. Model for CO2 leakage including multiple geological layers and multiple leaky wells.

    Nordbotten, Jan M; Kavetski, Dmitri; Celia, Michael A; Bachu, Stefan

    2009-02-01

    Geological storage of carbon dioxide (CO2) is likely to be an integral component of any realistic plan to reduce anthropogenic greenhouse gas emissions. In conjunction with large-scale deployment of carbon storage as a technology, there is an urgent need for tools which provide reliable and quick assessments of aquifer storage performance. Previously, abandoned wells from over a century of oil and gas exploration and production have been identified as critical potential leakage paths. The practical importance of abandoned wells is emphasized by the correlation of heavy CO2 emitters (typically associated with industrialized areas) to oil and gas producing regions in North America. Herein, we describe a novel framework for predicting the leakage from large numbers of abandoned wells, forming leakage paths connecting multiple subsurface permeable formations. The framework is designed to exploit analytical solutions to various components of the problem and, ultimately, leads to a grid-free approximation to CO2 and brine leakage rates, as well as fluid distributions. We apply our model in a comparison to an established numerical solverforthe underlying governing equations. Thereafter, we demonstrate the capabilities of the model on typical field data taken from the vicinity of Edmonton, Alberta. This data set consists of over 500 wells and 7 permeable formations. Results show the flexibility and utility of the solution methods, and highlight the role that analytical and semianalytical solutions can play in this important problem.

  15. A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China.

    Qi, Chang; Kelly, Brian C; Liao, Yanhui; He, Haoyu; Luo, Tao; Deng, Huiqiong; Liu, Tieqiao; Hao, Wei; Wang, Jichuan

    2015-03-01

    Although evidence exists for distinct barriers to drug abuse treatment (BDATs), investigations of their inter-relationships and the effect of individual characteristics on the barrier factors have been sparse, especially in China. A Multiple Indicators Multiple Causes (MIMIC) model is applied for this target. A sample of 262 drug users were recruited from three drug rehabilitation centers in Hunan Province, China. We applied a MIMIC approach to investigate the effect of gender, age, marital status, education, primary substance use, duration of primary drug use, and drug treatment experience on the internal barrier factors: absence of problem (AP), negative social support (NSS), fear of treatment (FT), and privacy concerns (PC). Drug users of various characteristics were found to report different internal barrier factors. Younger participants were more likely to report NSS (-0.19, p=0.038) and PC (-0.31, p<0.001). Compared to other drug users, ice users were more likely to report AP (0.44, p<0.001) and NSS (0.25, p=0.010). Drug treatment experiences related to AP (0.20, p=0.012). In addition, differential item functioning (DIF) occurred in three items when participant from groups with different duration of drug use, ice use, or marital status. Individual characteristics had significant effects on internal barriers to drug treatment. On this basis, BDAT perceived by different individuals could be assessed before tactics were utilized to successfully remove perceived barriers to drug treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  16. Multiple-relaxation-time lattice Boltzmann model for compressible fluids

    Chen Feng; Xu Aiguo; Zhang Guangcai; Li Yingjun

    2011-01-01

    We present an energy-conserving multiple-relaxation-time finite difference lattice Boltzmann model for compressible flows. The collision step is first calculated in the moment space and then mapped back to the velocity space. The moment space and corresponding transformation matrix are constructed according to the group representation theory. Equilibria of the nonconserved moments are chosen according to the need of recovering compressible Navier-Stokes equations through the Chapman-Enskog expansion. Numerical experiments showed that compressible flows with strong shocks can be well simulated by the present model. The new model works for both low and high speeds compressible flows. It contains more physical information and has better numerical stability and accuracy than its single-relaxation-time version. - Highlights: → We present an energy-conserving MRT finite-difference LB model. → The moment space is constructed according to the group representation theory. → The new model works for both low and high speeds compressible flows. → It has better numerical stability and wider applicable range than its SRT version.

  17. Optimal Retail Price Model for Partial Consignment to Multiple Retailers

    Po-Yu Chen

    2017-01-01

    Full Text Available This paper investigates the product pricing decision-making problem under a consignment stock policy in a two-level supply chain composed of one supplier and multiple retailers. The effects of the supplier’s wholesale prices and its partial inventory cost absorption of the retail prices of retailers with different market shares are investigated. In the partial product consignment model this paper proposes, the seller and the retailers each absorb part of the inventory costs. This model also provides general solutions for the complete product consignment and the traditional policy that adopts no product consignment. In other words, both the complete consignment and nonconsignment models are extensions of the proposed model (i.e., special cases. Research results indicated that the optimal retail price must be between 1/2 (50% and 2/3 (66.67% times the upper limit of the gross profit. This study also explored the results and influence of parameter variations on optimal retail price in the model.

  18. Strong population genetic structuring in an annual fish, Nothobranchius furzeri, suggests multiple savannah refugia in southern Mozambique.

    Bartáková, Veronika; Reichard, Martin; Janko, Karel; Polačik, Matej; Blažek, Radim; Reichwald, Kathrin; Cellerino, Alessandro; Bryja, Josef

    2013-09-12

    Intraspecific genetic variation of African fauna has been significantly affected by pronounced climatic fluctuations in Plio-Pleistocene, but, with the exception of large mammals, very limited empirical data on diversity of natural populations are available for savanna-dwelling animals. Nothobranchius furzeri is an annual fish from south-eastern Africa, inhabiting discrete temporary savannah pools outside main river alluvia. Their dispersal is limited and population processes affecting its genetic structure are likely a combination of those affecting terrestrial and aquatic taxa. N. furzeri is a model taxon in ageing research and several populations of known geographical origin are used in laboratory studies. Here, we analysed the genetic structure, diversity, historical demography and temporal patterns of divergence in natural populations of N. furzeri across its entire distribution range. Genetic structure and historical demography of N. furzeri were analysed using a combination of mitochondrial (partial cytochrome b sequences, 687 bp) and nuclear (13 microsatellites) markers in 693 fish from 36 populations. Genetic markers consistently demonstrated strong population structuring and suggested two main genetic groups associated with river basins. The split was dated to the Pliocene (>2 Mya). The northern group inhabits savannah pools across the basin of the intermittent river Chefu in south-western Mozambique and eastern Zimbabwe. The southern group (from southernmost Mozambique) is subdivided, with the River Limpopo forming a barrier (maximum divergence time 1 Mya). A strong habitat fragmentation (isolated temporary pools) is reflected in significant genetic structuring even between adjacent pools, with a major influence of genetic drift and significant isolation-by-distance. Analysis of historical demography revealed that the expansion of both groups is ongoing, supported by frequent founder effects in marginal parts of the range and evidence of secondary

  19. Genetic Diseases and Genetic Determinism Models in French Secondary School Biology Textbooks

    Castera, Jeremy; Bruguiere, Catherine; Clement, Pierre

    2008-01-01

    The presentation of genetic diseases in French secondary school biology textbooks is analysed to determine the major conceptions taught in the field of human genetics. References to genetic diseases, and the processes by which they are explained (monogeny, polygeny, chromosomal anomaly and environmental influence) are studied in recent French…

  20. Poisson versus threshold models for genetic analysis of clinical mastitis in US Holsteins.

    Vazquez, A I; Weigel, K A; Gianola, D; Bates, D M; Perez-Cabal, M A; Rosa, G J M; Chang, Y M

    2009-10-01

    Typically, clinical mastitis is coded as the presence or absence of disease in a given lactation, and records are analyzed with either linear models or binary threshold models. Because the presence of mastitis may include cows with multiple episodes, there is a loss of information when counts are treated as binary responses. Poisson models are appropriated for random variables measured as the number of events, and although these models are used extensively in studying the epidemiology of mastitis, they have rarely been used for studying the genetic aspects of mastitis. Ordinal threshold models are pertinent for ordered categorical responses; although one can hypothesize that the number of clinical mastitis episodes per animal reflects a continuous underlying increase in mastitis susceptibility, these models have rarely been used in genetic analysis of mastitis. The objective of this study was to compare probit, Poisson, and ordinal threshold models for the genetic evaluation of US Holstein sires for clinical mastitis. Mastitis was measured as a binary trait or as the number of mastitis cases. Data from 44,908 first-parity cows recorded in on-farm herd management software were gathered, edited, and processed for the present study. The cows were daughters of 1,861 sires, distributed over 94 herds. Predictive ability was assessed via a 5-fold cross-validation using 2 loss functions: mean squared error of prediction (MSEP) as the end point and a cost difference function. The heritability estimates were 0.061 for mastitis measured as a binary trait in the probit model and 0.085 and 0.132 for the number of mastitis cases in the ordinal threshold and Poisson models, respectively; because of scale differences, only the probit and ordinal threshold models are directly comparable. Among healthy animals, MSEP was smallest for the probit model, and the cost function was smallest for the ordinal threshold model. Among diseased animals, MSEP and the cost function were smallest

  1. Invasion genetics of a freshwater mussel (Dreissena rostriformis bugensis) in eastern Europe: high gene flow and multiple introductions.

    Therriault, T W; Orlova, M I; Docker, M F; Macisaac, H J; Heath, D D

    2005-07-01

    In recent years, the quagga mussel, Dreissena rostriformis bugensis, native to the Dnieper and Bug Limans of the northern Black Sea, has been dispersed by human activities across the basin, throughout much of the Volga River system, and to the Laurentian Great Lakes. We used six published microsatellite markers to survey populations throughout its native and introduced range to identify relationships among potential source populations and introduced ones. Mussels from 12 sites in Eurasia, including the central Caspian Sea and one in North America (Lake Erie), were sampled. Field surveys in the Volga River basin suggested that the species first colonized the middle reach of the river near Kubyshev Reservoir, and thereafter spread both upstream and downstream. Evidence of considerable gene flow among populations was observed and genetic diversity was consistent with a larger, metapopulation that has not experienced bottlenecks or founder effects. We propose that high gene flow, possibly due to multiple invasions, has facilitated establishment of quagga mussel populations in the Volga River system. The Caspian Sea population (D. rostriformis rostriformis (=distincta)) was genetically more distinct than other populations, a finding that may be related to habitat differences. The geographical pattern of genetic divergence is not characteristic of isolation-by-distance but, rather, of long-distance dispersal, most likely mediated by commercial ships' ballast water transfer.

  2. Patterns of genetic diversity of the cryptogenic red alga Polysiphonia morrowii (Ceramiales, Rhodophyta) suggest multiple origins of the Atlantic populations.

    Geoffroy, Alexandre; Destombe, Christophe; Kim, Byeongseok; Mauger, Stéphane; Raffo, María Paula; Kim, Myung Sook; Le Gall, Line

    2016-08-01

    The red alga Polysiphonia morrowii, native to the North Pacific (Northeast Asia), has recently been reported worldwide. To determine the origin of the French and Argentine populations of this introduced species, we compared samples from these two areas with samples collected in Korea and at Hakodate, Japan, the type locality of the species. Combined analyses of chloroplastic (rbcL) and mitochondrial (cox1) DNA revealed that the French and Argentine populations are closely related and differ substantially from the Korean and Japanese populations. The genetic structure of P. morrowii populations from South Atlantic and North Atlantic, which showed high haplotype diversity compared with populations from the North Pacific, suggested the occurrence of multiple introduction events from areas outside of the so-called native regions. Although similar, the French and Argentine populations are not genetically identical. Thus, the genetic structure of these two introduced areas may have been modified by cryptic and recurrent introduction events directly from Asia or from other introduced areas that act as introduction relays. In addition, the large number of private cytoplasmic types identified in the two introduced regions strongly suggests that local populations of P. morrowii existed before the recent detection of these invasions. Our results suggest that the most likely scenario is that the source population(s) of the French and Argentine populations was not located only in the North Pacific and/or that P. morrowii is a cryptogenic species.

  3. Whole-genome sequencing of monozygotic twins discordant for schizophrenia indicates multiple genetic risk factors for schizophrenia

    Jinsong Tang; Fan He; Fengyu Zhang; Yin Yao Shugart; Chunyu Liu; Yanqing Tang; Raymond C.K.Chan; Chuan-Yue Wang; Yong-Gang Yao; Xiaogang Chen; Yu Fan; Hong Li; Qun Xiang; Deng-Feng Zhang; Zongchang Li; Ying He; Yanhui Liao; Ya Wang

    2017-01-01

    Schizophrenia is a common disorder with a high heritability,but its genetic architecture is still elusive.We implemented whole-genome sequencing (WGS) analysis of 8 families with monozygotic (MZ) twin pairs discordant for schizophrenia to assess potential association of de novo mutations (DNMs) or inherited variants with susceptibility to schizophrenia.Eight non-synonymous DNMs (including one splicing site) were identified and shared by twins,which were either located in previously reported schizophrenia risk genes (p.V24689I mutation in TTN,p.S2506T mutation in GCN1L1,IVS3+1G > T in DOCK1) or had a benign to damaging effect according to in silico prediction analysis.By searching the inherited rare damaging or loss-of-function (LOF) variants and common susceptible alleles from three classes of schizophrenia candidate genes,we were able to distill genetic alterations in several schizophrenia risk genes,including GAD1,PLXNA2,RELN and FEZ1.Four inherited copy number variations (CNVs;including a large deletion at 16p13.11) implicated for schizophrenia were identified in four families,respectively.Most of families carried both missense DNMs and inherited risk variants,which might suggest that DNMs,inherited rare damaging variants and common risk alleles together conferred to schizophrenia susceptibility.Our results support that schizophrenia is caused by a combination of multiple genetic factors,with each DNM/variant showing a relatively small effect size.

  4. Energy sorghum--a genetic model for the design of C4 grass bioenergy crops.

    Mullet, John; Morishige, Daryl; McCormick, Ryan; Truong, Sandra; Hilley, Josie; McKinley, Brian; Anderson, Robert; Olson, Sara N; Rooney, William

    2014-07-01

    Sorghum is emerging as an excellent genetic model for the design of C4 grass bioenergy crops. Annual energy Sorghum hybrids also serve as a source of biomass for bioenergy production. Elucidation of Sorghum's flowering time gene regulatory network, and identification of complementary alleles for photoperiod sensitivity, enabled large-scale generation of energy Sorghum hybrids for testing and commercial use. Energy Sorghum hybrids with long vegetative growth phases were found to accumulate more than twice as much biomass as grain Sorghum, owing to extended growing seasons, greater light interception, and higher radiation use efficiency. High biomass yield, efficient nitrogen recycling, and preferential accumulation of stem biomass with low nitrogen content contributed to energy Sorghum's elevated nitrogen use efficiency. Sorghum's integrated genetics-genomics-breeding platform, diverse germplasm, and the opportunity for annual testing of new genetic designs in controlled environments and in multiple field locations is aiding fundamental discovery, and accelerating the improvement of biomass yield and optimization of composition for biofuels production. Recent advances in wide hybridization between Sorghum and other C4 grasses could allow the deployment of improved genetic designs of annual energy Sorghums in the form of wide-hybrid perennial crops. The current trajectory of energy Sorghum genetic improvement indicates that it will be possible to sustainably produce biofuels from C4 grass bioenergy crops that are cost competitive with petroleum-based transportation fuels. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  5. A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

    2016-06-01

    This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

  6. Genetic components to caste allocation in a multiple-queen ant species

    Libbrecht, Romain; Schwander, Tanja; Keller, Laurent

    2011-01-01

    Reproductive division of labor and the coexistence of distinct castes are hallmarks of insect societies. In social insect species with multiple queens per colony, the fitness of nestmate queens directly depends on the process of caste allocation (i.e., the relative investment in queen, sterile

  7. Mapping of the stochastic Lotka-Volterra model to models of population genetics and game theory

    Constable, George W. A.; McKane, Alan J.

    2017-08-01

    The relationship between the M -species stochastic Lotka-Volterra competition (SLVC) model and the M -allele Moran model of population genetics is explored via timescale separation arguments. When selection for species is weak and the population size is large but finite, precise conditions are determined for the stochastic dynamics of the SLVC model to be mappable to the neutral Moran model, the Moran model with frequency-independent selection, and the Moran model with frequency-dependent selection (equivalently a game-theoretic formulation of the Moran model). We demonstrate how these mappings can be used to calculate extinction probabilities and the times until a species' extinction in the SLVC model.

  8. Using hidden Markov models to align multiple sequences.

    Mount, David W

    2009-07-01

    A hidden Markov model (HMM) is a probabilistic model of a multiple sequence alignment (msa) of proteins. In the model, each column of symbols in the alignment is represented by a frequency distribution of the symbols (called a "state"), and insertions and deletions are represented by other states. One moves through the model along a particular path from state to state in a Markov chain (i.e., random choice of next move), trying to match a given sequence. The next matching symbol is chosen from each state, recording its probability (frequency) and also the probability of going to that state from a previous one (the transition probability). State and transition probabilities are multiplied to obtain a probability of the given sequence. The hidden nature of the HMM is due to the lack of information about the value of a specific state, which is instead represented by a probability distribution over all possible values. This article discusses the advantages and disadvantages of HMMs in msa and presents algorithms for calculating an HMM and the conditions for producing the best HMM.

  9. Analysis and application of opinion model with multiple topic interactions.

    Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

    2017-08-01

    To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

  10. Chad Genetic Diversity Reveals an African History Marked by Multiple Holocene Eurasian Migrations.

    Haber, Marc; Mezzavilla, Massimo; Bergström, Anders; Prado-Martinez, Javier; Hallast, Pille; Saif-Ali, Riyadh; Al-Habori, Molham; Dedoussis, George; Zeggini, Eleftheria; Blue-Smith, Jason; Wells, R Spencer; Xue, Yali; Zalloua, Pierre A; Tyler-Smith, Chris

    2016-12-01

    Understanding human genetic diversity in Africa is important for interpreting the evolution of all humans, yet vast regions in Africa, such as Chad, remain genetically poorly investigated. Here, we use genotype data from 480 samples from Chad, the Near East, and southern Europe, as well as whole-genome sequencing from 19 of them, to show that many populations today derive their genomes from ancient African-Eurasian admixtures. We found evidence of early Eurasian backflow to Africa in people speaking the unclassified isolate Laal language in southern Chad and estimate from linkage-disequilibrium decay that this occurred 4,750-7,200 years ago. It brought to Africa a Y chromosome lineage (R1b-V88) whose closest relatives are widespread in present-day Eurasia; we estimate from sequence data that the Chad R1b-V88 Y chromosomes coalesced 5,700-7,300 years ago. This migration could thus have originated among Near Eastern farmers during the African Humid Period. We also found that the previously documented Eurasian backflow into Africa, which occurred ∼3,000 years ago and was thought to be mostly limited to East Africa, had a more westward impact affecting populations in northern Chad, such as the Toubou, who have 20%-30% Eurasian ancestry today. We observed a decline in heterozygosity in admixed Africans and found that the Eurasian admixture can bias inferences on their coalescent history and confound genetic signals from adaptation and archaic introgression. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  11. Genetics of Cd36 and the clustering of multiple cardiovascular risk factors in spontaneous hypertension

    Pravenec, Michal; Zídek, Václav; Šimáková, Miroslava; Křen, Vladimír; Křenová, D.; Horký, K.; Jáchymová, M.; Míková, B.; Kazdová, L.; Aitman, T. J.; Churchill, P. C.; Webb, R. C.; Hingarh, N. H.; Yang, Y.; Wang, J. M.; St.Lezin, E. M.; Kurtz, W. T.

    1999-01-01

    Roč. 103, č. 12 (1999), s. 1651-1657 ISSN 0021-9738 R&D Projects: GA ČR GA306/97/0521; GA ČR GV204/98/K015 Grant - others:NIH(US) ROI HL-56028; NIH(US) PO1 HL-35018; NIH(US) HL-18575 Institutional research plan: CEZ:AV0Z5011922 Keywords : Cd36 * cardiovascular risk factors * spontaneous hypertension Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 10.921, year: 1999

  12. Effects of multiple genetic loci on the pathogenesis from serum urate to gout

    Zheng Dong; Jingru Zhou; Shuai Jiang; Yuan Li; Dongbao Zhao; Chengde Yang; Yanyun Ma; Yi Wang; Hongjun He; Hengdong Ji; Yajun Yang; Xiaofeng Wang; Xia Xu; Yafei Pang; Hejian Zou

    2017-01-01

    Gout is a common arthritis resulting from increased serum urate, and many loci have been identified that are associated with serum urate and gout. However, their influence on the progression from elevated serum urate levels to gout is unclear. This study aims to explore systematically the effects of genetic variants on the pathogenesis in approximately 5,000 Chinese individuals. Six genes (PDZK1, GCKR, TRIM46, HNF4G, SLC17A1, LRRC16A) were determined to be associated with serum urate (P FDR?

  13. hamlet, a binary genetic switch between single- and multiple- dendrite neuron morphology.

    Moore, Adrian W; Jan, Lily Yeh; Jan, Yuh Nung

    2002-08-23

    The dendritic morphology of neurons determines the number and type of inputs they receive. In the Drosophila peripheral nervous system (PNS), the external sensory (ES) neurons have a single nonbranched dendrite, whereas the lineally related multidendritic (MD) neurons have extensively branched dendritic arbors. We report that hamlet is a binary genetic switch between these contrasting morphological types. In hamlet mutants, ES neurons are converted to an MD fate, whereas ectopic hamlet expression in MD precursors results in transformation of MD neurons into ES neurons. Moreover, hamlet expression induced in MD neurons undergoing dendrite outgrowth drastically reduces arbor branching.

  14. An Intelligent Model for Pairs Trading Using Genetic Algorithms.

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

  15. Cost optimization model and its heuristic genetic algorithms

    Liu Wei; Wang Yongqing; Guo Jilin

    1999-01-01

    Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model

  16. Genetics

    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

  17. Direction of Effects in Multiple Linear Regression Models.

    Wiedermann, Wolfgang; von Eye, Alexander

    2015-01-01

    Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.

  18. Investigating multiple solutions in the constrained minimal supersymmetric standard model

    Allanach, B.C. [DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0HA (United Kingdom); George, Damien P. [DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0HA (United Kingdom); Cavendish Laboratory, University of Cambridge,JJ Thomson Avenue, Cambridge, CB3 0HE (United Kingdom); Nachman, Benjamin [SLAC, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States)

    2014-02-07

    Recent work has shown that the Constrained Minimal Supersymmetric Standard Model (CMSSM) can possess several distinct solutions for certain values of its parameters. The extra solutions were not previously found by public supersymmetric spectrum generators because fixed point iteration (the algorithm used by the generators) is unstable in the neighbourhood of these solutions. The existence of the additional solutions calls into question the robustness of exclusion limits derived from collider experiments and cosmological observations upon the CMSSM, because limits were only placed on one of the solutions. Here, we map the CMSSM by exploring its multi-dimensional parameter space using the shooting method, which is not subject to the stability issues which can plague fixed point iteration. We are able to find multiple solutions where in all previous literature only one was found. The multiple solutions are of two distinct classes. One class, close to the border of bad electroweak symmetry breaking, is disfavoured by LEP2 searches for neutralinos and charginos. The other class has sparticles that are heavy enough to evade the LEP2 bounds. Chargino masses may differ by up to around 10% between the different solutions, whereas other sparticle masses differ at the sub-percent level. The prediction for the dark matter relic density can vary by a hundred percent or more between the different solutions, so analyses employing the dark matter constraint are incomplete without their inclusion.

  19. Genetic moderation of multiple pathways linking early cumulative socioeconomic adversity and young adults' cardiometabolic disease risk.

    Wickrama, Kandauda A S; Lee, Tae Kyoung; O'Neal, Catherine Walker

    2018-02-01

    Recent research suggests that psychosocial resources and life stressors are mediating pathways explaining socioeconomic variation in young adults' health risks. However, less research has examined both these pathways simultaneously and their genetic moderation. A nationally representative sample of 11,030 respondents with prospective data collected over 13 years from the National Study of Adolescent to Adult Health was examined. First, the association between early cumulative socioeconomic adversity and young adults' (ages 25-34) cardiometabolic disease risk, as measured by 10 biomarkers, through psychosocial resources (educational attainment) and life stressors (accelerated transition to adulthood) was examined. Second, moderation of these pathways by the serotonin transporter linked polymorphic region gene (5-HTTLPR) was examined. There was evidence for the association between early socioeconomic adversity and young adults' cardiometabolic disease risk directly and indirectly through educational attainment and accelerated transitions. These direct and mediating pathways were amplified by the 5-HTTLPR polymorphism. These findings elucidate how early adversity can have an enduring influence on young adults' cardiometabolic disease risk directly and indirectly through psychosocial resources and life stressors and their genetic moderation. This information suggests that effective intervention and prevention programs should focus on early adversity, youth educational attainment, and their transition to young adulthood.

  20. Multiple genetic variants associated with posttransplantation diabetes mellitus in Chinese Han populations.

    Chen, Jie; Li, Lixin; An, Yunfei; Zhang, Junlong; Liao, Yun; Li, Yi; Wang, Lanlan

    2018-03-01

    Posttransplantation diabetes mellitus (PTDM) is a major complication after solid organ transplantation. This study is to investigate the association of nine genetic variant factors and PTDM in Chinese Han patients. HLA-DP (rs3077, rs9277535), HLA-DQ (rs7453920), signal transducer and activator of transcription 4 (STAT4) (rs7574865), IL-28B (rs12979860, rs8099917, and rs12980275), and IL-18 (rs1946518 and rs187238) were investigated in 260 liver transplant recipients (PTDM vs non-PTDM) by high-resolution melting curve analysis. Serum interleukin (IL)-1β, IL-6, IL-8, IL-17, interferon-γ, inducible protein-10, monocyte chemoattractant protein-1, and macrophage inflammatory protein-1b were analyzed by a Bio-Plex suspension array system (Bio-Plex Multiplex Immunoassays, Bio-Rad, Hercules, CA, USA). Signal transducer and activator of transcription 4 (rs7574865) T allele and IL-18 (rs1946518) A allele increase the risk for insulin resistance and PTDM. Recipients with STAT4 (rs7574865) T allele are associated with an increased concentration of IL-1β, interferon-γ, monocyte chemoattractant protein, and macrophage inflammatory protein-1b. The genetic variants of STAT4 (rs7574865) and IL-18 (rs1946518) may be new important markers for PTDM. © 2017 Wiley Periodicals, Inc.

  1. Characterising and modelling regolith stratigraphy using multiple geophysical techniques

    Thomas, M.; Cremasco, D.; Fotheringham, T.; Hatch, M. A.; Triantifillis, J.; Wilford, J.

    2013-12-01

    Regolith is the weathered, typically mineral-rich layer from fresh bedrock to land surface. It encompasses soil (A, E and B horizons) that has undergone pedogenesis. Below is the weathered C horizon that retains at least some of the original rocky fabric and structure. At the base of this is the lower regolith boundary of continuous hard bedrock (the R horizon). Regolith may be absent, e.g. at rocky outcrops, or may be many 10's of metres deep. Comparatively little is known about regolith, and critical questions remain regarding composition and characteristics - especially deeper where the challenge of collecting reliable data increases with depth. In Australia research is underway to characterise and map regolith using consistent methods at scales ranging from local (e.g. hillslope) to continental scales. These efforts are driven by many research needs, including Critical Zone modelling and simulation. Pilot research in South Australia using digitally-based environmental correlation techniques modelled the depth to bedrock to 9 m for an upland area of 128 000 ha. One finding was the inability to reliably model local scale depth variations over horizontal distances of 2 - 3 m and vertical distances of 1 - 2 m. The need to better characterise variations in regolith to strengthen models at these fine scales was discussed. Addressing this need, we describe high intensity, ground-based multi-sensor geophysical profiling of three hillslope transects in different regolith-landscape settings to characterise fine resolution (i.e. a number of frequencies; multiple frequency, multiple coil electromagnetic induction; and high resolution resistivity. These were accompanied by georeferenced, closely spaced deep cores to 9 m - or to core refusal. The intact cores were sub-sampled to standard depths and analysed for regolith properties to compile core datasets consisting of: water content; texture; electrical conductivity; and weathered state. After preprocessing (filtering, geo

  2. Interaction of multiple biomimetic antimicrobial polymers with model bacterial membranes

    Baul, Upayan, E-mail: upayanb@imsc.res.in; Vemparala, Satyavani, E-mail: vani@imsc.res.in [The Institute of Mathematical Sciences, C.I.T. Campus, Taramani, Chennai 600113 (India); Kuroda, Kenichi, E-mail: kkuroda@umich.edu [Department of Biologic and Materials Sciences, University of Michigan School of Dentistry, Ann Arbor, Michigan 48109 (United States)

    2014-08-28

    Using atomistic molecular dynamics simulations, interaction of multiple synthetic random copolymers based on methacrylates on prototypical bacterial membranes is investigated. The simulations show that the cationic polymers form a micellar aggregate in water phase and the aggregate, when interacting with the bacterial membrane, induces clustering of oppositely charged anionic lipid molecules to form clusters and enhances ordering of lipid chains. The model bacterial membrane, consequently, develops lateral inhomogeneity in membrane thickness profile compared to polymer-free system. The individual polymers in the aggregate are released into the bacterial membrane in a phased manner and the simulations suggest that the most probable location of the partitioned polymers is near the 1-palmitoyl-2-oleoyl-phosphatidylglycerol (POPG) clusters. The partitioned polymers preferentially adopt facially amphiphilic conformations at lipid-water interface, despite lacking intrinsic secondary structures such as α-helix or β-sheet found in naturally occurring antimicrobial peptides.

  3. Fischer 344 and Lewis Rat Strains as a Model of Genetic Vulnerability to Drug Addiction.

    Cadoni, Cristina

    2016-01-01

    Today it is well acknowledged that both nature and nurture play important roles in the genesis of psychopathologies, including drug addiction. Increasing evidence suggests that genetic factors contribute for at least 40-60% of the variation in liability to drug dependence. Human genetic studies suggest that multiple genes of small effect, rather than single genes, contribute to the genesis of behavioral psychopathologies. Therefore, the use of inbred rat strains might provide a valuable tool to identify differences, linked to genotype, important in liability to addiction and related disorders. In this regard, Lewis and Fischer 344 inbred rats have been proposed as a model of genetic vulnerability to drug addiction, given their innate differences in sensitivity to the reinforcing and rewarding effects of drugs of abuse, as well their different responsiveness to stressful stimuli. This review will provide evidence in support of this model for the study of the genetic influence on addiction vulnerability, with particular emphasis on differences in mesolimbic dopamine (DA) transmission, rewarding and emotional function. It will be highlighted that Lewis and Fischer 344 rats differ not only in several indices of DA transmission and adaptive changes following repeated drug exposure, but also in hypothalamic-pituitary-adrenal (HPA) axis responsiveness, influencing not only the ability of the individual to cope with stressful events, but also interfering with rewarding and motivational processes, given the influence of corticosteroids on dopamine neuron functionality. Further differences between the two strains, as impulsivity or anxiousness, might contribute to their different proneness to addiction, and likely these features might be linked to their different DA neurotransmission plasticity. Although differences in other neurotransmitter systems might deserve further investigation, results from the reviewed studies might open new vistas in understanding aberrant

  4. Fischer 344 and Lewis rat strains as a model of genetic vulnerability to drug addiction

    Cristina eCadoni

    2016-02-01

    Full Text Available Today it is well acknowledged that both nature and nurture play important roles in the genesis of psychopathologies, including drug addiction. Increasing evidence suggests that genetic factors contribute for at least 40-60 % of the variation in liability to drug dependence. Human genetic studies suggest that multiple genes of small effect, rather than single genes, contribute to the genesis of behavioral psychopathologies. Therefore the use of inbred rat strains might provide a valuable tool to identify differences, linked to genotype, important in liability to addiction and related disorders. In this regard, Lewis and Fischer 344 inbred rats have been proposed as a model of genetic vulnerability to drug addiction, given their innate differences in sensitivity to the reinforcing and rewarding effects of drugs of abuse, as well their different responsiveness to stressful stimuli. This review will provide evidence in support of this model for the study of the genetic influence on addiction vulnerability, with particular emphasis to differences in mesolimbic dopamine (DA transmission, rewarding and emotional function. It will be highlighted that Lewis and Fischer 344 rats differ not only in several indices of DA transmission and adaptive changes following repeated drug exposure, but also in hypothalamic-pituitary-adrenal (HPA axis responsiveness, influencing not only the ability of the individual to cope with stressful events, but also interfering with rewarding and motivational processes, given the influence of corticosteroids on dopamine neurons functionality.Further differences between the two strains, as impulsivity or anxiousness, might contribute to their different proneness to addiction, and likely these features might be linked to their different DA neurotransmission plasticity. Although differences in other neurotransmitter systems might deserve further investigations, results from the reviewed studies might open new vistas in

  5. An Advanced N -body Model for Interacting Multiple Stellar Systems

    Brož, Miroslav [Astronomical Institute of the Charles University, Faculty of Mathematics and Physics, V Holešovičkách 2, CZ-18000 Praha 8 (Czech Republic)

    2017-06-01

    We construct an advanced model for interacting multiple stellar systems in which we compute all trajectories with a numerical N -body integrator, namely the Bulirsch–Stoer from the SWIFT package. We can then derive various observables: astrometric positions, radial velocities, minima timings (TTVs), eclipse durations, interferometric visibilities, closure phases, synthetic spectra, spectral energy distribution, and even complete light curves. We use a modified version of the Wilson–Devinney code for the latter, in which the instantaneous true phase and inclination of the eclipsing binary are governed by the N -body integration. If all of these types of observations are at one’s disposal, a joint χ {sup 2} metric and an optimization algorithm (a simplex or simulated annealing) allow one to search for a global minimum and construct very robust models of stellar systems. At the same time, our N -body model is free from artifacts that may arise if mutual gravitational interactions among all components are not self-consistently accounted for. Finally, we present a number of examples showing dynamical effects that can be studied with our code and we discuss how systematic errors may affect the results (and how to prevent this from happening).

  6. Negative binomial models for abundance estimation of multiple closed populations

    Boyce, Mark S.; MacKenzie, Darry I.; Manly, Bryan F.J.; Haroldson, Mark A.; Moody, David W.

    2001-01-01

    Counts of uniquely identified individuals in a population offer opportunities to estimate abundance. However, for various reasons such counts may be burdened by heterogeneity in the probability of being detected. Theoretical arguments and empirical evidence demonstrate that the negative binomial distribution (NBD) is a useful characterization for counts from biological populations with heterogeneity. We propose a method that focuses on estimating multiple populations by simultaneously using a suite of models derived from the NBD. We used this approach to estimate the number of female grizzly bears (Ursus arctos) with cubs-of-the-year in the Yellowstone ecosystem, for each year, 1986-1998. Akaike's Information Criteria (AIC) indicated that a negative binomial model with a constant level of heterogeneity across all years was best for characterizing the sighting frequencies of female grizzly bears. A lack-of-fit test indicated the model adequately described the collected data. Bootstrap techniques were used to estimate standard errors and 95% confidence intervals. We provide a Monte Carlo technique, which confirms that the Yellowstone ecosystem grizzly bear population increased during the period 1986-1998.

  7. A diagnostic tree model for polytomous responses with multiple strategies.

    Ma, Wenchao

    2018-04-23

    Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students' problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students' partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM. © 2018 The British Psychological Society.

  8. A minimal model for multiple epidemics and immunity spreading.

    Kim Sneppen

    Full Text Available Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

  9. A minimal model for multiple epidemics and immunity spreading.

    Sneppen, Kim; Trusina, Ala; Jensen, Mogens H; Bornholdt, Stefan

    2010-10-18

    Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

  10. Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

    Almedeij, Jaber

    2012-01-01

    Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

  11. Genetics

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  12. Effect of Keishibukuryogan on Genetic and Dietary Obesity Models

    Fengying Gao

    2015-01-01

    Full Text Available Obesity has been recognized as one of the most important risk factors for a variety of chronic diseases, such as diabetes, hypertension/cardiovascular diseases, steatosis/hepatitis, and cancer. Keishibukuryogan (KBG, Gui Zhi Fu Ling Wan in Chinese is a traditional Chinese/Japanese (Kampo medicine that has been known to improve blood circulation and is also known for its anti-inflammatory or scavenging effect. In this study, we evaluated the effect of KBG in two distinct rodent models of obesity driven by either a genetic (SHR/NDmcr-cp rat model or dietary (high-fat diet-induced mouse obesity model mechanism. Although there was no significant effect on the body composition in either the SHR rat or the DIO mouse models, KBG treatment significantly decreased the serum level of leptin and liver TG level in the DIO mouse, but not in the SHR rat model. Furthermore, a lower fat deposition in liver and a smaller size of adipocytes in white adipose tissue were observed in the DIO mice treated with KBG. Importantly, we further found downregulation of genes involved in lipid metabolism in the KBG-treated liver, along with decreased liver TG and cholesterol level. Our present data experimentally support in fact that KBG can be an attractive Kampo medicine to improve obese status through a regulation of systemic leptin level and/or lipid metabolism.

  13. Multiple surveys employing a new sample-processing protocol reveal the genetic diversity of placozoans in Japan.

    Miyazawa, Hideyuki; Nakano, Hiroaki

    2018-03-01

    Placozoans, flat free-living marine invertebrates, possess an extremely simple bauplan lacking neurons and muscle cells and represent one of the earliest-branching metazoan phyla. They are widely distributed from temperate to tropical oceans. Based on mitochondrial 16S rRNA sequences, 19 haplotypes forming seven distinct clades have been reported in placozoans to date. In Japan, placozoans have been found at nine locations, but 16S genotyping has been performed at only two of these locations. Here, we propose a new processing protocol, "ethanol-treated substrate sampling," for collecting placozoans from natural environments. We also report the collection of placozoans from three new locations, the islands of Shikine-jima, Chichi-jima, and Haha-jima, and we present the distribution of the 16S haplotypes of placozoans in Japan. Multiple surveys conducted at multiple locations yielded five haplotypes that were not reported previously, revealing high genetic diversity in Japan, especially at Shimoda and Shikine-jima Island. The observed geographic distribution patterns were different among haplotypes; some were widely distributed, while others were sampled only from a single location. However, samplings conducted on different dates at the same sites yielded different haplotypes, suggesting that placozoans of a given haplotype do not inhabit the same site constantly throughout the year. Continued sampling efforts conducted during all seasons at multiple locations worldwide and the development of molecular markers within the haplotypes are needed to reveal the geographic distribution pattern and dispersal history of placozoans in greater detail.

  14. Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

    Smith, Kent W.; Sasaki, M. S.

    1979-01-01

    A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

  15. Genetic Variants in Epigenetic Pathways and Risks of Multiple Cancers in the GAME-ON Consortium.

    Toth, Reka; Scherer, Dominique; Kelemen, Linda E; Risch, Angela; Hazra, Aditi; Balavarca, Yesilda; Issa, Jean-Pierre J; Moreno, Victor; Eeles, Rosalind A; Ogino, Shuji; Wu, Xifeng; Ye, Yuanqing; Hung, Rayjean J; Goode, Ellen L; Ulrich, Cornelia M

    2017-06-01

    Background: Epigenetic disturbances are crucial in cancer initiation, potentially with pleiotropic effects, and may be influenced by the genetic background. Methods: In a subsets (ASSET) meta-analytic approach, we investigated associations of genetic variants related to epigenetic mechanisms with risks of breast, lung, colorectal, ovarian and prostate carcinomas using 51,724 cases and 52,001 controls. False discovery rate-corrected P values (q values cancer type. For example, variants in BABAM1 were confirmed as a susceptibility locus for squamous cell lung, overall breast, estrogen receptor (ER)-negative breast, and overall prostate, and overall serous ovarian cancer; the most significant variant was rs4808076 [OR = 1.14; 95% confidence interval (CI) = 1.10-1.19; q = 6.87 × 10 -5 ]. DPF1 rs12611084 was inversely associated with ER-negative breast, endometrioid ovarian, and overall and aggressive prostate cancer risk (OR = 0.93; 95% CI = 0.91-0.96; q = 0.005). Variants in L3MBTL3 were associated with colorectal, overall breast, ER-negative breast, clear cell ovarian, and overall and aggressive prostate cancer risk (e.g., rs9388766: OR = 1.06; 95% CI = 1.03-1.08; q = 0.02). Variants in TET2 were significantly associated with overall breast, overall prostate, overall ovarian, and endometrioid ovarian cancer risk, with rs62331150 showing bidirectional effects. Analyses of subpathways did not reveal gene subsets that contributed disproportionately to susceptibility. Conclusions: Functional and correlative studies are now needed to elucidate the potential links between germline genotype, epigenetic function, and cancer etiology. Impact: This approach provides novel insight into possible pleiotropic effects of genes involved in epigenetic processes. Cancer Epidemiol Biomarkers Prev; 26(6); 816-25. ©2017 AACR . ©2017 American Association for Cancer Research.

  16. System health monitoring using multiple-model adaptive estimation techniques

    Sifford, Stanley Ryan

    Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary

  17. Molecular genetics of cancer and tumorigenesis: Drosophila models

    Wu-Min Deng

    2011-01-01

    Why do some cells not respond to normal control of cell division and become tumorous? Which signals trigger some tumor cells to migrate and colonize other tissues? What genetic factors are responsible for tumorigenesis and cancer development? What environmental factors play a role in cancer formation and progression? In how many ways can our bodies prevent and restrict the growth of cancerous cells?How can we identify and deliver effective drugs to fight cancer? In the fight against cancer,which kills more people than any other disease,these and other questions have long interested researchers from a diverse range of fields.To answer these questions and to fight cancer more effectively,we must increase our understanding of basic cancer biology.Model organisms,including the fruit fly Drosophila melanogaster,have played instrumental roles in our understanding of this devastating disease and the search for effective cures.Drosophila and its highly effective,easy-touse,and ever-expanding genetic tools have contributed toand enriched our knowledge of cancer and tumor formation tremendously.

  18. Genetic variations of patients with familial or multiple melanoma in Southern Brazil.

    Grazziotin, T C; Rey, M C W; Bica, C G; Pinto, L A; Bonamigo, R R; Puig-Butille, J A; Cuellar, F; Puig, S

    2013-02-01

    Patients with familial melanoma or multiple primary melanoma represent a high-risk population to hereditary melanoma. Mutations in susceptibility genes, such as CDKN2A, CDK4 and MC1R, have been associated with the development of melanoma. The purpose of this study was to determine the genotypic background of patients with familial and/or multiple melanoma in southern Brazil. This study analysed 33 cases (5 patients with multiple primary melanoma and 28 patients from families with at least two well documented cases) and 29 controls. Genomic analysis of CDKN2A and CDK4 genes by PCR-SSCP analysis and sequencing and direct sequencing of MC1R were performed in all individuals. No functional mutations in CDKN2A or CDK4 were detected in the 62 individuals. Infrequent variants in polymorphic loci of CDKN2A gene were identified in 15 participants (24.2%) and 24/33 (72.8%) cases and 19/27 (70.4%) controls reported at least one infrequent variant in MC1R (P = 0.372). Furthermore, a non-significant tendency towards an association between melanoma risk and MC1R variants G274A and C451T and a non-significant linear tendency to the number of infrequent high-risk variants in MC1R were observed. These results suggest that in southern Brazilian population, CDKN2A or CDK4 germinal alterations may have a weaker influence than previously thought and environmental risk factors may play a central role in melanoma susceptibility. However, considering the tendency observed for gene MC1R, low-penetrance genes may be a relevant aetiological factor in southern Brazil with fair skin population and high sunlight exposure. © 2012 The Authors. Journal of the European Academy of Dermatology and Venereology © 2012 European Academy of Dermatology and Venereology.

  19. Shared mental models of integrated care: aligning multiple stakeholder perspectives.

    Evans, Jenna M; Baker, G Ross

    2012-01-01

    Health service organizations and professionals are under increasing pressure to work together to deliver integrated patient care. A common understanding of integration strategies may facilitate the delivery of integrated care across inter-organizational and inter-professional boundaries. This paper aims to build a framework for exploring and potentially aligning multiple stakeholder perspectives of systems integration. The authors draw from the literature on shared mental models, strategic management and change, framing, stakeholder management, and systems theory to develop a new construct, Mental Models of Integrated Care (MMIC), which consists of three types of mental models, i.e. integration-task, system-role, and integration-belief. The MMIC construct encompasses many of the known barriers and enablers to integrating care while also providing a comprehensive, theory-based framework of psychological factors that may influence inter-organizational and inter-professional relations. While the existing literature on integration focuses on optimizing structures and processes, the MMIC construct emphasizes the convergence and divergence of stakeholders' knowledge and beliefs, and how these underlying cognitions influence interactions (or lack thereof) across the continuum of care. MMIC may help to: explain what differentiates effective from ineffective integration initiatives; determine system readiness to integrate; diagnose integration problems; and develop interventions for enhancing integrative processes and ultimately the delivery of integrated care. Global interest and ongoing challenges in integrating care underline the need for research on the mental models that characterize the behaviors of actors within health systems; the proposed framework offers a starting point for applying a cognitive perspective to health systems integration.

  20. Comparing ESC and iPSC—Based Models for Human Genetic Disorders

    Tomer Halevy

    2014-10-01

    Full Text Available Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs from patients’ somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn’t be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

  1. Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

    Halevy, Tomer; Urbach, Achia

    2014-10-24

    Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

  2. Variable selection in Logistic regression model with genetic algorithm.

    Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

    2018-02-01

    Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

  3. Ripple-Spreading Network Model Optimization by Genetic Algorithm

    Xiao-Bing Hu

    2013-01-01

    Full Text Available Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

  4. Eye Movement Abnormalities in Multiple Sclerosis: Pathogenesis, Modeling, and Treatment

    Alessandro Serra

    2018-02-01

    Full Text Available Multiple sclerosis (MS commonly causes eye movement abnormalities that may have a significant impact on patients’ disability. Inflammatory demyelinating lesions, especially occurring in the posterior fossa, result in a wide range of disorders, spanning from acquired pendular nystagmus (APN to internuclear ophthalmoplegia (INO, among the most common. As the control of eye movements is well understood in terms of anatomical substrate and underlying physiological network, studying ocular motor abnormalities in MS provides a unique opportunity to gain insights into mechanisms of disease. Quantitative measurement and modeling of eye movement disorders, such as INO, may lead to a better understanding of common symptoms encountered in MS, such as Uhthoff’s phenomenon and fatigue. In turn, the pathophysiology of a range of eye movement abnormalities, such as APN, has been clarified based on correlation of experimental model with lesion localization by neuroimaging in MS. Eye movement disorders have the potential of being utilized as structural and functional biomarkers of early cognitive deficit, and possibly help in assessing disease status and progression, and to serve as platform and functional outcome to test novel therapeutic agents for MS. Knowledge of neuropharmacology applied to eye movement dysfunction has guided testing and use of a number of pharmacological agents to treat some eye movement disorders found in MS, such as APN and other forms of central nystagmus.

  5. Evolution in quantum leaps: multiple combinatorial transfers of HPI and other genetic modules in Enterobacteriaceae.

    Armand Paauw

    Full Text Available Horizontal gene transfer is a key step in the evolution of Enterobacteriaceae. By acquiring virulence determinants of foreign origin, commensals can evolve into pathogens. In Enterobacteriaceae, horizontal transfer of these virulence determinants is largely dependent on transfer by plasmids, phages, genomic islands (GIs and genomic modules (GMs. The High Pathogenicity Island (HPI is a GI encoding virulence genes that can be transferred between different Enterobacteriaceae. We investigated the HPI because it was present in an Enterobacter hormaechei outbreak strain (EHOS. Genome sequence analysis showed that the EHOS contained an integration site for mobile elements and harbored two GIs and three putative GMs, including a new variant of the HPI (HPI-ICEEh1. We demonstrate, for the first time, that combinatorial transfers of GIs and GMs between Enterobacter cloacae complex isolates must have occurred. Furthermore, the excision and circularization of several combinations of the GIs and GMs was demonstrated. Because of its flexibility, the multiple integration site of mobile DNA can be considered an integration hotspot (IHS that increases the genomic plasticity of the bacterium. Multiple combinatorial transfers of diverse combinations of the HPI and other genomic elements among Enterobacteriaceae may accelerate the generation of new pathogenic strains.

  6. Quantitative genetic models of sexual selection by male choice.

    Nakahashi, Wataru

    2008-09-01

    There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

  7. Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

    Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

    2016-11-01

    Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

  8. Experimental Population Genetics in the Introductory Genetics Laboratory Using "Drosophila" as a Model Organism

    Johnson, Ronald; Kennon, Tillman

    2009-01-01

    Hypotheses of population genetics are derived and tested by students in the introductory genetics laboratory classroom as they explore the effects of biotic variables (physical traits of fruit flies) and abiotic variables (island size and distance) on fruit fly populations. In addition to this hypothesis-driven experiment, the development of…

  9. Effects of multiple genetic loci on the pathogenesis from serum urate to gout.

    Dong, Zheng; Zhou, Jingru; Jiang, Shuai; Li, Yuan; Zhao, Dongbao; Yang, Chengde; Ma, Yanyun; Wang, Yi; He, Hongjun; Ji, Hengdong; Yang, Yajun; Wang, Xiaofeng; Xu, Xia; Pang, Yafei; Zou, Hejian; Jin, Li; Wang, Jiucun

    2017-03-02

    Gout is a common arthritis resulting from increased serum urate, and many loci have been identified that are associated with serum urate and gout. However, their influence on the progression from elevated serum urate levels to gout is unclear. This study aims to explore systematically the effects of genetic variants on the pathogenesis in approximately 5,000 Chinese individuals. Six genes (PDZK1, GCKR, TRIM46, HNF4G, SLC17A1, LRRC16A) were determined to be associated with serum urate (P FDR  gene, SLC17A4, contributed to the development of gout from hyperuricemia (OR = 1.56, P FDR  = 3.68E-09; OR = 1.27, P FDR  = 0.013, respectively). Also, HNF4G is a novel gene associated with susceptibility to gout (OR = 1.28, P FDR  = 1.08E-03). In addition, A1CF and TRIM46 were identified as associated with gout in the Chinese population for the first time (P FDR  gout and suggests that urate-associated genes functioning as urate transporters may play a specific role in the pathogenesis of gout. Furthermore, two novel gout-associated genes (HNF4G and SLC17A4) were identified.

  10. Genetic algorithm based optimization of advanced solar cell designs modeled in Silvaco AtlasTM

    Utsler, James

    2006-01-01

    A genetic algorithm was used to optimize the power output of multi-junction solar cells. Solar cell operation was modeled using the Silvaco ATLASTM software. The output of the ATLASTM simulation runs served as the input to the genetic algorithm. The genetic algorithm was run as a diffusing computation on a network of eighteen dual processor nodes. Results showed that the genetic algorithm produced better power output optimizations when compared with the results obtained using the hill cli...

  11. Precise localization of multiple epiphyseal dysplasia and pseudoachondroplasia mutations by genetic and physical mapping of chromosome 19

    Knowlton, R.G.; Cekleniak, J.A. [Jefferson Medical College, Philadelphia, PA (United States); Cohn, D.H. [Cedars-Sinai Medical Center, Los Angeles, CA (United States)] [and others

    1994-09-01

    Multiple epiphyseal dysplasia (EDM1), a dominantly inherited chondrodysplasia resulting in peripheral joint deformities and premature osteoarthritis, and pseudoachondroplasia (PSACH), a more severe disorder associated with short-limbed dwarfism, have recently been mapped to the pericentromeric region of chromosome 19. Chondrocytes from some PSACH patients accumulate lamellar deposits in the endoplasmic reticulum that are immunologically cross-reactive with aggrecan. However, neither aggrecan nor any known candidate gene maps to the EDM1/PSACH region of chromosome 19. Genetic linkage mapping in two lage families had placed the disease locus between D19S215 (19p12) and D19S212 (19p13.1), an interval of about 3.5 Mb. With at least five potentially informative cross-overs within this interval, recombination mapping at greater resolution was undertaken. From cosmids assigned to the region by fluorescence in situ hybridization and contig assembly, dinucleotide repeat tracts were identified for use as polymorphic genetic markers. Linkage data from three new dinucleotide repeat markers from cosmids mapped between D19S212 and D19S215 limit the EDM1/PSACH locus to an interval spanning approximately 2 Mb.

  12. Multiple genetic origins of histidine-rich protein 2 gene deletion in Plasmodium falciparum parasites from Peru

    Akinyi, Sheila; Hayden, Tonya; Gamboa, Dionicia; Torres, Katherine; Bendezu, Jorge; Abdallah, Joseph F.; Griffing, Sean M.; Quezada, Wilmer Marquiño; Arrospide, Nancy; De Oliveira, Alexandre Macedo; Lucas, Carmen; Magill, Alan J.; Bacon, David J.; Barnwell, John W.; Udhayakumar, Venkatachalam

    2013-01-01

    The majority of malaria rapid diagnostic tests (RDTs) detect Plasmodium falciparum histidine-rich protein 2 (PfHRP2), encoded by the pfhrp2 gene. Recently, P. falciparum isolates from Peru were found to lack pfhrp2 leading to false-negative RDT results. We hypothesized that pfhrp2-deleted parasites in Peru derived from a single genetic event. We evaluated the parasite population structure and pfhrp2 haplotype of samples collected between 1998 and 2005 using seven neutral and seven chromosome 8 microsatellite markers, respectively. Five distinct pfhrp2 haplotypes, corresponding to five neutral microsatellite-based clonal lineages, were detected in 1998-2001; pfhrp2 deletions occurred within four haplotypes. In 2003-2005, outcrossing among the parasite lineages resulted in eight population clusters that inherited the five pfhrp2 haplotypes seen previously and a new haplotype; pfhrp2 deletions occurred within four of these haplotypes. These findings indicate that the genetic origin of pfhrp2 deletion in Peru was not a single event, but likely occurred multiple times. PMID:24077522

  13. Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

    Briley, Daniel A.; Tucker-Drob, Elliot M.

    2017-01-01

    The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

  14. Prevalence of multiple sclerosis in Verona, Italy: an epidemiological and genetic study.

    Gajofatto, A; Stefani, A; Turatti, M; Bianchi, M R; Lira, M G; Moretto, G; Salviati, A; Benedetti, M D

    2013-04-01

    Recent multiple sclerosis (MS) prevalence studies classify Italy as a high-risk area without intra-regional latitude effect. To determine MS prevalence in Verona, Italy, and frequency of myelin oligodendrocyte glycoprotein (MOG) gene G511C polymorphism and HLA-DRB1*15 locus in a sample of cases and healthy controls. The study area population on the prevalence date (31 December 2001) was 253208 (133508 women, 119700 men). Multiple case sources were examined. Patients fulfilling McDonald's criteria (2001) were included. Crude, age- and sex-specific prevalence rates were computed. MOG G511C polymorphism and HLA-DRB1*15 were determined by standard methods. We identified 270 cases of MS yielding a crude prevalence rate of 106.6/100000 (95% CI: 94-120). Prevalence was higher in women (140.8/100000) than in men (68.5/100000). The age-adjusted prevalence rate standardized to the European population was 96.0/100000. MOG G511C polymorphism did not differ between cases and controls. HLA-DRB1*15 frequency was 58/155 (37%) in cases and 24/157 (15%) in controls (P<0.001). There was no HLA-DRB1*15 influence on susceptibility to other autoimmune disorders. The high MS prevalence in Verona confirms Italy as a high-risk area with a homogenous distribution across the country. HLA-DRB1*15 is a relevant MS susceptibility locus in the Italian population, possibly with little influence on the occurrence of concomitant autoimmune disorders. © 2012 The Author(s) European Journal of Neurology © 2012 EFNS.

  15. A Drosophila model for toxicogenomics: Genetic variation in susceptibility to heavy metal exposure.

    Shanshan Zhou

    2017-07-01

    Full Text Available The genetic factors that give rise to variation in susceptibility to environmental toxins remain largely unexplored. Studies on genetic variation in susceptibility to environmental toxins are challenging in human populations, due to the variety of clinical symptoms and difficulty in determining which symptoms causally result from toxic exposure; uncontrolled environments, often with exposure to multiple toxicants; and difficulty in relating phenotypic effect size to toxic dose, especially when symptoms become manifest with a substantial time lag. Drosophila melanogaster is a powerful model that enables genome-wide studies for the identification of allelic variants that contribute to variation in susceptibility to environmental toxins, since the genetic background, environmental rearing conditions and toxic exposure can be precisely controlled. Here, we used extreme QTL mapping in an outbred population derived from the D. melanogaster Genetic Reference Panel to identify alleles associated with resistance to lead and/or cadmium, two ubiquitous environmental toxins that present serious health risks. We identified single nucleotide polymorphisms (SNPs associated with variation in resistance to both heavy metals as well as SNPs associated with resistance specific to each of them. The effects of these SNPs were largely sex-specific. We applied mutational and RNAi analyses to 33 candidate genes and functionally validated 28 of them. We constructed networks of candidate genes as blueprints for orthologous networks of human genes. The latter not only provided functional contexts for known human targets of heavy metal toxicity, but also implicated novel candidate susceptibility genes. These studies validate Drosophila as a translational toxicogenomics gene discovery system.

  16. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

    Liqiang Zhang

    2013-01-01

    Full Text Available The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD and parallel FOR loop (PARFOR, is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

  17. Mathematical Modeling of Loop Heat Pipes with Multiple Capillary Pumps and Multiple Condensers. Part 1; Stead State Stimulations

    Hoang, Triem T.; OConnell, Tamara; Ku, Jentung

    2004-01-01

    Loop Heat Pipes (LHPs) have proven themselves as reliable and robust heat transport devices for spacecraft thermal control systems. So far, the LHPs in earth-orbit satellites perform very well as expected. Conventional LHPs usually consist of a single capillary pump for heat acquisition and a single condenser for heat rejection. Multiple pump/multiple condenser LHPs have shown to function very well in ground testing. Nevertheless, the test results of a dual pump/condenser LHP also revealed that the dual LHP behaved in a complicated manner due to the interaction between the pumps and condensers. Thus it is redundant to say that more research is needed before they are ready for 0-g deployment. One research area that perhaps compels immediate attention is the analytical modeling of LHPs, particularly the transient phenomena. Modeling a single pump/single condenser LHP is difficult enough. Only a handful of computer codes are available for both steady state and transient simulations of conventional LHPs. No previous effort was made to develop an analytical model (or even a complete theory) to predict the operational behavior of the multiple pump/multiple condenser LHP systems. The current research project offered a basic theory of the multiple pump/multiple condenser LHP operation. From it, a computer code was developed to predict the LHP saturation temperature in accordance with the system operating and environmental conditions.

  18. Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

    Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.

    2011-01-01

    This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models

  19. Global and 3D spatial assessment of neuroinflammation in rodent models of Multiple Sclerosis.

    Shashank Gupta

    Full Text Available Multiple Sclerosis (MS is a progressive autoimmune inflammatory and demyelinating disease of the central nervous system (CNS. T cells play a key role in the progression of neuroinflammation in MS and also in the experimental autoimmune encephalomyelitis (EAE animal models for the disease. A technology for quantitative and 3 dimensional (3D spatial assessment of inflammation in this and other CNS inflammatory conditions is much needed. Here we present a procedure for 3D spatial assessment and global quantification of the development of neuroinflammation based on Optical Projection Tomography (OPT. Applying this approach to the analysis of rodent models of MS, we provide global quantitative data of the major inflammatory component as a function of the clinical course. Our data demonstrates a strong correlation between the development and progression of neuroinflammation and clinical disease in several mouse and a rat model of MS refining the information regarding the spatial dynamics of the inflammatory component in EAE. This method provides a powerful tool to investigate the effect of environmental and genetic forces and for assessing the therapeutic effects of drug therapy in animal models of MS and other neuroinflammatory/neurodegenerative disorders.

  20. Causal models in epidemiology: past inheritance and genetic future

    Kriebel David

    2006-07-01

    Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional

  1. GRAVITATIONAL LENS MODELING WITH GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZERS

    Rogers, Adam; Fiege, Jason D.

    2011-01-01

    Strong gravitational lensing of an extended object is described by a mapping from source to image coordinates that is nonlinear and cannot generally be inverted analytically. Determining the structure of the source intensity distribution also requires a description of the blurring effect due to a point-spread function. This initial study uses an iterative gravitational lens modeling scheme based on the semilinear method to determine the linear parameters (source intensity profile) of a strongly lensed system. Our 'matrix-free' approach avoids construction of the lens and blurring operators while retaining the least-squares formulation of the problem. The parameters of an analytical lens model are found through nonlinear optimization by an advanced genetic algorithm (GA) and particle swarm optimizer (PSO). These global optimization routines are designed to explore the parameter space thoroughly, mapping model degeneracies in detail. We develop a novel method that determines the L-curve for each solution automatically, which represents the trade-off between the image χ 2 and regularization effects, and allows an estimate of the optimally regularized solution for each lens parameter set. In the final step of the optimization procedure, the lens model with the lowest χ 2 is used while the global optimizer solves for the source intensity distribution directly. This allows us to accurately determine the number of degrees of freedom in the problem to facilitate comparison between lens models and enforce positivity on the source profile. In practice, we find that the GA conducts a more thorough search of the parameter space than the PSO.

  2. The use of genetic algorithms to model protoplanetary discs

    Hetem, Annibal; Gregorio-Hetem, Jane

    2007-12-01

    The protoplanetary discs of T Tauri and Herbig Ae/Be stars have previously been studied using geometric disc models to fit their spectral energy distribution (SED). The simulations provide a means to reproduce the signatures of various circumstellar structures, which are related to different levels of infrared excess. With the aim of improving our previous model, which assumed a simple flat-disc configuration, we adopt here a reprocessing flared-disc model that assumes hydrostatic, radiative equilibrium. We have developed a method to optimize the parameter estimation based on genetic algorithms (GAs). This paper describes the implementation of the new code, which has been applied to Herbig stars from the Pico dos Dias Survey catalogue, in order to illustrate the quality of the fitting for a variety of SED shapes. The star AB Aur was used as a test of the GA parameter estimation, and demonstrates that the new code reproduces successfully a canonical example of the flared-disc model. The GA method gives a good quality of fit, but the range of input parameters must be chosen with caution, as unrealistic disc parameters can be derived. It is confirmed that the flared-disc model fits the flattened SEDs typical of Herbig stars; however, embedded objects (increasing SED slope) and debris discs (steeply decreasing SED slope) are not well fitted with this configuration. Even considering the limitation of the derived parameters, the automatic process of SED fitting provides an interesting tool for the statistical analysis of the circumstellar luminosity of large samples of young stars.

  3. From animal models to human disease: a genetic approach for personalized medicine in ALS.

    Picher-Martel, Vincent; Valdmanis, Paul N; Gould, Peter V; Julien, Jean-Pierre; Dupré, Nicolas

    2016-07-11

    Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disease in adults. Classical ALS is characterized by the death of upper and lower motor neurons leading to progressive paralysis. Approximately 10 % of ALS patients have familial form of the disease. Numerous different gene mutations have been found in familial cases of ALS, such as mutations in superoxide dismutase 1 (SOD1), TAR DNA-binding protein 43 (TDP-43), fused in sarcoma (FUS), C9ORF72, ubiquilin-2 (UBQLN2), optineurin (OPTN) and others. Multiple animal models were generated to mimic the disease and to test future treatments. However, no animal model fully replicates the spectrum of phenotypes in the human disease and it is difficult to assess how a therapeutic effect in disease models can predict efficacy in humans. Importantly, the genetic and phenotypic heterogeneity of ALS leads to a variety of responses to similar treatment regimens. From this has emerged the concept of personalized medicine (PM), which is a medical scheme that combines study of genetic, environmental and clinical diagnostic testing, including biomarkers, to individualized patient care. In this perspective, we used subgroups of specific ALS-linked gene mutations to go through existing animal models and to provide a comprehensive profile of the differences and similarities between animal models of disease and human disease. Finally, we reviewed application of biomarkers and gene therapies relevant in personalized medicine approach. For instance, this includes viral delivering of antisense oligonucleotide and small interfering RNA in SOD1, TDP-43 and C9orf72 mice models. Promising gene therapies raised possibilities for treating differently the major mutations in familial ALS cases.

  4. Stabilization of multiple rib fractures in a canine model.

    Huang, Ke-Nan; Xu, Zhi-Fei; Sun, Ju-Xian; Ding, Xin-Yu; Wu, Bin; Li, Wei; Qin, Xiong; Tang, Hua

    2014-12-01

    Operative stabilization is frequently used in the clinical treatment of multiple rib fractures (MRF); however, no ideal material exists for use in this fixation. This study investigates a newly developed biodegradable plate system for the stabilization of MRF. Silk fiber-reinforced polycaprolactone (SF/PCL) plates were developed for rib fracture stabilization and studied using a canine flail chest model. Adult mongrel dogs were divided into three groups: one group received the SF/PCL plates, one group received standard clinical steel plates, and the final group did not undergo operative fracture stabilization (n = 6 for each group). Radiographic, mechanical, and histologic examination was performed to evaluate the effectiveness of the biodegradable material for the stabilization of the rib fractures. No nonunion and no infections were found when using SF-PCL plates. The fracture sites collapsed in the untreated control group, leading to obvious chest wall deformity not encountered in the two groups that underwent operative stabilization. Our experimental study shows that the SF/PCL plate has the biocompatibility and mechanical strength suitable for fixation of MRF and is potentially ideal for the treatment of these injuries. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Multiplicative multifractal modeling and discrimination of human neuronal activity

    Zheng Yi; Gao Jianbo; Sanchez, Justin C.; Principe, Jose C.; Okun, Michael S.

    2005-01-01

    Understanding neuronal firing patterns is one of the most important problems in theoretical neuroscience. It is also very important for clinical neurosurgery. In this Letter, we introduce a computational procedure to examine whether neuronal firing recordings could be characterized by cascade multiplicative multifractals. By analyzing raw recording data as well as generated spike train data from 3 patients collected in two brain areas, the globus pallidus externa (GPe) and the globus pallidus interna (GPi), we show that the neural firings are consistent with a multifractal process over certain time scale range (t 1 ,t 2 ), where t 1 is argued to be not smaller than the mean inter-spike-interval of neuronal firings, while t 2 may be related to the time that neuronal signals propagate in the major neural branching structures pertinent to GPi and GPe. The generalized dimension spectrum D q effectively differentiates the two brain areas, both intra- and inter-patients. For distinguishing between GPe and GPi, it is further shown that the cascade model is more effective than the methods recently examined by Schiff et al. as well as the Fano factor analysis. Therefore, the methodology may be useful in developing computer aided tools to help clinicians perform precision neurosurgery in the operating room

  6. A Fuzzy Logic Framework for Integrating Multiple Learned Models

    Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)

    1999-03-01

    The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

  7. Multiple models guide strategies for agricultural nutrient reductions

    Scavia, Donald; Kalcic, Margaret; Muenich, Rebecca Logsdon; Read, Jennifer; Aloysius, Noel; Bertani, Isabella; Boles, Chelsie; Confesor, Remegio; DePinto, Joseph; Gildow, Marie; Martin, Jay; Redder, Todd; Robertson, Dale M.; Sowa, Scott P.; Wang, Yu-Chen; Yen, Haw

    2017-01-01

    In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load-reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.

  8. Genetic diversity and antimicrobial resistance of Escherichia coli from human and animal sources uncovers multiple resistances from human sources.

    A Mark Ibekwe

    Full Text Available Escherichia coli are widely used as indicators of fecal contamination, and in some cases to identify host sources of fecal contamination in surface water. Prevalence, genetic diversity and antimicrobial susceptibility were determined for 600 generic E. coli isolates obtained from surface water and sediment from creeks and channels along the middle Santa Ana River (MSAR watershed of southern California, USA, after a 12 month study. Evaluation of E. coli populations along the creeks and channels showed that E. coli were more prevalent in sediment compared to surface water. E. coli populations were not significantly different (P = 0.05 between urban runoff sources and agricultural sources, however, E. coli genotypes determined by pulsed-field gel electrophoresis (PFGE were less diverse in the agricultural sources than in urban runoff sources. PFGE also showed that E. coli populations in surface water were more diverse than in the sediment, suggesting isolates in sediment may be dominated by clonal populations.Twenty four percent (144 isolates of the 600 isolates exhibited resistance to more than one antimicrobial agent. Most multiple resistances were associated with inputs from urban runoff and involved the antimicrobials rifampicin, tetracycline, and erythromycin. The occurrence of a greater number of E. coli with multiple antibiotic resistances from urban runoff sources than agricultural sources in this watershed provides useful evidence in planning strategies for water quality management and public health protection.

  9. Calcium Intervention Ameliorates Experimental Model of Multiple Sclerosis

    Dariush Haghmorad

    2014-05-01

    Full Text Available Objective: Multiple sclerosis (MS is the most common inflammatory disease of the CNS. Experimental autoimmune encephalomyelitis (EAE is a widely used model for MS. In the present research, our aim was to test the therapeutic efficacy of Calcium (Ca in an experimental model of MS. Methods: In this study the experiment was done on C57BL/6 mice. EAE was induced using 200 μg of the MOG35-55 peptide emulsified in CFA and injected subcutaneously on day 0 over two flank areas. In addition, 250 ng of pertussis toxin was injected on days 0 and 2. In the treatment group, 30 mg/kg Ca was administered intraperitoneally four times at regular 48 hour intervals. The mice were sacrificed 21 days after EAE induction and blood samples were taken from their hearts. The brains of mice were removed for histological analysis and their isolated splenocytes were cultured. Results: Our results showed that treatment with Ca caused a significant reduction in the severity of the EAE. Histological analysis indicated that there was no plaque in brain sections of Ca treated group of mice whereas 4 ± 1 plaques were detected in brain sections of controls. The density of mononuclear infiltration in the CNS of Ca treated mice was lower than in controls. The serum level of Nitric Oxide in the treatment group was lower than in the control group but was not significant. Moreover, the levels of IFN-γ in cell culture supernatant of splenocytes in treated mice were significantly lower than in the control group. Conclusion: The data indicates that Ca intervention can effectively attenuate EAE progression.

  10. Genetic analysis of yeast RPA1 reveals its multiple functions in DNA metabolism

    Umezu, K.; Sugawara, N.; Chen, C.; Haber, J.E.; Kolodner, R.D.

    1998-01-01

    Replication protein A (RPA) is a single-stranded DNA-binding protein identified as an essential factor for SV40 DNA replication in vitro. To understand the in vivo functions of RPA, we mutagenized the Saccharomyces cerevisiae RFA1 gene and identified 19 ultraviolet light (UV) irradiation- and methyl methane sulfonate (MMS)-sensitive mutants and 5 temperature-sensitive mutants. The UV- and MMS-sensitive mutants showed up to 10 4 to 10 5 times increased sensitivity to these agents. Some of the UV- and MMSsensitive mutants were killed by an HO-induced double-strand break atMAT. Physical analysis of recombination in one UV- and MMS-sensitive rfa1 mutant demonstrated that it was defective for mating type switching and single-strand annealing recombination. Two temperature-sensitive mutants were characterized in detail, and at the restrictive temperature were found to have an arrest phenotype and DNA content indicative of incomplete DNA replication. DNA sequence analysis indicated that most of the mutations altered amino acids that were conserved between yeast, human, and Xenopus RPA1. Taken together, we conclude that RPA1 has multiple roles in vivo and functions in DNA replication, repair, and recombination, like the single-stranded DNA-binding proteins of bacteria and phages. (author)

  11. Genetic transformation and gene silencing mediated by multiple copies of a transgene in eastern white pine.

    Tang, Wei; Newton, Ronald J; Weidner, Douglas A

    2007-01-01

    An efficient transgenic eastern white pine (Pinus strobus L.) plant regeneration system has been established using Agrobacterium tumefaciens strain GV3850-mediated transformation and the green fluorescent protein (gfp) gene as a reporter in this investigation. Stable integration of transgenes in the plant genome of pine was confirmed by polymerase chain reaction (PCR), Southern blot, and northern blot analyses. Transgene expression was analysed in pine T-DNA transformants carrying different numbers of copies of T-DNA insertions. Post-transcriptional gene silencing (PTGS) was mostly obtained in transgenic lines with more than three copies of T-DNA, but not in transgenic lines with one copy of T-DNA. In situ hybridization chromosome analysis of transgenic lines demonstrated that silenced transgenic lines had two or more T-DNA insertions in the same chromosome. These results suggest that two or more T-DNA insertions in the same chromosome facilitate efficient gene silencing in transgenic pine cells expressing green fluorescent protein. There were no differences in shoot differentiation and development between transgenic lines with multiple T-DNA copies and transgenic lines with one or two T-DNA copies.

  12. Phylogeography and postglacial recolonization of Europe by Rhinolophus hipposideros: evidence from multiple genetic markers.

    Dool, Serena E; Puechmaille, Sébastien J; Dietz, Christian; Juste, Javier; Ibáñez, Carlos; Hulva, Pavel; Roué, Stéphane G; Petit, Eric J; Jones, Gareth; Russo, Danilo; Toffoli, Roberto; Viglino, Andrea; Martinoli, Adriano; Rossiter, Stephen J; Teeling, Emma C

    2013-08-01

    The demographic history of Rhinolophus hipposideros (lesser horseshoe bat) was reconstructed across its European, North African and Middle-Eastern distribution prior to, during and following the most recent glaciations by generating and analysing a multimarker data set. This data set consisted of an X-linked nuclear intron (Bgn; 543 bp), mitochondrial DNA (cytb-tRNA-control region; 1630 bp) and eight variable microsatellite loci for up to 373 individuals from 86 localities. Using this data set of diverse markers, it was possible to determine the species' demography at three temporal stages. Nuclear intron data revealed early colonization into Europe from the east, which pre-dates the Quaternary glaciations. The mtDNA data supported multiple glacial refugia across the Mediterranean, the largest of which were found in the Ibero-Maghreb region and an eastern location (Anatolia/Middle East)-that were used by R. hipposideros during the most recent glacial cycles. Finally, microsatellites provided the most recent information on these species' movements since the Last Glacial Maximum and suggested that lineages that had diverged into glacial refugia, such as in the Ibero-Maghreb region, have remained isolated. These findings should be used to inform future conservation management strategies for R. hipposideros and show the power of using a multimarker data set for phylogeographic studies. © 2013 John Wiley & Sons Ltd.

  13. Mycobacterium tuberculosis Acquires Limited Genetic Diversity in Prolonged Infections, Reactivations and Transmissions Involving Multiple Hosts

    Marta Herranz

    2018-01-01

    Full Text Available Background:Mycobacterium tuberculosis (MTB has limited ability to acquire variability. Analysis of its microevolution might help us to evaluate the pathways followed to acquire greater infective success. Whole-genome sequencing (WGS in the analysis of the transmission of MTB has elucidated the magnitude of variability in MTB. Analysis of transmission currently depends on the identification of clusters, according to the threshold of variability (<5 SNPs between isolates.Objective: We evaluated whether the acquisition of variability in MTB, was more frequent in situations which could favor it, namely intrapatient, prolonged infections or reactivations and interpatient transmissions involving multiple sequential hosts.Methods: We used WGS to analyze the accumulation of variability in sequential isolates from prolonged infections or translations from latency to reactivation. We then measured microevolution in transmission clusters with prolonged transmission time, high number of involved cases, simultaneous involvement of latency and active transmission.Results: Intrapatient and interpatient acquisition of variability was limited, within the ranges expected according to the thresholds of variability proposed, even though bursts of variability were observed.Conclusions: The thresholds of variability proposed for MTB seem to be valid in most circumstances, including those theoretically favoring acquisition of variability. Our data point to multifactorial modulation of microevolution, although further studies are necessary to elucidate the factors underlying this modulation.

  14. Genetic and environmental determinants of 25-hydroxyvitamin D levels in multiple sclerosis

    Laursen, Julie H.; Søndergaard, Helle Bach; Albrechtsen, Anders

    2015-01-01

    BACKGROUND: Evidence is accumulating supporting a beneficial effect of vitamin D in multiple sclerosis (MS). Genome-wide association studies (GWAS) have shown significant associations between 25-hydroxyvitamin D (25(OH)D) and single nucleotide polymorphisms (SNPs) in key genes in the vitamin D...... discrimination (Life Technologies).RESULTS: We found significant associations between 25(OH)D and SNPs in GC (rs7041, p = 0.01 and rs2282679, p = 0.03) and CYP2R1 (rs10741657, p =1.8 × 10(-4)). Season of blood sampling (p = 2.8 × 10(-31)), sex (p = 1.9 × 10(-5)), BMI (p = 2.3 × 10(-5)), vitamin supplements (p...... = 7.0 × 10(-22)), and fish intake (p = 0.02) also had significant effects on 25(OH)D.CONCLUSION: In this cross-sectional study, we found significant effects of environmental factors and SNPs in GC and CYP2R1 on 25(OH)D in MS patients. Since 25(OH)D might have protective effects in MS, and vitamin D...

  15. HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

    Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

    2017-01-15

    Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodologies is that a single imaging pattern can distinguish between healthy and diseased populations, or between two subgroups of patients (e.g., progressors vs. non-progressors). This assumption effectively ignores the ample evidence for the heterogeneous nature of brain diseases. Neurodegenerative, neuropsychiatric and neurodevelopmental disorders are largely characterized by high clinical heterogeneity, which likely stems in part from underlying neuroanatomical heterogeneity of various pathologies. Detecting and characterizing heterogeneity may deepen our understanding of disease mechanisms and lead to patient-specific treatments. However, few approaches tackle disease subtype discovery in a principled machine learning framework. To address this challenge, we present a novel non-linear learning algorithm for simultaneous binary classification and subtype identification, termed HYDRA (Heterogeneity through Discriminative Analysis). Neuroanatomical subtypes are effectively captured by multiple linear hyperplanes, which form a convex polytope that separates two groups (e.g., healthy controls from pathologic samples); each face of this polytope effectively defines a disease subtype. We validated HYDRA on simulated and clinical data. In the latter case, we applied the proposed method independently to the imaging and genetic datasets of the Alzheimer's Disease Neuroimaging Initiative (ADNI 1) study. The imaging dataset consisted of T1-weighted volumetric magnetic resonance images of 123 AD patients and 177 controls. The genetic dataset consisted of single nucleotide polymorphism information of 103 AD patients and 139 controls. We identified 3 reproducible subtypes of atrophy in AD relative to controls: (1) diffuse and extensive

  16. A ¤flexible additive multiplicative hazard model

    Martinussen, T.; Scheike, T. H.

    2002-01-01

    Aalen's additive model; Counting process; Cox regression; Hazard model; Proportional excess harzard model; Time-varying effect......Aalen's additive model; Counting process; Cox regression; Hazard model; Proportional excess harzard model; Time-varying effect...

  17. Investigation of the three-dimensional lattice HP protein folding model using a genetic algorithm

    Fábio L. Custódio

    2004-01-01

    Full Text Available An approach to the hydrophobic-polar (HP protein folding model was developed using a genetic algorithm (GA to find the optimal structures on a 3D cubic lattice. A modification was introduced to the scoring system of the original model to improve the model's capacity to generate more natural-like structures. The modification was based on the assumption that it may be preferable for a hydrophobic monomer to have a polar neighbor than to be in direct contact with the polar solvent. The compactness and the segregation criteria were used to compare structures created by the original HP model and by the modified one. An islands' algorithm, a new selection scheme and multiple-points crossover were used to improve the performance of the algorithm. Ten sequences, seven with length 27 and three with length 64 were analyzed. Our results suggest that the modified model has a greater tendency to form globular structures. This might be preferable, since the original HP model does not take into account the positioning of long polar segments. The algorithm was implemented in the form of a program with a graphical user interface that might have a didactical potential in the study of GA and on the understanding of hydrophobic core formation.

  18. The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

    Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

    2014-01-01

    In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

  19. Expression and Genetic Analysis of MicroRNAs Involved in Multiple Sclerosis

    Daniela Galimberti

    2013-02-01

    Full Text Available Evidence underlines the importance of microRNAs (miRNAs in the pathogenesis of multiple sclerosis (MS. Based on the fact that miRNAs are present in human biological fluids, we previously showed that miR-223, miR-23a and miR-15b levels were downregulated in the sera of MS patients versus controls. Here, the expression levels of these candidate miRNAs were determined in peripheral blood mononuclear cells (PBMCs and the serum of MS patients, in addition to three genotyped single nucleotide polymorphisms (SNPs. Mapping in the genomic regions of miR-223, miR-23a and miR-15b genes, 399 cases and 420 controls were tested. Expression levels of miR-223 and miR-23a were altered in PBMCs from MS patients versus controls. Conversely, there were no differences in the expression levels of miR-15b. A significantly decreased genotypic frequency of miR-223 rs1044165 T/T genotype was observed in MS patients. Moreover, the allelic frequency of miR-23a rs3745453 C allele was significantly increased in patients versus controls. In contrast, there were no differences in the distribution of miR-15b SNP. In conclusion, our results suggest that miR-223 and miR-23a could play a role in the pathogenesis of MS. Moreover, miR-223 rs1044165 polymorphism likely acts as a protective factor, while miR-23a rs3745453 variant seems to act as a risk factor for MS.

  20. Expression and Genetic Analysis of MicroRNAs Involved in Multiple Sclerosis.

    Ridolfi, Elisa; Fenoglio, Chiara; Cantoni, Claudia; Calvi, Alberto; De Riz, Milena; Pietroboni, Anna; Villa, Chiara; Serpente, Maria; Bonsi, Rossana; Vercellino, Marco; Cavalla, Paola; Galimberti, Daniela; Scarpini, Elio

    2013-02-25

    Evidence underlines the importance of microRNAs (miRNAs) in the pathogenesis of multiple sclerosis (MS). Based on the fact that miRNAs are present in human biological fluids, we previously showed that miR-223, miR-23a and miR-15b levels were downregulated in the sera of MS patients versus controls. Here, the expression levels of these candidate miRNAs were determined in peripheral blood mononuclear cells (PBMCs) and the serum of MS patients, in addition to three genotyped single nucleotide polymorphisms (SNPs). Mapping in the genomic regions of miR-223, miR-23a and miR-15b genes, 399 cases and 420 controls were tested. Expression levels of miR-223 and miR-23a were altered in PBMCs from MS patients versus controls. Conversely, there were no differences in the expression levels of miR-15b. A significantly decreased genotypic frequency of miR-223 rs1044165 T/T genotype was observed in MS patients. Moreover, the allelic frequency of miR-23a rs3745453 C allele was significantly increased in patients versus controls. In contrast, there were no differences in the distribution of miR-15b SNP. In conclusion, our results suggest that miR-223 and miR-23a could play a role in the pathogenesis of MS. Moreover, miR-223 rs1044165 polymorphism likely acts as a protective factor, while miR-23a rs3745453 variant seems to act as a risk factor for MS.

  1. BSG and MCT1 Genetic Variants Influence Survival in Multiple Myeloma Patients

    Piotr Łacina

    2018-04-01

    Full Text Available Multiple myeloma (MM is a haematologic malignancy characterized by the presence of atypical plasma cells. Basigin (BSG, CD147 controls lactate export through the monocarboxylic acid transporter 1 (MCT1, SLC16A1 and supports MM survival and proliferation. Additionally, BSG is implicated in response to treatment with immunomodulatory drugs (thalidomide and its derivatives. We investigated the role of single nucleotide polymorphisms (SNPs in the gene coding for BSG and SLC16A1 in MM. Following an in silico analysis, eight SNPs (four in BSG and four in SLC16A1 predicted to have a functional effect were selected and analyzed in 135 MM patients and 135 healthy individuals. Alleles rs4919859 C, rs8637 G, and haplotype CG were associated with worse progression-free survival (p = 0.006, p = 0.017, p = 0.002, respectively, while rs7556664 A, rs7169 T and rs1049434 A (all in linkage disequilibrium (LD, r2 > 0.98 were associated with better overall survival (p = 0.021. Similar relationships were observed in thalidomide-treated patients. Moreover, rs4919859 C, rs8637 G, rs8259 A and the CG haplotype were more common in patients in stages II–III of the International Staging System (p < 0.05, while rs8259 A correlated with higher levels of β-2-microglobulin and creatinine (p < 0.05. Taken together, our results show that BSG and SLC16A1 variants affect survival, and may play an important role in MM.

  2. Exclusive description of multiple production on nuclei in the additive quark model. Multiplicity distributions in interactions with heavy nuclei

    Levchenko, B.B.; Nikolaev, N.N.

    1985-01-01

    In the framework of the additive quark model of multiple production on nuclei we calculate the multiplicity distributions of secondary particles and the correlations between secondary particles in πA and pA interactions with heavy nuclei. We show that intranuclear cascades are responsible for up to 50% of the nuclear increase of the multiplicity of fast particles. We analyze the sensitivity of the multiplicities and their correlations to the choice of the quark-hadronization function. We show that with good accuracy the yield of relativistic secondary particles from heavy and intermediate nuclei depends only on the number N/sub p/ of protons knocked out of the nucleus, and not on the mass number of the nucleus (N/sub p/ scaling)

  3. Comparative study between a QCD inspired model and a multiple diffraction model

    Luna, E.G.S.; Martini, A.F.; Menon, M.J.

    2003-01-01

    A comparative study between a QCD Inspired Model (QCDIM) and a Multiple Diffraction Model (MDM) is presented, with focus on the results for pp differential cross section at √s = 52.8 GeV. It is shown that the MDM predictions are in agreement with experimental data, except for the dip region and that the QCDIM describes only the diffraction peak region. Interpretations in terms of the corresponding eikonals are also discussed. (author)

  4. Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening.

    Quarterman, Josh; Kim, Soo Rin; Kim, Pan-Jun; Jin, Yong-Su

    2015-01-20

    In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Genetic structure of Phytophthora infestans populations in China indicates multiple migration events.

    Guo, Liyun; Zhu, Xiao-Qiong; Hu, Chia-Hui; Ristaino, Jean Beagle

    2010-10-01

    One hundred isolates of Phytophthora infestans collected from 10 provinces in China between 1998 and 2004 were analyzed for mating type, metalaxyl resistance, mitochondrial DNA (mtDNA) haplotype, allozyme genotype, and restriction fragment length polymorphism (RFLP) with the RG-57 probe. In addition, herbarium samples collected in China, Russia, Australia, and other Asian countries were also typed for mtDNA haplotype. The Ia haplotype was found during the first outbreaks of the disease in China (1938 and 1940), Japan (1901, 1930, and 1931), India (1913), Peninsular Malaysia (1950), Nepal (1954), The Philippines (1910), Australia (1917), Russia (1917), and Latvia (1935). In contrast, the Ib haplotype was found after 1950 in China on both potato and tomato (1952, 1954, 1956, and 1982) and in India (1968 and 1974). Another migration of a genotype found in Siberia called SIB-1 (Glucose-6-phosphate isomerase [Gpi] 100/100, Peptidase [Pep] 100/100, IIa mtDNA haplotype) was identified using RFLP fingerprints among 72% of the isolates and was widely distributed in the north and south of China and has also been reported in Japan. A new genotype named CN-11 (Gpi 100/111, Pep 100/100, IIb mtDNA haplotype), found only in the south of China, and two additional genotypes (Gpi 100/100, Pep 100/100, Ia mtDNA haplotype) named CN-9 and CN-10 were identified. There were more diverse genotypes among isolates from Yunnan province than elsewhere. The SIB-1 (IIa) genotype is identical to those from Siberia, suggesting later migration of this genotype from either Russia or Japan into China. The widespread predominance of SIB-1 suggests that this genotype has enhanced fitness compared with other genotypes found. Movement of the pathogen into China via infected seed from several sources most likely accounts for the distribution of pathogen genotypes observed. MtDNA haplotype evidence and RFLP data suggest multiple migrations of the pathogen into China after the initial introduction of the

  6. Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches

    Kramer, Koen; van der Werf, D. C.

    2010-01-01

    The environment is changing and so are forests, in their functioning, in species composition, and in the species’ genetic composition. Many empirical and process-based models exist to support forest management. However, most of these models do not consider the impact of environmental changes and forest management on genetic diversity nor on the rate of adaptation of critical plant processes. How genetic diversity and rates of adaptation depend on management actions is a crucial next step in m...

  7. A method for detecting IBD regions simultaneously in multiple individuals--with applications to disease genetics

    Moltke, Ida; Albrechtsen, Anders; Hansen, Thomas V O

    2011-01-01

    genome containing disease-causing variants. However, IBD regions can be difficult to detect, especially in the common case where no pedigree information is available. In particular, all existing non-pedigree based methods can only infer IBD sharing between two individuals. Here, we present a new Markov...... Chain Monte Carlo method for detection of IBD regions, which does not rely on any pedigree information. It is based on a probabilistic model applicable to unphased SNP data. It can take inbreeding, allele frequencies, genotyping errors, and genomic distances into account. And most importantly, it can...

  8. In silico assessment of genetic variation in KCNA5 reveals multiple mechanisms of human atrial arrhythmogenesis

    Colman, Michael A; Ni, Haibo; Liang, Bo

    2017-01-01

    and quantify the functional impact of these KCNA5 mutations on atrial electrical activity. A multi-scale model of the human atria was updated to incorporate detailed experimental data on IKur from both wild-type and mutants. The effects of the mutations on human atrial action potential and rate dependence were...... provides new insights into understanding the mechanisms by which mutant IKur contributes to atrial arrhythmias. In addition, as IKur is an atrial-specific channel and a number of IKur-selective blockers have been developed as anti-AF agents, this study also helps to understand some contradictory results...

  9. MODELING OF NAPHTHA PYROLYSIS WITH USING GENETIC ALGORITM

    V. K. Bityukov

    2015-01-01

    Full Text Available Summary. In operation of industrial pyrolysis furnaces, the main task is the selection of the optimal mode of thermal decomposition of the feedstock, depending on the yield of the desired products under conditions of technological limitations on the process. To solve this problem for an operating reactor, this paper considers the SRT-VI Large-Capacity industrial Furnace , the mathematical model of the pyrolysis process was constructed, using a kinetic scheme which consists of primary reaction of decomposition of raw materials and secondary elementary reactions of interaction of the considered mixture components, the heat balance equation and hydrodynamics of flow in the coil. The raw material for the selected installation type is naphtha (straight-run petrol. Output parameters of the model are the molar costs of marketable hydrocarbons. The reactor is described by the equation of ideal displacement in the static mode of operation. It is assumed that all reactions have a temperature dependence that follows the Arrhenius law. The activation energies of chemical processes were estimated using the PolanyiSemenov equation and identification of pre-exponential factors was carried out using a genetic algorithm (GA. This task requires solving simultaneous system of differential equations describing the pyrolysis process and a search for a large number of unknown parameters, and therefore it is proposed to modify the GA. Optimal scheme includes Gray encoding arithmetic operators, tournament selection, with tournament ranking more than 4, crossover with partial random choice of alleys, mutations with a high probability of occurring and elitism with competitive global competition. Using the proposed approach, the parametric identification of model process is accomplished. The analysis of the simulation results with the data of operating reactor showed its suitability for use in order to control the pyrolysis process.

  10. Evolutionary Genetic Analysis Uncovers Multiple Species with Distinct Habitat Preferences and Antibiotic Resistance Phenotypes in the Stenotrophomonas maltophilia Complex

    Luz E. Ochoa-Sánchez

    2017-08-01

    Full Text Available The genus Stenotrophomonas (Gammaproteobacteria has a broad environmental distribution. Stenotrophomonas maltophilia is its best known species because it is a globally emerging, multidrug-resistant (MDR, opportunistic pathogen. Members of this species are known to display high genetic, ecological and phenotypic diversity, forming the so-called S. maltophilia complex (Smc. Heterogeneous resistance and virulence phenotypes have been reported for environmental Smc isolates of diverse ecological origin. We hypothesized that this heterogeneity could be in part due to the potential lumping of several cryptic species in the Smc. Here we used state-of-the-art phylogenetic and population genetics methods to test this hypothesis based on the multilocus dataset available for the genus at pubmlst.org. It was extended with sequences from complete and draft genome sequences to assemble a comprehensive set of reference sequences. This framework was used to analyze 108 environmental isolates obtained in this study from the sediment and water column of four rivers and streams in Central Mexico, affected by contrasting levels of anthropogenic pollution. The aim of the study was to identify species in this collection, defined as genetically cohesive sequence clusters, and to determine the extent of their genetic, ecological and phenotypic differentiation. The multispecies coalescent, coupled with Bayes factor analysis was used to delimit species borders, together with population genetic structure analyses, recombination and gene flow estimates between sequence clusters. These analyses consistently revealed that the Smc contains at least 5 significantly differentiated lineages: S. maltophilia and Smc1 to Smc4. Only S. maltophilia was found to be intrinsically MDR, all its members expressing metallo-β-lactamases (MBLs. The other Smc lineages were not MDR and did not express MBLs. We also obtained isolates related to S. acidaminiphila, S. humi and S. terrae. They

  11. Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

    Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

    2017-08-01

    Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.

  12. Modeling of genetic algorithms with a finite population

    C.H.M. van Kemenade

    1997-01-01

    textabstractCross-competition between non-overlapping building blocks can strongly influence the performance of evolutionary algorithms. The choice of the selection scheme can have a strong influence on the performance of a genetic algorithm. This paper describes a number of different genetic

  13. Modelling Autistic Features in Mice Using Quantitative Genetic Approaches

    Molenhuis, Remco T; Bruining, Hilgo; Kas, Martien J

    2017-01-01

    Animal studies provide a unique opportunity to study the consequences of genetic variants at the behavioural level. Human studies have identified hundreds of risk genes for autism spectrum disorder (ASD) that can lead to understanding on how genetic variation contributes to individual differences in

  14. A Realistic Model under which the Genetic Code is Optimal

    Buhrman, H.; van der Gulik, P.T.S.; Klau, G.W.; Schaffner, C.; Speijer, D.; Stougie, L.

    2013-01-01

    The genetic code has a high level of error robustness. Using values of hydrophobicity scales as a proxy for amino acid character, and the mean square measure as a function quantifying error robustness, a value can be obtained for a genetic code which reflects the error robustness of that code. By

  15. Numerical modelling of multiple scattering between two elastical particles

    Bjørnø, Irina; Jensen, Leif Bjørnø

    1998-01-01

    in suspension have been studied extensively since Foldy's formulation of his theory for isotropic scattering by randomly distributed scatterers. However, a number of important problems related to multiple scattering are still far from finding their solutions. A particular, but still unsolved, problem......Multiple acoustical signal interactions with sediment particles in the vicinity of the seabed may significantly change the course of sediment concentration profiles determined by inversion from acoustical backscattering measurements. The scattering properties of high concentrations of sediments...... is the question of proximity thresholds for influence of multiple scattering in terms of particle properties like volume fraction, average distance between particles or other related parameters. A few available experimental data indicate a significance of multiple scattering in suspensions where the concentration...

  16. 231 Using Multiple Regression Analysis in Modelling the Role of ...

    User

    of Internal Revenue, Tourism Bureau and hotel records. The multiple regression .... additional guest facilities such as restaurant, a swimming pool or child care and social function ... and provide good quality service to the public. Conclusion.

  17. Modeling a Single SEP Event from Multiple Vantage Points Using the iPATH Model

    Hu, Junxiang; Li, Gang; Fu, Shuai; Zank, Gary; Ao, Xianzhi

    2018-02-01

    Using the recently extended 2D improved Particle Acceleration and Transport in the Heliosphere (iPATH) model, we model an example gradual solar energetic particle event as observed at multiple locations. Protons and ions that are energized via the diffusive shock acceleration mechanism are followed at a 2D coronal mass ejection-driven shock where the shock geometry varies across the shock front. The subsequent transport of energetic particles, including cross-field diffusion, is modeled by a Monte Carlo code that is based on a stochastic differential equation method. Time intensity profiles and particle spectra at multiple locations and different radial distances, separated in longitudes, are presented. The results shown here are relevant to the upcoming Parker Solar Probe mission.

  18. Species delimitation in lemurs: multiple genetic loci reveal low levels of species diversity in the genus Cheirogaleus

    Rasoloarison Rodin M

    2009-02-01

    Full Text Available Abstract Background Species are viewed as the fundamental unit in most subdisciplines of biology. To conservationists this unit represents the currency for global biodiversity assessments. Even though Madagascar belongs to one of the top eight biodiversity hotspots of the world, the taxonomy of its charismatic lemuriform primates is not stable. Within the last 25 years, the number of described lemur species has more than doubled, with many newly described species identified among the nocturnal and small-bodied cheirogaleids. Here, we characterize the diversity of the dwarf lemurs (genus Cheirogaleus and assess the status of the seven described species, based on phylogenetic and population genetic analysis of mtDNA (cytb + cox2 and three nuclear markers (adora3, fiba and vWF. Results This study identified three distinct evolutionary lineages within the genus Cheirogaleus. Population genetic cluster analyses revealed a further layer of population divergence with six distinct genotypic clusters. Conclusion Based on the general metapopulation lineage concept and multiple concordant data sets, we identify three exclusive groups of dwarf lemur populations that correspond to three of the seven named species: C. major, C. medius and C. crossleyi. These three species were found to be genealogically exclusive in both mtDNA and nDNA loci and are morphologically distinguishable. The molecular and morphometric data indicate that C. adipicaudatus and C. ravus are synonymous with C. medius and C. major, respectively. Cheirogaleus sibreei falls into the C. medius mtDNA clade, but in morphological analyses the membership is not clearly resolved. We do not have sufficient data to assess the status of C. minusculus. Although additional patterns of population differentiation are evident, there are no clear subdivisions that would warrant additional specific status. We propose that ecological and more geographic data should be collected to confirm these results.

  19. Predictive value of testing for multiple genetic variants in multifactorial diseases: implications for the discourse on ethical, legal and social issues

    A. Cecile J.W. Janssens

    2006-12-01

    Full Text Available Multifactorial diseases such as type 2 diabetes, osteoporosis, and cardiovascular disease are caused by a complex interplay of many genetic and nongenetic factors, each of which conveys a minor increase in the risk of disease. Unraveling the genetic origins of these diseases is expected to lead to individualized medicine, in which the prevention and treatment strategies are personalized on the basis of the results of predictive genetic tests. This great optimism is counterbalanced by concerns about the ethical, legal, and social implications of genomic medicine, such as the protection of privacy and autonomy, stigmatization, discrimination, and the psychological burden of genetic testing. These concerns are translated from genetic testing in monogenic disorders, but this translation may not be appropriate. Multiple genetic testing (genomic profiling has essential differences from genetic testing in monogenic disorders. The differences lie in the lower predictive value of the test results, the pleiotropic effects of susceptibility genes, and the low inheritance of genomic profiles. For these reasons, genomic profiling may be more similar to nongenetic tests than to predictive tests for monogenic diseases. Therefore, ethical, legal, and social issues that apply to predictive genetic testing for monogenic diseases may not be relevant for the prediction of multifactorial disorders in genomic medicine.

  20. An Additive-Multiplicative Cox-Aalen Regression Model

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects...

  1. Use of a genetic algorithm in a subchannel model

    Alberto Teyssedou; Armando Nava-Dominguez

    2005-01-01

    Full text of publication follows: The channel of a nuclear reactor contains the fuel bundles which are made up of fuel elements distributed in a manner that creates a series of interconnected subchannels through which the coolant flows. Subchannel codes are used to determine local flow variables; these codes consider the complex geometry of a nuclear fuel bundle as being divided in simple parallel and interconnected cells called 'subchannels'. Each subchannel is bounded by the solid walls of the fuel rods or by imaginary boundaries placed between adjacent subchannels. In each subchannel the flow is considered as one dimensional, therefore lateral mixing mechanisms between subchannels should be taken into account. These mixing mechanisms are: Diversion cross-flow, Turbulent mixing, Turbulent void diffusion, Void drift and Buoyancy drift; they are implemented as independent contribution terms in a pseudo-vectorial lateral momentum equation. These mixing terms are calculated with correlations that require the use of empirical coefficients. It has been observed, however, that there is no unique set of coefficients and or correlations that can be used to predict a complete range of experimental conditions. To avoid this drawback, in this paper a Genetic Algorithm (GA) was coupled to a subchannel model. The use of a GA in conjunction with an appropriate objective function allows the subchannel model to internally determine the optimal values of the coefficients without user intervention. The subchannel model requires two diffusion coefficients, the drift flux two-phase flow distribution coefficient, C 0 , and a coefficient used to control the lateral pressure losses. The GA algorithm was implemented in order to find the most appropriate values of these four coefficients. Genetic algorithms (GA) are based on the theory of evolution; thus, the GA manipulates a population of individuals (chromosomes) in order to evolve them towards a best adaptation (fitness criterion) to

  2. Estimation and interpretation of genetic effects with epistasis using the NOIA model.

    Alvarez-Castro, José M; Carlborg, Orjan; Rönnegård, Lars

    2012-01-01

    We introduce this communication with a brief outline of the historical landmarks in genetic modeling, especially concerning epistasis. Then, we present methods for the use of genetic modeling in QTL analyses. In particular, we summarize the essential expressions of the natural and orthogonal interactions (NOIA) model of genetic effects. Our motivation for reviewing that theory here is twofold. First, this review presents a digest of the expressions for the application of the NOIA model, which are often mixed with intermediate and additional formulae in the original articles. Second, we make the required theory handy for the reader to relate the genetic concepts to the particular mathematical expressions underlying them. We illustrate those relations by providing graphical interpretations and a diagram summarizing the key features for applying genetic modeling with epistasis in comprehensive QTL analyses. Finally, we briefly review some examples of the application of NOIA to real data and the way it improves the interpretability of the results.

  3. Development of Genetic Occurrence Models for Geothermal Prospecting

    Walker, J. D.; Sabin, A.; Unruh, J.; Monastero, F. C.; Combs, J.

    2007-12-01

    , including high heat flow, anomalous temperature water wells, high-temperature indications from aqueous geothermometry and geochemistry, Pliocene or younger ages from low-temperature thermochronometers, as well as more obvious factors such as geysers and fumaroles (which by definition will be missing for blind resources). Our occurrence-model strategy inverts the current approach that relies first on obvious evidence of geothermal activity. We evaluated our approach by retrospectively applying the protocol to the characteristics of producing geothermal fields, and in all cases, known resource areas fit the parameters identified from a genetic perspective.

  4. Development and amplification of multiple co-dominant genetic markers from single spores of arbuscular mycorrhizal fungi by nested multiplex PCR

    Holtgrewe-Stukenbrock, Eva; Rosendahl, Søren

    2005-01-01

    Multiple co-dominant genetic markers from single spores of the arbuscular mycorrhizal (AM) fungi Glomus mosseae, Glomus caledonium, and Glomus geosporum were amplified by nested multiplex PCR using a combination of primers for simultaneous amplification of five loci in one PCR. Subsequently, each...... marker was amplified separately in nested PCR using specific primers. Polymorphic loci within the three putative single copy genes GmFOX2, GmTOR2, and GmGIN1 were characterized by sequencing and single strand conformation polymorphisms (SSCP). Primers specific for the LSU rDNA D2 region were included...... are homokaryotic. All isolates of G. mosseae had unique genotypes. The amplification of multiple co-dominant genetic markers from single spores by the nested multiplex PCR approach provides an important tool for future studies of AM fungi population genetics and evolution....

  5. Experimental Autoimmune Encephalomyelitis (EAE) as Animal Models of Multiple Sclerosis (MS).

    Glatigny, Simon; Bettelli, Estelle

    2018-01-08

    Multiple sclerosis (MS) is a multifocal demyelinating disease of the central nervous system (CNS) leading to the progressive destruction of the myelin sheath surrounding axons. It can present with variable clinical and pathological manifestations, which might reflect the involvement of distinct pathogenic processes. Although the mechanisms leading to the development of the disease are not fully understood, numerous evidences indicate that MS is an autoimmune disease, the initiation and progression of which are dependent on an autoimmune response against myelin antigens. In addition, genetic susceptibility and environmental triggers likely contribute to the initiation of the disease. At this time, there is no cure for MS, but several disease-modifying therapies (DMTs) are available to control and slow down disease progression. A good number of these DMTs were identified and tested using animal models of MS referred to as experimental autoimmune encephalomyelitis (EAE). In this review, we will recapitulate the characteristics of EAE models and discuss how they help shed light on MS pathogenesis and help test new treatments for MS patients. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

  6. Quantitative genetics of Taura syndrome resistance in Pacific (Penaeus vannamei): A cure model approach

    Ødegård, Jørgen; Gitterle, Thomas; Madsen, Per

    2011-01-01

    cure survival model using Gibbs sampling, treating susceptibility and endurance as separate genetic traits. Results: Overall mortality at the end of test was 28%, while 38% of the population was considered susceptible to the disease. The estimated underlying heritability was high for susceptibility (0....... However, genetic evaluation of susceptibility based on the cure model showed clear associations with standard genetic evaluations that ignore the cure fraction for these data. Using the current testing design, genetic variation in observed survival time and absolute survival at the end of test were most...

  7. Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm

    Hao, Yufang; Xie, Shaodong

    2018-03-01

    Air quality monitoring networks play a significant role in identifying the spatiotemporal patterns of air pollution, and they need to be deployed efficiently, with a minimum number of sites. The revision and optimal adjustment of existing monitoring networks is crucial for cities that have undergone rapid urban expansion and experience temporal variations in pollution patterns. The approach based on the Weather Research and Forecasting-California PUFF (WRF-CALPUFF) model and genetic algorithm (GA) was developed to design an optimal monitoring network. The maximization of coverage with minimum overlap and the ability to detect violations of standards were developed as the design objectives for redistributed networks. The non-dominated sorting genetic algorithm was applied to optimize the network size and site locations simultaneously for Shijiazhuang city, one of the most polluted cities in China. The assessment on the current network identified the insufficient spatial coverage of SO2 and NO2 monitoring for the expanding city. The optimization results showed that significant improvements were achieved in multiple objectives by redistributing the original network. Efficient coverage of the resulting designs improved to 60.99% and 76.06% of the urban area for SO2 and NO2, respectively. The redistributing design for multi-pollutant including 8 sites was also proposed, with the spatial representation covered 52.30% of the urban area and the overlapped areas decreased by 85.87% compared with the original network. The abilities to detect violations of standards were not improved as much as the other two objectives due to the conflicting nature between the multiple objectives. Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect. Overall, our study presents an effective and feasible procedure for air quality network optimization at a city scale.

  8. [The discussion of the infiltrative model of mathematical knowledge to genetics teaching].

    Liu, Jun; Luo, Pei-Gao

    2011-11-01

    Genetics, the core course of biological field, is an importance major-basic course in curriculum of many majors related with biology. Due to strong theoretical and practical as well as abstract of genetics, it is too difficult to study on genetics for many students. At the same time, mathematics is one of the basic courses in curriculum of the major related natural science, which has close relationship with the establishment, development and modification of genetics. In this paper, to establish the intrinsic logistic relationship and construct the integral knowledge network and to help students improving the analytic, comprehensive and logistic abilities, we applied some mathematical infiltrative model genetic knowledge in genetics teaching, which could help students more deeply learn and understand genetic knowledge.

  9. Tools and Models for Integrating Multiple Cellular Networks

    Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.

    2015-11-06

    In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

  10. Lyssavirus infection: 'low dose, multiple exposure' in the mouse model.

    Banyard, Ashley C; Healy, Derek M; Brookes, Sharon M; Voller, Katja; Hicks, Daniel J; Núñez, Alejandro; Fooks, Anthony R

    2014-03-06

    The European bat lyssaviruses (EBLV-1 and EBLV-2) are zoonotic pathogens present within bat populations across Europe. The maintenance and transmission of lyssaviruses within bat colonies is poorly understood. Cases of repeated isolation of lyssaviruses from bat roosts have raised questions regarding the maintenance and intraspecies transmissibility of these viruses within colonies. Furthermore, the significance of seropositive bats in colonies remains unclear. Due to the protected nature of European bat species, and hence restrictions to working with the natural host for lyssaviruses, this study analysed the outcome following repeat inoculation of low doses of lyssaviruses in a murine model. A standardized dose of virus, EBLV-1, EBLV-2 or a 'street strain' of rabies (RABV), was administered via a peripheral route to attempt to mimic what is hypothesized as natural infection. Each mouse (n=10/virus/group/dilution) received four inoculations, two doses in each footpad over a period of four months, alternating footpad with each inoculation. Mice were tail bled between inoculations to evaluate antibody responses to infection. Mice succumbed to infection after each inoculation with 26.6% of mice developing clinical disease following the initial exposure across all dilutions (RABV, 32.5% (n=13/40); EBLV-1, 35% (n=13/40); EBLV-2, 12.5% (n=5/40)). Interestingly, the lowest dose caused clinical disease in some mice upon first exposure ((RABV, 20% (n=2/10) after first inoculation; RABV, 12.5% (n=1/8) after second inoculation; EBLV-2, 10% (n=1/10) after primary inoculation). Furthermore, five mice developed clinical disease following the second exposure to live virus (RABV, n=1; EBLV-1, n=1; EBLV-2, n=3) although histopathological examination indicated that the primary inoculation was the most probably cause of death due to levels of inflammation and virus antigen distribution observed. All the remaining mice (RABV, n=26; EBLV-1, n=26; EBLV-2, n=29) survived the tertiary and

  11. Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

    Zhang, Shou-ping; Xin, Xiao-kang

    2017-07-01

    Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

  12. Rapid installation of numerical models in multiple parent codes

    Brannon, R.M.; Wong, M.K.

    1996-10-01

    A set of``model interface guidelines``, called MIG, is offered as a means to more rapidly install numerical models (such as stress-strain laws) into any parent code (hydrocode, finite element code, etc.) without having to modify the model subroutines. The model developer (who creates the model package in compliance with the guidelines) specifies the model`s input and storage requirements in a standardized way. For portability, database management (such as saving user inputs and field variables) is handled by the parent code. To date, NUG has proved viable in beta installations of several diverse models in vectorized and parallel codes written in different computer languages. A NUG-compliant model can be installed in different codes without modifying the model`s subroutines. By maintaining one model for many codes, MIG facilitates code-to-code comparisons and reduces duplication of effort potentially reducing the cost of installing and sharing models.

  13. Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

    Schmidlen, Tara; Sturm, Amy C; Hovick, Shelly; Scheinfeldt, Laura; Scott Roberts, J; Morr, Lindsey; McElroy, Joseph; Toland, Amanda E; Christman, Michael; O'Daniel, Julianne M; Gordon, Erynn S; Bernhardt, Barbara A; Ormond, Kelly E; Sweet, Kevin

    2018-02-19

    With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

  14. Hierarchical linear modeling of longitudinal pedigree data for genetic association analysis

    Tan, Qihua; B Hjelmborg, Jacob V; Thomassen, Mads

    2014-01-01

    -effect models to explicitly model the genetic relationship. These have proved to be an efficient way of dealing with sample clustering in pedigree data. Although current algorithms implemented in popular statistical packages are useful for adjusting relatedness in the mixed modeling of genetic effects...... associated with blood pressure with estimated inflation factors of 0.99, suggesting that our modeling of random effects efficiently handles the genetic relatedness in pedigrees. Application to simulated data captures important variants specified in the simulation. Our results show that the method is useful......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees, which could affect statistical assessment of the genetic effects. Approaches have been proposed to integrate kinship correlation into the mixed...

  15. Correlation of Klebsiella pneumoniae comparative genetic analyses with virulence profiles in a murine respiratory disease model.

    Ramy A Fodah

    Full Text Available Klebsiella pneumoniae is a bacterial pathogen of worldwide importance and a significant contributor to multiple disease presentations associated with both nosocomial and community acquired disease. ATCC 43816 is a well-studied K. pneumoniae strain which is capable of causing an acute respiratory disease in surrogate animal models. In this study, we performed sequencing of the ATCC 43816 genome to support future efforts characterizing genetic elements required for disease. Furthermore, we performed comparative genetic analyses to the previously sequenced genomes from NTUH-K2044 and MGH 78578 to gain an understanding of the conservation of known virulence determinants amongst the three strains. We found that ATCC 43816 and NTUH-K2044 both possess the known virulence determinant for yersiniabactin, as well as a Type 4 secretion system (T4SS, CRISPR system, and an acetonin catabolism locus, all absent from MGH 78578. While both NTUH-K2044 and MGH 78578 are clinical isolates, little is known about the disease potential of these strains in cell culture and animal models. Thus, we also performed functional analyses in the murine macrophage cell lines RAW264.7 and J774A.1 and found that MGH 78578 (K52 serotype was internalized at higher levels than ATCC 43816 (K2 and NTUH-K2044 (K1, consistent with previous characterization of the antiphagocytic properties of K1 and K2 serotype capsules. We also examined the three K. pneumoniae strains in a novel BALB/c respiratory disease model and found that ATCC 43816 and NTUH-K2044 are highly virulent (LD50<100 CFU while MGH 78578 is relatively avirulent.

  16. Developing a Model of Advanced Training to Promote Career Advancement for Certified Genetic Counselors: An Investigation of Expanded Skills, Advanced Training Paths, and Professional Opportunities.

    Baty, Bonnie J; Trepanier, Angela; Bennett, Robin L; Davis, Claire; Erby, Lori; Hippman, Catriona; Lerner, Barbara; Matthews, Anne; Myers, Melanie F; Robbins, Carol B; Singletary, Claire N

    2016-08-01

    There are currently multiple paths through which genetic counselors can acquire advanced knowledge and skills. However, outside of continuing education opportunities, there are few formal training programs designed specifically for the advanced training of genetic counselors. In the genetic counseling profession, there is currently considerable debate about the paths that should be available to attain advanced skills, as well as the skills that might be needed for practice in the future. The Association of Genetic Counseling Program Directors (AGCPD) convened a national committee, the Committee on Advanced Training for Certified Genetic Counselors (CATCGC), to investigate varied paths to post-master's training and career development. The committee began its work by developing three related grids that view career advancement from the viewpoints of the skills needed to advance (skills), ways to obtain these skills (paths), and existing genetic counselor positions that offer career change or advancement (positions). Here we describe previous work related to genetic counselor career advancement, the charge of the CATCGC, our preliminary work in developing a model through which to view genetic counselor advanced training and career advancement opportunities, and our next steps in further developing and disseminating the model.

  17. Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

    Valor, A.; Caleyo, F.; Alfonso, L.; Rivas, D.; Hallen, J.M.

    2007-01-01

    In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion

  18. Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

    Valor, A. [Facultad de Fisica, Universidad de La Habana, San Lazaro y L, Vedado, 10400 Havana (Cuba); Caleyo, F. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico)]. E-mail: fcaleyo@gmail.com; Alfonso, L. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico); Rivas, D. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico); Hallen, J.M. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico)

    2007-02-15

    In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.

  19. A review of animal models used to evaluate potential allergenicity of genetically modified organisms (GMOs)

    Marsteller, Nathan; Bøgh, Katrine Lindholm; Goodman, Richard E.

    2017-01-01

    Food safety regulators request prediction of allergenicity for newly expressed proteins in genetically modified (GM) crops and in novel foods. Some have suggested using animal models to assess potential allergenicity. A variety of animal models have been used in research to evaluate sensitisation...... of genetically modified organisms (GMOs).......Food safety regulators request prediction of allergenicity for newly expressed proteins in genetically modified (GM) crops and in novel foods. Some have suggested using animal models to assess potential allergenicity. A variety of animal models have been used in research to evaluate sensitisation...

  20. Genetic and genomic analysis of RNases in model cyanobacteria.

    Cameron, Jeffrey C; Gordon, Gina C; Pfleger, Brian F

    2015-10-01

    Cyanobacteria are diverse photosynthetic microbes with the ability to convert CO2 into useful products. However, metabolic engineering of cyanobacteria remains challenging because of the limited resources for modifying the expression of endogenous and exogenous biochemical pathways. Fine-tuned control of protein production will be critical to optimize the biological conversion of CO2 into desirable molecules. Messenger RNAs (mRNAs) are labile intermediates that play critical roles in determining the translation rate and steady-state protein concentrations in the cell. The majority of studies on mRNA turnover have focused on the model heterotrophic bacteria Escherichia coli and Bacillus subtilis. These studies have elucidated many RNA modifying and processing enzymes and have highlighted the differences between these Gram-negative and Gram-positive bacteria, respectively. In contrast, much less is known about mRNA turnover in cyanobacteria. We generated a compendium of the major ribonucleases (RNases) and provide an in-depth analysis of RNase III-like enzymes in commonly studied and diverse cyanobacteria. Furthermore, using targeted gene deletion, we genetically dissected the RNases in Synechococcus sp. PCC 7002, one of the fastest growing and industrially attractive cyanobacterial strains. We found that all three cyanobacterial homologs of RNase III and a member of the RNase II/R family are not essential under standard laboratory conditions, while homologs of RNase E/G, RNase J1/J2, PNPase, and a different member of the RNase II/R family appear to be essential for growth. This work will enhance our understanding of native control of gene expression and will facilitate the development of an RNA-based toolkit for metabolic engineering in cyanobacteria.

  1. Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

    Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

    2010-01-01

    Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

  2. A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.

    Gompert, Zachariah

    2016-01-01

    Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur

  3. A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.

    Zachariah Gompert

    Full Text Available Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20 SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure, particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among

  4. Different concepts and models of information for family-relevant genetic findings: comparison and ethical analysis.

    Lenk, Christian; Frommeld, Debora

    2015-08-01

    Genetic predispositions often concern not only individual persons, but also other family members. Advances in the development of genetic tests lead to a growing number of genetic diagnoses in medical practice and to an increasing importance of genetic counseling. In the present article, a number of ethical foundations and preconditions for this issue are discussed. Four different models for the handling of genetic information are presented and analyzed including a discussion of practical implications. The different models' ranges of content reach from a strictly autonomous position over self-governed arrangements in the practice of genetic counseling up to the involvement of official bodies and committees. The different models show a number of elements which seem to be very useful for the handling of genetic data in families from an ethical perspective. In contrast, the limitations of the standard medical attempt regarding confidentiality and personal autonomy in the context of genetic information in the family are described. Finally, recommendations for further ethical research and the development of genetic counseling in families are given.

  5. An Additive-Multiplicative Restricted Mean Residual Life Model

    Mansourvar, Zahra; Martinussen, Torben; Scheike, Thomas H.

    2016-01-01

    mean residual life model to study the association between the restricted mean residual life function and potential regression covariates in the presence of right censoring. This model extends the proportional mean residual life model using an additive model as its covariate dependent baseline....... For the suggested model, some covariate effects are allowed to be time-varying. To estimate the model parameters, martingale estimating equations are developed, and the large sample properties of the resulting estimators are established. In addition, to assess the adequacy of the model, we investigate a goodness...

  6. Extending positive CLASS results across multiple instructors and multiple classes of Modeling Instruction

    Brewe, Eric; Traxler, Adrienne; de la Garza, Jorge; Kramer, Laird H.

    2013-12-01

    We report on a multiyear study of student attitudes measured with the Colorado Learning Attitudes about Science Survey in calculus-based introductory physics taught with the Modeling Instruction curriculum. We find that five of six instructors and eight of nine sections using Modeling Instruction showed significantly improved attitudes from pre- to postcourse. Cohen’s d effect sizes range from 0.08 to 0.95 for individual instructors. The average effect was d=0.45, with a 95% confidence interval of (0.26-0.64). These results build on previously published results showing positive shifts in attitudes from Modeling Instruction classes. We interpret these data in light of other published positive attitudinal shifts and explore mechanistic explanations for similarities and differences with other published positive shifts.

  7. Extending positive CLASS results across multiple instructors and multiple classes of Modeling Instruction

    Eric Brewe

    2013-10-01

    Full Text Available We report on a multiyear study of student attitudes measured with the Colorado Learning Attitudes about Science Survey in calculus-based introductory physics taught with the Modeling Instruction curriculum. We find that five of six instructors and eight of nine sections using Modeling Instruction showed significantly improved attitudes from pre- to postcourse. Cohen’s d effect sizes range from 0.08 to 0.95 for individual instructors. The average effect was d=0.45, with a 95% confidence interval of (0.26–0.64. These results build on previously published results showing positive shifts in attitudes from Modeling Instruction classes. We interpret these data in light of other published positive attitudinal shifts and explore mechanistic explanations for similarities and differences with other published positive shifts.

  8. Interstitial integrals in the multiple-scattering model

    Swanson, J.R.; Dill, D.

    1982-01-01

    We present an efficient method for the evaluation of integrals involving multiple-scattering wave functions over the interstitial region. Transformation of the multicenter interstitial wave functions to a single center representation followed by a geometric projection reduces the integrals to products of analytic angular integrals and numerical radial integrals. The projection function, which has the value 1 in the interstitial region and 0 elsewhere, has a closed-form partial-wave expansion. The method is tested by comparing its results with exact normalization and dipole integrals; the differences are 2% at worst and typically less than 1%. By providing an efficient means of calculating Coulomb integrals, the method allows treatment of electron correlations using a multiple scattering basis set

  9. Two-level mixed modeling of longitudinal pedigree data for genetic association analysis

    Tan, Q.

    2013-01-01

    of follow-up. Approaches have been proposed to integrate kinship correlation into the mixed effect models to explicitly model the genetic relationship which have been proven as an efficient way for dealing with sample clustering in pedigree data. Although useful for adjusting relatedness in the mixed...... assess the genetic associations with the mean level and the rate of change in a phenotype both with kinship correlation integrated in the mixed effect models. We apply our method to longitudinal pedigree data to estimate the genetic effects on systolic blood pressure measured over time in large pedigrees......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees which could affect statistical assessment of the genetic effects on both the mean level of the phenotype and its rate of change over the time...

  10. Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks

    Amanifard, N.; Nariman-Zadeh, N.; Farahani, M.H.; Khalkhali, A.

    2008-01-01

    Over the past 15 years there have been several research efforts to capture the stall inception nature in axial flow compressors. However previous analytical models could not explain the formation of short-length-scale stall cells. This paper provides a new model based on evolved GMDH neural network for transient evolution of multiple short-length-scale stall cells in an axial compressor. Genetic Algorithms (GAs) are also employed for optimal design of connectivity configuration of such GMDH-type neural networks. In this way, low-pass filter (LPF) pressure trace near the rotor leading edge is modelled with respect to the variation of pressure coefficient, flow rate coefficient, and number of rotor rotations which are defined as inputs

  11. A new spatial multiple discrete-continuous modeling approach to land use change analysis.

    2013-09-01

    This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

  12. Steam consumption minimization model in a multiple evaporation effect in a sugar plant

    Villada, Fernando; Valencia, Jaime A; Moreno, German; Murillo, J. Joaquin

    1992-01-01

    In this work, a mathematical model to minimize the steam consumption in a multiple effect evaporation system is shown. The model is based in the dynamic programming technique and the results are tested in a Colombian sugar mill

  13. Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

    José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

    2011-07-01

    Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

  14. New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

    Dong, Yiqiu; Zeng, Tieyong

    2013-01-01

    A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

  15. Applications of Systems Genetics and Biology for Obesity Using Pig Models

    Kogelman, Lisette; Kadarmideen, Haja N.

    2016-01-01

    approach, a branch of systems biology. In this chapter, we will describe the state of the art of genetic studies on human obesity, using pig populations. We will describe the features of using the pig as a model for human obesity and briefly discuss the genetics of obesity, and we will focus on systems...

  16. Pursuing the method of multiple working hypotheses for hydrological modeling

    Clark, M.P.; Kavetski, D.; Fenicia, F.

    2011-01-01

    Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding

  17. Identification of Treatment Targets in a Genetic Mouse Model of Voluntary Methamphetamine Drinking.

    Phillips, T J; Mootz, J R K; Reed, C

    2016-01-01

    Methamphetamine has powerful stimulant and euphoric effects that are experienced as rewarding and encourage use. Methamphetamine addiction is associated with debilitating illnesses, destroyed relationships, child neglect, violence, and crime; but after many years of research, broadly effective medications have not been identified. Individual differences that may impact not only risk for developing a methamphetamine use disorder but also affect treatment response have not been fully considered. Human studies have identified candidate genes that may be relevant, but lack of control over drug history, the common use or coabuse of multiple addictive drugs, and restrictions on the types of data that can be collected in humans are barriers to progress. To overcome some of these issues, a genetic animal model comprised of lines of mice selectively bred for high and low voluntary methamphetamine intake was developed to identify risk and protective alleles for methamphetamine consumption, and identify therapeutic targets. The mu opioid receptor gene was supported as a target for genes within a top-ranked transcription factor network associated with level of methamphetamine intake. In addition, mice that consume high levels of methamphetamine were found to possess a nonfunctional form of the trace amine-associated receptor 1 (TAAR1). The Taar1 gene is within a mouse chromosome 10 quantitative trait locus for methamphetamine consumption, and TAAR1 function determines sensitivity to aversive effects of methamphetamine that may curb intake. The genes, gene interaction partners, and protein products identified in this genetic mouse model represent treatment target candidates for methamphetamine addiction. © 2016 Elsevier Inc. All rights reserved.

  18. Multiple Models of Reality and How to Use Them

    Jamroga, W.J.; Blockeel, H.; Denecker, M.

    2002-01-01

    A virtual agent may obviously benefit from having an up-to-date model of her environment of activity. The model may include actual users' profiles, a dynamic environment characteristic or some assumptions being accepted by default. However, the agent doesn't have to stick to one model only, she can

  19. Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

    Tufto, Jarle

    2015-08-01

    Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  20. A Review of the Modelling of Thermally Interacting Multiple Boreholes

    Seama Koohi-Fayegh

    2013-06-01

    Full Text Available Much attention is now focused on utilizing ground heat pumps for heating and cooling buildings, as well as water heating, refrigeration and other thermal tasks. Modeling such systems is important for understanding, designing and optimizing their performance and characteristics. Several heat transfer models exist for ground heat exchangers. In this review article, challenges of modelling heat transfer in vertical heat exchangers are described, some analytical and numerical models are reviewed and compared, recent related developments are described and the importance of modelling these systems is discussed from a variety of aspects, such as sustainability of geothermal systems or their potential impacts on the ecosystems nearby.