Science.gov

Sample records for additive genetic model

  1. Functional Generalized Additive Models.

    PubMed

    McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David

    2014-01-01

    We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online.

  2. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

    PubMed Central

    Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

    2012-01-01

    Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

  3. Mixed additive models

    NASA Astrophysics Data System (ADS)

    Carvalho, Francisco; Covas, Ricardo

    2016-06-01

    We consider mixed models y =∑i =0 w Xiβi with V (y )=∑i =1 w θiMi Where Mi=XiXi⊤ , i = 1, . . ., w, and µ = X0β0. For these we will estimate the variance components θ1, . . ., θw, aswell estimable vectors through the decomposition of the initial model into sub-models y(h), h ∈ Γ, with V (y (h ))=γ (h )Ig (h )h ∈Γ . Moreover we will consider L extensions of these models, i.e., y˚=Ly+ɛ, where L=D (1n1, . . ., 1nw) and ɛ, independent of y, has null mean vector and variance covariance matrix θw+1Iw, where w =∑i =1 n wi .

  4. Additive-dominance genetic model analyses for late-maturity alpha-amylase activity in a bread wheat factorial crossing population.

    PubMed

    Rasul, Golam; Glover, Karl D; Krishnan, Padmanaban G; Wu, Jixiang; Berzonsky, William A; Ibrahim, Amir M H

    2015-12-01

    Elevated level of late maturity α-amylase activity (LMAA) can result in low falling number scores, reduced grain quality, and downgrade of wheat (Triticum aestivum L.) class. A mating population was developed by crossing parents with different levels of LMAA. The F2 and F3 hybrids and their parents were evaluated for LMAA, and data were analyzed using the R software package 'qgtools' integrated with an additive-dominance genetic model and a mixed linear model approach. Simulated results showed high testing powers for additive and additive × environment variances, and comparatively low powers for dominance and dominance × environment variances. All variance components and their proportions to the phenotypic variance for the parents and hybrids were significant except for the dominance × environment variance. The estimated narrow-sense heritability and broad-sense heritability for LMAA were 14 and 54%, respectively. High significant negative additive effects for parents suggest that spring wheat cultivars 'Lancer' and 'Chester' can serve as good general combiners, and that 'Kinsman' and 'Seri-82' had negative specific combining ability in some hybrids despite of their own significant positive additive effects, suggesting they can be used as parents to reduce LMAA levels. Seri-82 showed very good general combining ability effect when used as a male parent, indicating the importance of reciprocal effects. High significant negative dominance effects and high-parent heterosis for hybrids demonstrated that the specific hybrid combinations; Chester × Kinsman, 'Lerma52' × Lancer, Lerma52 × 'LoSprout' and 'Janz' × Seri-82 could be generated to produce cultivars with significantly reduced LMAA level.

  5. Non-additive and Additive Genetic Effects on Extraversion in 3314 Dutch Adolescent Twins and Their Parents

    PubMed Central

    Rebollo-Mesa, Irene; Hudziak, James J.; Willemsen, Gonneke; Boomsma, Dorret I.

    2012-01-01

    The influence of non-additive genetic influences on personality traits has been increasingly reported in adult populations. Less is known, however, with respect to younger samples. In this study, we examine additive and non-additive genetic contributions to the personality trait of extraversion in 1,689 Dutch twin pairs, 1,505 mothers and 1,637 fathers of the twins. The twins were on average 15.5 years (range 12–18 years). To increase statistical power to detect non-additive genetic influences, data on extraversion were also collected in parents and simultaneously analyzed. Genetic modeling procedures incorporating age as a potential modifier of heritability showed significant influences of additive (20–23%) and non-additive genetic factors (31–33%) in addition to unshared environment (46–48%) for adolescents and for their parents. The additive genetic component was slightly and positively related to age. No significant sex differences were found for either extraversion means or for the magnitude of the genetic and environmental influences. There was no evidence of non-random mating for extraversion in the parental generation. Results show that in addition to additive genetic influences, extraversion in adolescents is influenced by non-additive genetic factors. PMID:18240014

  6. Explaining additional genetic variation in complex traits

    PubMed Central

    Robinson, Matthew R.; Wray, Naomi R.; Visscher, Peter M.

    2015-01-01

    Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those which influence phenotype, as there are likely to be very many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping including recording of non-genetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power. PMID:24629526

  7. Unnatural reactive amino acid genetic code additions

    DOEpatents

    Deiters, Alexander; Cropp, Ashton T; Chin, Jason W; Anderson, Christopher J; Schultz, Peter G

    2013-05-21

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  8. Unnatural reactive amino acid genetic code additions

    DOEpatents

    Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.

    2014-08-26

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  9. Unnatural reactive amino acid genetic code additions

    SciTech Connect

    Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.

    2011-02-15

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  10. Unnatural reactive amino acid genetic code additions

    SciTech Connect

    Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.

    2011-08-09

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNAsyn-thetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  11. Additive and nonadditive genetic variation in avian personality traits.

    PubMed

    van Oers, K; Drent, P J; de Jong, G; van Noordwijk, A J

    2004-11-01

    Individuals of all vertebrate species differ consistently in their reactions to mildly stressful challenges. These typical reactions, described as personalities or coping strategies, have a clear genetic basis, but the structure of their inheritance in natural populations is almost unknown. We carried out a quantitative genetic analysis of two personality traits (exploration and boldness) and the combination of these two traits (early exploratory behaviour). This study was carried out on the lines resulting from a two-directional artificial selection experiment on early exploratory behaviour (EEB) of great tits (Parus major) originating from a wild population. In analyses using the original lines, reciprocal F(1) and reciprocal first backcross generations, additive, dominance, maternal effects ands sex-dependent expression of exploration, boldness and EEB were estimated. Both additive and dominant genetic effects were important determinants of phenotypic variation in exploratory behaviour and boldness. However, no sex-dependent expression was observed in either of these personality traits. These results are discussed with respect to the maintenance of genetic variation in personality traits, and the expected genetic structure of other behavioural and life history traits in general.

  12. Efficient Improvement of Silage Additives by Using Genetic Algorithms

    PubMed Central

    Davies, Zoe S.; Gilbert, Richard J.; Merry, Roger J.; Kell, Douglas B.; Theodorou, Michael K.; Griffith, Gareth W.

    2000-01-01

    The enormous variety of substances which may be added to forage in order to manipulate and improve the ensilage process presents an empirical, combinatorial optimization problem of great complexity. To investigate the utility of genetic algorithms for designing effective silage additive combinations, a series of small-scale proof of principle silage experiments were performed with fresh ryegrass. Having established that significant biochemical changes occur over an ensilage period as short as 2 days, we performed a series of experiments in which we used 50 silage additive combinations (prepared by using eight bacterial and other additives, each of which was added at six different levels, including zero [i.e., no additive]). The decrease in pH, the increase in lactate concentration, and the free amino acid concentration were measured after 2 days and used to calculate a “fitness” value that indicated the quality of the silage (compared to a control silage made without additives). This analysis also included a “cost” element to account for different total additive levels. In the initial experiment additive levels were selected randomly, but subsequently a genetic algorithm program was used to suggest new additive combinations based on the fitness values determined in the preceding experiments. The result was very efficient selection for silages in which large decreases in pH and high levels of lactate occurred along with low levels of free amino acids. During the series of five experiments, each of which comprised 50 treatments, there was a steady increase in the amount of lactate that accumulated; the best treatment combination was that used in the last experiment, which produced 4.6 times more lactate than the untreated silage. The additive combinations that were found to yield the highest fitness values in the final (fifth) experiment were assessed to determine a range of biochemical and microbiological quality parameters during full-term silage

  13. Additive and nonadditive genetic variances for milk yield, fertility, and lifetime performance traits of dairy cattle.

    PubMed

    Fuerst, C; Sölkner, J

    1994-04-01

    Additive and nonadditive genetic variances were estimated for yield traits and fertility for three subsequent lactations and for lifetime performance traits of purebred and crossbred dairy cattle populations. Traits were milk yield, energy-corrected milk yield, fat percentage, protein percentage, calving interval, length of productive life, and lifetime FCM of purebred Simmental, Simmental including crossbreds, and Braunvieh crossed with Brown Swiss. Data files ranged from 66,740 to 375,093 records. An approach based on pedigree information for sire and maternal grandsire was used and included additive, dominance, and additive by additive genetic effects. Variances were estimated using the tildehat approximation to REML. Heritability estimated without nonadditive effects in the model was overestimated, particularly in presence of additive by additive variance. Dominance variance was important for most traits; for the lifetime performance traits, dominance was clearly higher than additive variance. Additive by additive variance was very high for milk yield and energy-corrected milk yield, especially for data including crossbreds. Effect of inbreeding was low in most cases. Inclusion of nonadditive effects in genetic evaluation models might improve estimation of additive effects and may require consideration for dairy cattle breeding programs.

  14. Computational Process Modeling for Additive Manufacturing

    NASA Technical Reports Server (NTRS)

    Bagg, Stacey; Zhang, Wei

    2014-01-01

    Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

  15. Dynamic causal modeling with genetic algorithms.

    PubMed

    Pyka, M; Heider, D; Hauke, S; Kircher, T; Jansen, A

    2011-01-15

    In the last years, dynamic causal modeling has gained increased popularity in the neuroimaging community as an approach for the estimation of effective connectivity from functional magnetic resonance imaging (fMRI) data. The algorithm calls for an a priori defined model, whose parameter estimates are subsequently computed upon the given data. As the number of possible models increases exponentially with additional areas, it rapidly becomes inefficient to compute parameter estimates for all models in order to reveal the family of models with the highest posterior probability. In the present study, we developed a genetic algorithm for dynamic causal models and investigated whether this evolutionary approach can accelerate the model search. In this context, the configuration of the intrinsic, extrinsic and bilinear connection matrices represents the genetic code and Bayesian model selection serves as a fitness function. Using crossover and mutation, populations of models are created and compared with each other. The most probable ones survive the current generation and serve as a source for the next generation of models. Tests with artificially created data sets show that the genetic algorithm approximates the most plausible models faster than a random-driven brute-force search. The fitness landscape revealed by the genetic algorithm indicates that dynamic causal modeling has excellent properties for evolution-driven optimization techniques.

  16. Genetic assessment of additional endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study.

    PubMed

    Greenwood, Tiffany A; Lazzeroni, Laura C; Calkins, Monica E; Freedman, Robert; Green, Michael F; Gur, Raquel E; Gur, Ruben C; Light, Gregory A; Nuechterlein, Keith H; Olincy, Ann; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Swerdlow, Neal R; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

    2016-01-01

    The Consortium on the Genetics of Schizophrenia Family Study (COGS-1) has previously reported our efforts to characterize the genetic architecture of 12 primary endophenotypes for schizophrenia. We now report the characterization of 13 additional measures derived from the same endophenotype test paradigms in the COGS-1 families. Nine of the measures were found to discriminate between schizophrenia patients and controls, were significantly heritable (31 to 62%), and were sufficiently independent of previously assessed endophenotypes, demonstrating utility as additional endophenotypes. Genotyping via a custom array of 1536 SNPs from 94 candidate genes identified associations for CTNNA2, ERBB4, GRID1, GRID2, GRIK3, GRIK4, GRIN2B, NOS1AP, NRG1, and RELN across multiple endophenotypes. An experiment-wide p value of 0.003 suggested that the associations across all SNPs and endophenotypes collectively exceeded chance. Linkage analyses performed using a genome-wide SNP array further identified significant or suggestive linkage for six of the candidate endophenotypes, with several genes of interest located beneath the linkage peaks (e.g., CSMD1, DISC1, DLGAP2, GRIK2, GRIN3A, and SLC6A3). While the partial convergence of the association and linkage likely reflects differences in density of gene coverage provided by the distinct genotyping platforms, it is also likely an indication of the differential contribution of rare and common variants for some genes and methodological differences in detection ability. Still, many of the genes implicated by COGS through endophenotypes have been identified by independent studies of common, rare, and de novo variation in schizophrenia, all converging on a functional genetic network related to glutamatergic neurotransmission that warrants further investigation. PMID:26597662

  17. Genetic assessment of additional endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study.

    PubMed

    Greenwood, Tiffany A; Lazzeroni, Laura C; Calkins, Monica E; Freedman, Robert; Green, Michael F; Gur, Raquel E; Gur, Ruben C; Light, Gregory A; Nuechterlein, Keith H; Olincy, Ann; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Swerdlow, Neal R; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

    2016-01-01

    The Consortium on the Genetics of Schizophrenia Family Study (COGS-1) has previously reported our efforts to characterize the genetic architecture of 12 primary endophenotypes for schizophrenia. We now report the characterization of 13 additional measures derived from the same endophenotype test paradigms in the COGS-1 families. Nine of the measures were found to discriminate between schizophrenia patients and controls, were significantly heritable (31 to 62%), and were sufficiently independent of previously assessed endophenotypes, demonstrating utility as additional endophenotypes. Genotyping via a custom array of 1536 SNPs from 94 candidate genes identified associations for CTNNA2, ERBB4, GRID1, GRID2, GRIK3, GRIK4, GRIN2B, NOS1AP, NRG1, and RELN across multiple endophenotypes. An experiment-wide p value of 0.003 suggested that the associations across all SNPs and endophenotypes collectively exceeded chance. Linkage analyses performed using a genome-wide SNP array further identified significant or suggestive linkage for six of the candidate endophenotypes, with several genes of interest located beneath the linkage peaks (e.g., CSMD1, DISC1, DLGAP2, GRIK2, GRIN3A, and SLC6A3). While the partial convergence of the association and linkage likely reflects differences in density of gene coverage provided by the distinct genotyping platforms, it is also likely an indication of the differential contribution of rare and common variants for some genes and methodological differences in detection ability. Still, many of the genes implicated by COGS through endophenotypes have been identified by independent studies of common, rare, and de novo variation in schizophrenia, all converging on a functional genetic network related to glutamatergic neurotransmission that warrants further investigation.

  18. FEMALE AND MALE GENETIC EFFECTS ON OFFSPRING PATERNITY: ADDITIVE GENETIC (CO)VARIANCES IN FEMALE EXTRA-PAIR REPRODUCTION AND MALE PATERNITY SUCCESS IN SONG SPARROWS (MELOSPIZA MELODIA)

    PubMed Central

    Reid, Jane M; Arcese, Peter; Keller, Lukas F; Losdat, Sylvain

    2014-01-01

    Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra-pair reproduction and male within-pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra-pair reproduction and male liability for within-pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free-living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra-pair reproduction is facilitated by genetic covariance with male within-pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically. PMID:24724612

  19. Female and male genetic effects on offspring paternity: additive genetic (co)variances in female extra-pair reproduction and male paternity success in song sparrows (Melospiza melodia).

    PubMed

    Reid, Jane M; Arcese, Peter; Keller, Lukas F; Losdat, Sylvain

    2014-08-01

    Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra-pair reproduction and male within-pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra-pair reproduction and male liability for within-pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free-living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra-pair reproduction is facilitated by genetic covariance with male within-pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically.

  20. Additive Genetic Risk from Five Serotonin System Polymorphisms Interacts with Interpersonal Stress to Predict Depression

    PubMed Central

    Vrshek-Schallhorn, Suzanne; Stroud, Catherine B.; Mineka, Susan; Zinbarg, Richard E.; Adam, Emma K.; Redei, Eva E.; Hammen, Constance; Craske, Michelle G.

    2016-01-01

    Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (GxE). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a GxE predicting depression, we created an additive multilocus profile score from five serotonin system polymorphisms (one each in the genes HTR1A, HTR2A, HTR2C, and two in TPH2). Analyses focused on two forms of interpersonal stress as environmental risk factors. Using five years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (HR = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The GxE effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the GxE effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467

  1. Effect of multiplicative and additive noise on genetic transcriptional regulatory mechanism

    NASA Astrophysics Data System (ADS)

    Liu, Xue-Mei; Xie, Hui-Zhang; Liu, Liang-Gang; Li, Zhi-Bing

    2009-02-01

    A multiplicative noise and an additive noise are introduced in the kinetic model of Smolen-Baxter-Byrne [P. Smolen, D.A. Baxter, J.H. Byrne, Amer. J. Physiol. Cell. Physiol. 274 (1998) 531], in which the expression of gene is controlled by protein concentration of transcriptional activator. The Fokker-Planck equation is solved and the steady-state probability distribution is obtained numerically. It is found that the multiplicative noise converts the bistability to monostability that can be regarded as a noise-induced transition. The additive noise reduces the transcription efficiency. The correlation between the multiplicative noise and the additive noise works as a genetic switch and regulates the gene transcription effectively.

  2. Very low levels of direct additive genetic variance in fitness and fitness components in a red squirrel population.

    PubMed

    McFarlane, S Eryn; Gorrell, Jamieson C; Coltman, David W; Humphries, Murray M; Boutin, Stan; McAdam, Andrew G

    2014-05-01

    A trait must genetically correlate with fitness in order to evolve in response to natural selection, but theory suggests that strong directional selection should erode additive genetic variance in fitness and limit future evolutionary potential. Balancing selection has been proposed as a mechanism that could maintain genetic variance if fitness components trade off with one another and has been invoked to account for empirical observations of higher levels of additive genetic variance in fitness components than would be expected from mutation-selection balance. Here, we used a long-term study of an individually marked population of North American red squirrels (Tamiasciurus hudsonicus) to look for evidence of (1) additive genetic variance in lifetime reproductive success and (2) fitness trade-offs between fitness components, such as male and female fitness or fitness in high- and low-resource environments. "Animal model" analyses of a multigenerational pedigree revealed modest maternal effects on fitness, but very low levels of additive genetic variance in lifetime reproductive success overall as well as fitness measures within each sex and environment. It therefore appears that there are very low levels of direct genetic variance in fitness and fitness components in red squirrels to facilitate contemporary adaptation in this population.

  3. Advances on genetic rat models of epilepsy.

    PubMed

    Serikawa, Tadao; Mashimo, Tomoji; Kuramoro, Takashi; Voigt, Birger; Ohno, Yukihiro; Sasa, Masashi

    2015-01-01

    Considering the suitability of laboratory rats in epilepsy research, we and other groups have been developing genetic models of epilepsy in this species. After epileptic rats or seizure-susceptible rats were sporadically found in outbred stocks, the epileptic traits were usually genetically-fixed by selective breeding. So far, the absence seizure models GAERS and WAG/Rij, audiogenic seizure models GEPR-3 and GEPR-9, generalized tonic-clonic seizure models IER, NER and WER, and Canavan-disease related epileptic models TRM and SER have been established. Dissection of the genetic bases including causative genes in these epileptic rat models would be a significant step toward understanding epileptogenesis. N-ethyl-N-nitrosourea (ENU) mutagenesis provides a systematic approach which allowed us to develop two novel epileptic rat models: heat-induced seizure susceptible (Hiss) rats with an Scn1a missense mutation and autosomal dominant lateral temporal epilepsy (ADLTE) model rats with an Lgi1 missense mutation. In addition, we have established episodic ataxia type 1 (EA1) model rats with a Kcna1 missense mutation derived from the ENU-induced rat mutant stock, and identified a Cacna1a missense mutation in a N-Methyl-N-nitrosourea (MNU)-induced mutant rat strain GRY, resulting in the discovery of episodic ataxia type 2 (EA2) model rats. Thus, epileptic rat models have been established on the two paths: 'phenotype to gene' and 'gene to phenotype'. In the near future, development of novel epileptic rat models will be extensively promoted by the use of sophisticated genome editing technologies.

  4. Advances on genetic rat models of epilepsy

    PubMed Central

    Serikawa, Tadao; Mashimo, Tomoji; Kuramoto, Takashi; Voigt, Birger; Ohno, Yukihiro; Sasa, Masashi

    2014-01-01

    Considering the suitability of laboratory rats in epilepsy research, we and other groups have been developing genetic models of epilepsy in this species. After epileptic rats or seizure-susceptible rats were sporadically found in outbred stocks, the epileptic traits were usually genetically-fixed by selective breeding. So far, the absence seizure models GAERS and WAG/Rij, audiogenic seizure models GEPR-3 and GEPR-9, generalized tonic-clonic seizure models IER, NER and WER, and Canavan-disease related epileptic models TRM and SER have been established. Dissection of the genetic bases including causative genes in these epileptic rat models would be a significant step toward understanding epileptogenesis. N-ethyl-N-nitrosourea (ENU) mutagenesis provides a systematic approach which allowed us to develop two novel epileptic rat models: heat-induced seizure susceptible (Hiss) rats with an Scn1a missense mutation and autosomal dominant lateral temporal epilepsy (ADLTE) model rats with an Lgi1 missense mutation. In addition, we have established episodic ataxia type 1 (EA1) model rats with a Kcna1 missense mutation derived from the ENU-induced rat mutant stock, and identified a Cacna1a missense mutation in a N-Methyl-N-nitrosourea (MNU)-induced mutant rat strain GRY, resulting in the discovery of episodic ataxia type 2 (EA2) model rats. Thus, epileptic rat models have been established on the two paths: ‘phenotype to gene’ and ‘gene to phenotype’. In the near future, development of novel epileptic rat models will be extensively promoted by the use of sophisticated genome editing technologies. PMID:25312505

  5. Additive and non-additive genetic components of the jack male life history in Chinook salmon (Oncorhynchus tshawytscha).

    PubMed

    Forest, Adriana R; Semeniuk, Christina A D; Heath, Daniel D; Pitcher, Trevor E

    2016-08-01

    Chinook salmon, Oncorhynchus tshawytscha, exhibit alternative reproductive tactics (ARTs) where males exist in two phenotypes: large "hooknose" males and smaller "jacks" that reach sexual maturity after only 1 year in seawater. The mechanisms that determine "jacking rate"-the rate at which males precociously sexually mature-are known to involve both genetics and differential growth rates, where individuals that become jacks exhibit higher growth earlier in life. The additive genetic components have been studied and it is known that jack sires produce significantly more jack offspring than hooknose sires, and vice versa. The current study was the first to investigate both additive and non-additive genetic components underlying jacking through the use of a full-factorial breeding design using all hooknose sires. The effect of dams and sires descendant from a marker-assisted broodstock program that identified "high performance" and "low performance" lines using growth- and survival-related gene markers was also studied. Finally, the relative growth of jack, hooknose, and female offspring was examined. No significant dam, sire, or interaction effects were observed in this study, and the maternal, additive, and non-additive components underlying jacking were small. Differences in jacking rates in this study were determined by dam performance line, where dams that originated from the low performance line produced significantly more jacks. Jack offspring in this study had a significantly larger body size than both hooknose males and females starting 1 year post-fertilization. This study provides novel information regarding the genetic architecture underlying ARTs in Chinook salmon that could have implications for the aquaculture industry, where jacks are not favoured due to their small body size and poor flesh quality. PMID:27450674

  6. Additive and non-additive genetic components of the jack male life history in Chinook salmon (Oncorhynchus tshawytscha).

    PubMed

    Forest, Adriana R; Semeniuk, Christina A D; Heath, Daniel D; Pitcher, Trevor E

    2016-08-01

    Chinook salmon, Oncorhynchus tshawytscha, exhibit alternative reproductive tactics (ARTs) where males exist in two phenotypes: large "hooknose" males and smaller "jacks" that reach sexual maturity after only 1 year in seawater. The mechanisms that determine "jacking rate"-the rate at which males precociously sexually mature-are known to involve both genetics and differential growth rates, where individuals that become jacks exhibit higher growth earlier in life. The additive genetic components have been studied and it is known that jack sires produce significantly more jack offspring than hooknose sires, and vice versa. The current study was the first to investigate both additive and non-additive genetic components underlying jacking through the use of a full-factorial breeding design using all hooknose sires. The effect of dams and sires descendant from a marker-assisted broodstock program that identified "high performance" and "low performance" lines using growth- and survival-related gene markers was also studied. Finally, the relative growth of jack, hooknose, and female offspring was examined. No significant dam, sire, or interaction effects were observed in this study, and the maternal, additive, and non-additive components underlying jacking were small. Differences in jacking rates in this study were determined by dam performance line, where dams that originated from the low performance line produced significantly more jacks. Jack offspring in this study had a significantly larger body size than both hooknose males and females starting 1 year post-fertilization. This study provides novel information regarding the genetic architecture underlying ARTs in Chinook salmon that could have implications for the aquaculture industry, where jacks are not favoured due to their small body size and poor flesh quality.

  7. Network reconstruction using nonparametric additive ODE models.

    PubMed

    Henderson, James; Michailidis, George

    2014-01-01

    Network representations of biological systems are widespread and reconstructing unknown networks from data is a focal problem for computational biologists. For example, the series of biochemical reactions in a metabolic pathway can be represented as a network, with nodes corresponding to metabolites and edges linking reactants to products. In a different context, regulatory relationships among genes are commonly represented as directed networks with edges pointing from influential genes to their targets. Reconstructing such networks from data is a challenging problem receiving much attention in the literature. There is a particular need for approaches tailored to time-series data and not reliant on direct intervention experiments, as the former are often more readily available. In this paper, we introduce an approach to reconstructing directed networks based on dynamic systems models. Our approach generalizes commonly used ODE models based on linear or nonlinear dynamics by extending the functional class for the functions involved from parametric to nonparametric models. Concomitantly we limit the complexity by imposing an additive structure on the estimated slope functions. Thus the submodel associated with each node is a sum of univariate functions. These univariate component functions form the basis for a novel coupling metric that we define in order to quantify the strength of proposed relationships and hence rank potential edges. We show the utility of the method by reconstructing networks using simulated data from computational models for the glycolytic pathway of Lactocaccus Lactis and a gene network regulating the pluripotency of mouse embryonic stem cells. For purposes of comparison, we also assess reconstruction performance using gene networks from the DREAM challenges. We compare our method to those that similarly rely on dynamic systems models and use the results to attempt to disentangle the distinct roles of linearity, sparsity, and derivative

  8. Network Reconstruction Using Nonparametric Additive ODE Models

    PubMed Central

    Henderson, James; Michailidis, George

    2014-01-01

    Network representations of biological systems are widespread and reconstructing unknown networks from data is a focal problem for computational biologists. For example, the series of biochemical reactions in a metabolic pathway can be represented as a network, with nodes corresponding to metabolites and edges linking reactants to products. In a different context, regulatory relationships among genes are commonly represented as directed networks with edges pointing from influential genes to their targets. Reconstructing such networks from data is a challenging problem receiving much attention in the literature. There is a particular need for approaches tailored to time-series data and not reliant on direct intervention experiments, as the former are often more readily available. In this paper, we introduce an approach to reconstructing directed networks based on dynamic systems models. Our approach generalizes commonly used ODE models based on linear or nonlinear dynamics by extending the functional class for the functions involved from parametric to nonparametric models. Concomitantly we limit the complexity by imposing an additive structure on the estimated slope functions. Thus the submodel associated with each node is a sum of univariate functions. These univariate component functions form the basis for a novel coupling metric that we define in order to quantify the strength of proposed relationships and hence rank potential edges. We show the utility of the method by reconstructing networks using simulated data from computational models for the glycolytic pathway of Lactocaccus Lactis and a gene network regulating the pluripotency of mouse embryonic stem cells. For purposes of comparison, we also assess reconstruction performance using gene networks from the DREAM challenges. We compare our method to those that similarly rely on dynamic systems models and use the results to attempt to disentangle the distinct roles of linearity, sparsity, and derivative

  9. Computational Process Modeling for Additive Manufacturing (OSU)

    NASA Technical Reports Server (NTRS)

    Bagg, Stacey; Zhang, Wei

    2015-01-01

    Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

  10. CREATION OF THE MODEL ADDITIONAL PROTOCOL

    SciTech Connect

    Houck, F.; Rosenthal, M.; Wulf, N.

    2010-05-25

    In 1991, the international nuclear nonproliferation community was dismayed to discover that the implementation of safeguards by the International Atomic Energy Agency (IAEA) under its NPT INFCIRC/153 safeguards agreement with Iraq had failed to detect Iraq's nuclear weapon program. It was now clear that ensuring that states were fulfilling their obligations under the NPT would require not just detecting diversion but also the ability to detect undeclared materials and activities. To achieve this, the IAEA initiated what would turn out to be a five-year effort to reappraise the NPT safeguards system. The effort engaged the IAEA and its Member States and led to agreement in 1997 on a new safeguards agreement, the Model Protocol Additional to the Agreement(s) between States and the International Atomic Energy Agency for the Application of Safeguards. The Model Protocol makes explicit that one IAEA goal is to provide assurance of the absence of undeclared nuclear material and activities. The Model Protocol requires an expanded declaration that identifies a State's nuclear potential, empowers the IAEA to raise questions about the correctness and completeness of the State's declaration, and, if needed, allows IAEA access to locations. The information required and the locations available for access are much broader than those provided for under INFCIRC/153. The negotiation was completed in quite a short time because it started with a relatively complete draft of an agreement prepared by the IAEA Secretariat. This paper describes how the Model Protocol was constructed and reviews key decisions that were made both during the five-year period and in the actual negotiation.

  11. The Evolution of Human Intelligence and the Coefficient of Additive Genetic Variance in Human Brain Size

    ERIC Educational Resources Information Center

    Miller, Geoffrey F.; Penke, Lars

    2007-01-01

    Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…

  12. Animal models for genetic neuromuscular diseases.

    PubMed

    Vainzof, Mariz; Ayub-Guerrieri, Danielle; Onofre, Paula C G; Martins, Poliana C M; Lopes, Vanessa F; Zilberztajn, Dinorah; Maia, Lucas S; Sell, Karen; Yamamoto, Lydia U

    2008-03-01

    , both presenting significant reduction of alpha2-laminin in the muscle and a severe phenotype. The myodystrophy mouse (Large(myd)) harbors a mutation in the glycosyltransferase Large, which leads to altered glycosylation of alpha-DG, and also a severe phenotype. Other informative models for muscle proteins include the knockout mouse for myostatin, which demonstrated that this protein is a negative regulator of muscle growth. Additionally, the stress syndrome in pigs, caused by mutations in the porcine RYR1 gene, helped to localize the gene causing malignant hypertermia and Central Core myopathy in humans. The study of animal models for genetic diseases, in spite of the existence of differences in some phenotypes, can provide important clues to the understanding of the pathogenesis of these disorders and are also very valuable for testing strategies for therapeutic approaches. PMID:18202836

  13. Detecting contaminated birthdates using generalized additive models

    PubMed Central

    2014-01-01

    Background Erroneous patient birthdates are common in health databases. Detection of these errors usually involves manual verification, which can be resource intensive and impractical. By identifying a frequent manifestation of birthdate errors, this paper presents a principled and statistically driven procedure to identify erroneous patient birthdates. Results Generalized additive models (GAM) enabled explicit incorporation of known demographic trends and birth patterns. With false positive rates controlled, the method identified birthdate contamination with high accuracy. In the health data set used, of the 58 actual incorrect birthdates manually identified by the domain expert, the GAM-based method identified 51, with 8 false positives (resulting in a positive predictive value of 86.0% (51/59) and a false negative rate of 12.0% (7/58)). These results outperformed linear time-series models. Conclusions The GAM-based method is an effective approach to identify systemic birthdate errors, a common data quality issue in both clinical and administrative databases, with high accuracy. PMID:24923281

  14. Routine Discovery of Complex Genetic Models using Genetic Algorithms

    PubMed Central

    Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

    2010-01-01

    Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

  15. Routine Discovery of Complex Genetic Models using Genetic Algorithms.

    PubMed

    Moore, Jason H; Hahn, Lance W; Ritchie, Marylyn D; Thornton, Tricia A; White, Bill C

    2004-02-01

    Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes.

  16. Epistasis Is a Major Determinant of the Additive Genetic Variance in Mimulus guttatus

    PubMed Central

    Monnahan, Patrick J.; Kelly, John K.

    2015-01-01

    The influence of genetic interactions (epistasis) on the genetic variance of quantitative traits is a major unresolved problem relevant to medical, agricultural, and evolutionary genetics. The additive genetic component is typically a high proportion of the total genetic variance in quantitative traits, despite that underlying genes must interact to determine phenotype. This study estimates direct and interaction effects for 11 pairs of Quantitative Trait Loci (QTLs) affecting floral traits within a single population of Mimulus guttatus. With estimates of all 9 genotypes for each QTL pair, we are able to map from QTL effects to variance components as a function of population allele frequencies, and thus predict changes in variance components as allele frequencies change. This mapping requires an analytical framework that properly accounts for bias introduced by estimation errors. We find that even with abundant interactions between QTLs, most of the genetic variance is likely to be additive. However, the strong dependency of allelic average effects on genetic background implies that epistasis is a major determinant of the additive genetic variance, and thus, the population’s ability to respond to selection. PMID:25946702

  17. A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.

    PubMed

    Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan

    2015-01-01

    Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance

  18. A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana

    PubMed Central

    Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan

    2015-01-01

    Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance

  19. Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments.

    PubMed

    Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

    2015-12-01

    The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families.

  20. Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

    PubMed Central

    Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

    2015-01-01

    The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

  1. Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects.

    PubMed

    Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A

    2016-03-01

    The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates' offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of "half-sibling" in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure.

  2. Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects

    PubMed Central

    Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A.

    2016-01-01

    The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure. PMID:26801647

  3. Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects.

    PubMed

    Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A

    2016-03-01

    The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates' offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of "half-sibling" in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure. PMID:26801647

  4. Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

    PubMed Central

    Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

    2014-01-01

    Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

  5. Additive functions in boolean models of gene regulatory network modules.

    PubMed

    Darabos, Christian; Di Cunto, Ferdinando; Tomassini, Marco; Moore, Jason H; Provero, Paolo; Giacobini, Mario

    2011-01-01

    Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity

  6. Additive Functions in Boolean Models of Gene Regulatory Network Modules

    PubMed Central

    Darabos, Christian; Di Cunto, Ferdinando; Tomassini, Marco; Moore, Jason H.; Provero, Paolo; Giacobini, Mario

    2011-01-01

    Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity

  7. Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

    PubMed Central

    Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

    2015-01-01

    Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

  8. The contribution of additive genetic variation to personality variation: heritability of personality.

    PubMed

    Dochtermann, Ned A; Schwab, Tori; Sih, Andrew

    2015-01-01

    Individual animals frequently exhibit repeatable differences from other members of their population, differences now commonly referred to as 'animal personality'. Personality differences can arise, for example, from differences in permanent environmental effects--including parental and epigenetic contributors--and the effect of additive genetic variation. Although several studies have evaluated the heritability of behaviour, less is known about general patterns of heritability and additive genetic variation in animal personality. As overall variation in behaviour includes both the among-individual differences that reflect different personalities and temporary environmental effects, it is possible for personality to be largely genetically influenced even when heritability of behaviour per se is quite low. The relative contribution of additive genetic variation to personality variation can be estimated whenever both repeatability and heritability are estimated for the same data. Using published estimates to address this issue, we found that approximately 52% of animal personality variation was attributable to additive genetic variation. Thus, while the heritability of behaviour is often moderate or low, the heritability of personality is much higher. Our results therefore (i) demonstrate that genetic differences are likely to be a major contributor to variation in animal personality and (ii) support the phenotypic gambit: that evolutionary inferences drawn from repeatability estimates may often be justified.

  9. Large animal models of rare genetic disorders: sheep as phenotypically relevant models of human genetic disease.

    PubMed

    Pinnapureddy, Ashish R; Stayner, Cherie; McEwan, John; Baddeley, Olivia; Forman, John; Eccles, Michael R

    2015-09-02

    Animals that accurately model human disease are invaluable in medical research, allowing a critical understanding of disease mechanisms, and the opportunity to evaluate the effect of therapeutic compounds in pre-clinical studies. Many types of animal models are used world-wide, with the most common being small laboratory animals, such as mice. However, rodents often do not faithfully replicate human disease, despite their predominant use in research. This discordancy is due in part to physiological differences, such as body size and longevity. In contrast, large animal models, including sheep, provide an alternative to mice for biomedical research due to their greater physiological parallels with humans. Completion of the full genome sequences of many species, and the advent of Next Generation Sequencing (NGS) technologies, means it is now feasible to screen large populations of domesticated animals for genetic variants that resemble human genetic diseases, and generate models that more accurately model rare human pathologies. In this review, we discuss the notion of using sheep as large animal models, and their advantages in modelling human genetic disease. We exemplify several existing naturally occurring ovine variants in genes that are orthologous to human disease genes, such as the Cln6 sheep model for Batten disease. These, and other sheep models, have contributed significantly to our understanding of the relevant human disease process, in addition to providing opportunities to trial new therapies in animals with similar body and organ size to humans. Therefore sheep are a significant species with respect to the modelling of rare genetic human disease, which we summarize in this review.

  10. [Food additives and genetically modified food--a risk for allergic patients?].

    PubMed

    Wüthrich, B

    1999-04-01

    Adverse reactions to food and food additives must be classified according to pathogenic criteria. It is necessary to strictly differentiate between an allergy, triggered by a substance-specific immunological mechanism, and an intolerance, in which no specific immune reaction can be established. In contrast to views expressed in the media, by laymen and patients, adverse reactions to additives are less frequent than is believed. Due to frequently "alternative" methods of examination, an allergy to food additives is often wrongly blamed as the cause of a wide variety of symptoms and illness. Diagnosing an allergy or intolerance to additives normally involves carrying out double-blind, placebo-controlled oral provocation tests with food additives. Allergic reactions to food additives occur particularly against additives which are organic in origin. In principle, it is possible that during the manufacture of genetically modified plants and food, proteins are transferred which potentially create allergies. However, legislation exists both in the USA (Federal Drug Administration, FDA) and in Switzerland (Ordinance on the approval process for GM food, GM food additives and GM accessory agents for processing) which require a careful analysis before a genetically modified product is launched, particularly where foreign genes are introduced. Products containing genetically modified organisms (GMO) as additives must be declared. In addition, the source of the foreign protein must be identified. The "Round-up ready" (RR) soya flour introduced in Switzerland is no different from natural soya flour in terms of its allergenic potential. Genetically modified food can be a blessing for allergic individuals if gene technology were to succeed in removing the allergen (e.g. such possibilities exist for rice). The same caution shown towards genetically modified food might also be advisable for foreign food in our diet. Luckily, the immune system of the digestive tract in healthy people

  11. [Food additives and genetically modified food--a risk for allergic patients?].

    PubMed

    Wüthrich, B

    1999-04-01

    Adverse reactions to food and food additives must be classified according to pathogenic criteria. It is necessary to strictly differentiate between an allergy, triggered by a substance-specific immunological mechanism, and an intolerance, in which no specific immune reaction can be established. In contrast to views expressed in the media, by laymen and patients, adverse reactions to additives are less frequent than is believed. Due to frequently "alternative" methods of examination, an allergy to food additives is often wrongly blamed as the cause of a wide variety of symptoms and illness. Diagnosing an allergy or intolerance to additives normally involves carrying out double-blind, placebo-controlled oral provocation tests with food additives. Allergic reactions to food additives occur particularly against additives which are organic in origin. In principle, it is possible that during the manufacture of genetically modified plants and food, proteins are transferred which potentially create allergies. However, legislation exists both in the USA (Federal Drug Administration, FDA) and in Switzerland (Ordinance on the approval process for GM food, GM food additives and GM accessory agents for processing) which require a careful analysis before a genetically modified product is launched, particularly where foreign genes are introduced. Products containing genetically modified organisms (GMO) as additives must be declared. In addition, the source of the foreign protein must be identified. The "Round-up ready" (RR) soya flour introduced in Switzerland is no different from natural soya flour in terms of its allergenic potential. Genetically modified food can be a blessing for allergic individuals if gene technology were to succeed in removing the allergen (e.g. such possibilities exist for rice). The same caution shown towards genetically modified food might also be advisable for foreign food in our diet. Luckily, the immune system of the digestive tract in healthy people

  12. Do Health Professionals Need Additional Competencies for Stratified Cancer Prevention Based on Genetic Risk Profiling?

    PubMed Central

    Chowdhury, Susmita; Henneman, Lidewij; Dent, Tom; Hall, Alison; Burton, Alice; Pharoah, Paul; Pashayan, Nora; Burton, Hilary

    2015-01-01

    There is growing evidence that inclusion of genetic information about known common susceptibility variants may enable population risk-stratification and personalized prevention for common diseases including cancer. This would require the inclusion of genetic testing as an integral part of individual risk assessment of an asymptomatic individual. Front line health professionals would be expected to interact with and assist asymptomatic individuals through the risk stratification process. In that case, additional knowledge and skills may be needed. Current guidelines and frameworks for genetic competencies of non-specialist health professionals place an emphasis on rare inherited genetic diseases. For common diseases, health professionals do use risk assessment tools but such tools currently do not assess genetic susceptibility of individuals. In this article, we compare the skills and knowledge needed by non-genetic health professionals, if risk-stratified prevention is implemented, with existing competence recommendations from the UK, USA and Europe, in order to assess the gaps in current competences. We found that health professionals would benefit from understanding the contribution of common genetic variations in disease risk, the rationale for a risk-stratified prevention pathway, and the implications of using genomic information in risk-assessment and risk management of asymptomatic individuals for common disease prevention. PMID:26068647

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

    NASA Astrophysics Data System (ADS)

    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.

  14. Additives

    NASA Technical Reports Server (NTRS)

    Smalheer, C. V.

    1973-01-01

    The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

  15. LISREL Modeling: Genetic and Environmental Influences on IQ Revisited.

    ERIC Educational Resources Information Center

    Chipuer, Heather M.; And Others

    1990-01-01

    A model-fitting analysis of the covariance structure of an intelligence quotient (IQ) data set is reported using a model that considers additive and nonadditive genetic parameters and shared and nonshared environment parameters that permit different estimates for different types of relatives. The use of LISREL for such purposes is reviewed. (SLD)

  16. Genetically Engineered Pig Models for Human Diseases

    PubMed Central

    Prather, Randall S.; Lorson, Monique; Ross, Jason W.; Whyte, Jeffrey J.; Walters, Eric

    2015-01-01

    Although pigs are used widely as models of human disease, their utility as models has been enhanced by genetic engineering. Initially, transgenes were added randomly to the genome, but with the application of homologous recombination, zinc finger nucleases, and transcription activator-like effector nuclease (TALEN) technologies, now most any genetic change that can be envisioned can be completed. To date these genetic modifications have resulted in animals that have the potential to provide new insights into human diseases for which a good animal model did not exist previously. These new animal models should provide the preclinical data for treatments that are developed for diseases such as Alzheimer's disease, cystic fibrosis, retinitis pigmentosa, spinal muscular atrophy, diabetes, and organ failure. These new models will help to uncover aspects and treatments of these diseases that were otherwise unattainable. The focus of this review is to describe genetically engineered pigs that have resulted in models of human diseases. PMID:25387017

  17. Additive interaction in survival analysis: use of the additive hazards model.

    PubMed

    Rod, Naja Hulvej; Lange, Theis; Andersen, Ingelise; Marott, Jacob Louis; Diderichsen, Finn

    2012-09-01

    It is a widely held belief in public health and clinical decision-making that interventions or preventive strategies should be aimed at patients or population subgroups where most cases could potentially be prevented. To identify such subgroups, deviation from additivity of absolute effects is the relevant measure of interest. Multiplicative survival models, such as the Cox proportional hazards model, are often used to estimate the association between exposure and risk of disease in prospective studies. In Cox models, deviations from additivity have usually been assessed by surrogate measures of additive interaction derived from multiplicative models-an approach that is both counter-intuitive and sometimes invalid. This paper presents a straightforward and intuitive way of assessing deviation from additivity of effects in survival analysis by use of the additive hazards model. The model directly estimates the absolute size of the deviation from additivity and provides confidence intervals. In addition, the model can accommodate both continuous and categorical exposures and models both exposures and potential confounders on the same underlying scale. To illustrate the approach, we present an empirical example of interaction between education and smoking on risk of lung cancer. We argue that deviations from additivity of effects are important for public health interventions and clinical decision-making, and such estimations should be encouraged in prospective studies on health. A detailed implementation guide of the additive hazards model is provided in the appendix.

  18. Modeling techniques for gaining additional urban space

    NASA Astrophysics Data System (ADS)

    Thunig, Holger; Naumann, Simone; Siegmund, Alexander

    2009-09-01

    One of the major accompaniments of the globalization is the rapid growing of urban areas. Urban sprawl is the main environmental problem affecting those cities across different characteristics and continents. Various reasons for the increase in urban sprawl in the last 10 to 30 years have been proposed [1], and often depend on the socio-economic situation of cities. The quantitative reduction and the sustainable handling of land should be performed by inner urban development instead of expanding urban regions. Following the principal "spare the urban fringe, develop the inner suburbs first" requires differentiated tools allowing for quantitative and qualitative appraisals of current building potentials. Using spatial high resolution remote sensing data within an object-based approach enables the detection of potential areas while GIS-data provides information for the quantitative valuation. This paper presents techniques for modeling urban environment and opportunities of utilization of the retrieved information for urban planners and their special needs.

  19. Joint Modeling of Imaging and Genetics

    PubMed Central

    Batmanghelich, Nematollah K.; Dalca, Adrian V.; Sabuncu, Mert R.; Golland, Polina

    2014-01-01

    We propose a unified Bayesian framework for detecting genetic variants associated with a disease while exploiting image-based features as an intermediate phenotype. Traditionally, imaging genetics methods comprise two separate steps. First, image features are selected based on their relevance to the disease phenotype. Second, a set of genetic variants are identified to explain the selected features. In contrast, our method performs these tasks simultaneously to ultimately assign probabilistic measures of relevance to both genetic and imaging markers. We derive an efficient approximate inference algorithm that handles high dimensionality of imaging genetic data. We evaluate the algorithm on synthetic data and show that it outperforms traditional models. We also illustrate the application of the method on ADNI data. PMID:24684016

  20. Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach

    NASA Astrophysics Data System (ADS)

    Kumral, Mustafa; Ozer, Umit

    2013-03-01

    Grade and tonnage are the most important technical uncertainties in mining ventures because of the use of estimations/simulations, which are mostly generated from drill data. Open pit mines are planned and designed on the basis of the blocks representing the entire orebody. Each block has different estimation/simulation variance reflecting uncertainty to some extent. The estimation/simulation realizations are submitted to mine production scheduling process. However, the use of a block model with varying estimation/simulation variances will lead to serious risk in the scheduling. In the medium of multiple simulations, the dispersion variances of blocks can be thought to regard technical uncertainties. However, the dispersion variance cannot handle uncertainty associated with varying estimation/simulation variances of blocks. This paper proposes an approach that generates the configuration of the best additional drilling campaign to generate more homogenous estimation/simulation variances of blocks. In other words, the objective is to find the best drilling configuration in such a way as to minimize grade uncertainty under budget constraint. Uncertainty measure of the optimization process in this paper is interpolation variance, which considers data locations and grades. The problem is expressed as a minmax problem, which focuses on finding the best worst-case performance i.e., minimizing interpolation variance of the block generating maximum interpolation variance. Since the optimization model requires computing the interpolation variances of blocks being simulated/estimated in each iteration, the problem cannot be solved by standard optimization tools. This motivates to use two-space genetic algorithm (GA) approach to solve the problem. The technique has two spaces: feasible drill hole configuration with minimization of interpolation variance and drill hole simulations with maximization of interpolation variance. Two-space interacts to find a minmax solution

  1. Genetic and environmental melanoma models in fish

    PubMed Central

    Patton, E Elizabeth; Mitchell, David L; Nairn, Rodney S

    2010-01-01

    Experimental animal models are extremely valuable for the study of human diseases, especially those with underlying genetic components. The exploitation of various animal models, from fruitflies to mice, has led to major advances in our understanding of the etiologies of many diseases, including cancer. Cutaneous malignant melanoma is a form of cancer for which both environmental insult (i.e., UV) and hereditary predisposition are major causative factors. Fish melanoma models have been used in studies of both spontaneous and induced melanoma formation. Genetic hybrids between platyfish and swordtails, different species of the genus Xiphophorus, have been studied since the 1920s to identify genetic determinants of pigmentation and melanoma formation. Recently, transgenesis has been used to develop zebrafish and medaka models for melanoma research. This review will provide a historical perspective on the use of fish models in melanoma research, and an updated summary of current and prospective studies using these unique experimental systems. PMID:20230482

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

    PubMed

    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.

  3. Genetically modified mouse models addressing gonadotropin function.

    PubMed

    Ratner, Laura D; Rulli, Susana B; Huhtaniemi, Ilpo T

    2014-03-01

    The development of genetically modified animals has been useful to understand the mechanisms involved in the regulation of the gonadotropin function. It is well known that alterations in the secretion of a single hormone is capable of producing profound reproductive abnormalities. Human chorionic gonadotropin (hCG) is a glycoprotein hormone normally secreted by the human placenta, and structurally and functionally it is related to pituitary LH. LH and hCG bind to the same LH/hCG receptor, and hCG is often used as an analog of LH to boost gonadotropin action. There are many physiological and pathological conditions where LH/hCG levels and actions are elevated. In order to understand how elevated LH/hCG levels may impact on the hypothalamic-pituitary-gonadal axis we have developed a transgenic mouse model with chronic hCG hypersecretion. Female mice develop many gonadal and extragonadal phenotypes including obesity, infertility, hyperprolactinemia, and pituitary and mammary gland tumors. This article summarizes recent findings on the mechanisms involved in pituitary gland tumorigenesis and hyperprolactinemia in the female mice hypersecreting hCG, in particular the relationship of progesterone with the hyperprolactinemic condition of the model. In addition, we describe the role of hyperprolactinemia as the main cause of infertility and the phenotypic abnormalities in these mice, and the use of dopamine agonists bromocriptine and cabergoline to normalize these conditions.

  4. Genetically modified pig models for neurodegenerative disorders.

    PubMed

    Holm, Ida E; Alstrup, Aage Kristian Olsen; Luo, Yonglun

    2016-01-01

    Increasing incidence of neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease has become one of the most challenging health issues in ageing humans. One approach to combat this is to generate genetically modified animal models of neurodegenerative disorders for studying pathogenesis, prognosis, diagnosis, treatment, and prevention. Owing to the genetic, anatomic, physiologic, pathologic, and neurologic similarities between pigs and humans, genetically modified pig models of neurodegenerative disorders have been attractive large animal models to bridge the gap of preclinical investigations between rodents and humans. In this review, we provide a neuroanatomical overview in pigs and summarize and discuss the generation of genetically modified pig models of neurodegenerative disorders including Alzheimer's diseases, Huntington's disease, Parkinson's disease, amyotrophic lateral sclerosis, spinal muscular atrophy, and ataxia-telangiectasia. We also highlight how non-invasive bioimaging technologies such as positron emission tomography (PET), computer tomography (CT), and magnetic resonance imaging (MRI), and behavioural testing have been applied to characterize neurodegenerative pig models. We further propose a multiplex genome editing and preterm recloning (MAP) approach by using the rapid growth of the ground-breaking precision genome editing technology CRISPR/Cas9 and somatic cell nuclear transfer (SCNT). With this approach, we hope to shorten the temporal requirement in generating multiple transgenic pigs, increase the survival rate of founder pigs, and generate genetically modified pigs that will more closely resemble the disease-causing mutations and recapitulate pathological features of human conditions. PMID:26446984

  5. Genetic models of homosexuality: generating testable predictions.

    PubMed

    Gavrilets, Sergey; Rice, William R

    2006-12-22

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism.

  6. Genetic linkage analysis to identify a gene required for the addition of phosphoethanolamine to meningococcal lipopolysaccharide.

    PubMed

    Tang, Christoph M; Stroud, Dave; Mackinnon, Fiona; Makepeace, Katherine; Plested, Joyce; Moxon, E Richard; Chalmers, Ronald

    2002-02-01

    Lipopolysaccharide (LPS) is important for the virulence of Neisseria meningitidis, and is the target of immune responses. We took advantage of a monoclonal antibody (Mab B5) that recognises phosphoethanolamine (PEtn) attached to the inner core of meningococcal LPS to identify genes required for the addition of PEtn to LPS. Insertional mutants that lost Mab B5 reactivity were isolated and characterised, but failed to yield genes directly responsible for PEtn substitution. Subsequent genetic linkage analysis was used to define a region of DNA containing a single intact open reading frame which is sufficient to confer B5 reactivity to a B5 negative meningococcal isolate. The results provide an initial characterisation of the genetic basis of a key, immunodominant epitope of meningococcal LPS.

  7. Criteria for deviation from predictions by the concentration addition model.

    PubMed

    Takeshita, Jun-Ichi; Seki, Masanori; Kamo, Masashi

    2016-07-01

    Loewe's additivity (concentration addition) is a well-known model for predicting the toxic effects of chemical mixtures under the additivity assumption of toxicity. However, from the perspective of chemical risk assessment and/or management, it is important to identify chemicals whose toxicities are additive when present concurrently, that is, it should be established whether there are chemical mixtures to which the concentration addition predictive model can be applied. The objective of the present study was to develop criteria for judging test results that deviated from the predictions by the concentration addition chemical mixture model. These criteria were based on the confidence interval of the concentration addition model's prediction and on estimation of errors of the predicted concentration-effect curves by toxicity tests after exposure to single chemicals. A log-logit model with 2 parameters was assumed for the concentration-effect curve of each individual chemical. These parameters were determined by the maximum-likelihood method, and the criteria were defined using the variances and the covariance of the parameters. In addition, the criteria were applied to a toxicity test of a binary mixture of p-n-nonylphenol and p-n-octylphenol using the Japanese killifish, medaka (Oryzias latipes). Consequently, the concentration addition model using confidence interval was capable of predicting the test results at any level, and no reason for rejecting the concentration addition was found. Environ Toxicol Chem 2016;35:1806-1814. © 2015 SETAC. PMID:26660330

  8. Genetic demographic networks: Mathematical model and applications.

    PubMed

    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

  9. Additive genetic variance and developmental plasticity in growth trajectories in a wild cooperative mammal.

    PubMed

    Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T

    2014-09-01

    Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early.

  10. Additive genetic variance and developmental plasticity in growth trajectories in a wild cooperative mammal.

    PubMed

    Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T

    2014-09-01

    Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early. PMID:24962704

  11. Addition of restriction fragment length polymorphism markers to the genetic linkage map of Brassica rapa L. (syn. campestris).

    PubMed

    Panigrahi, Jogeswar; Patnaik, Anjana; Kole, Phullara; Koleb, Chitta ranjan

    2009-01-01

    Genetic linkage analysis of 151 restriction fragment length polymorphism (RFLP) loci, that included eight new loci, detected by the six probes in the present study, and four trait loci including seed colour, leaf pubescence, resistance to white rust caused by Albugo candida race-2 (AC-2) and race-7 (AC-7) employing the MAPMAKER/EXP 3.0 programme led to the development of 10 linkage groups (LGs) spanning over 44.4 centiMorgan (cM) to 130.4 cM containing 9 to 22 loci and two short LGs with two or three marker loci in Brassica rapa. The enriched map covers 993.1 cM of B. rapa genome with an average marker interval of 6.41. Eight new RFLP loci occupied new map positions on five linkage groups, LG 2, 3, 6, 8 and 9. Addition of these RFLP loci led to appreciable changes in the corresponding linkage groups and resulted in an increase of the total map length by 102.8 cM and of the marker interval by 0.35 cM. Interval mapping by using the computer programme MAPMAKER/ QTL 1.1 for scanning the genetic map led to the detection of one major quantitative trait locus (QTL) in LG 4 and one minor QTL in LG 8 governing resistance to AC-7. Both QTLs contributed 7.89 to the interaction phenotype (IP) score with 96.3% genetic variation. The multi-locus model suggested additive gene action with 96.8% genetic variation.

  12. Downscaling GCM Output with Genetic Programming Model

    NASA Astrophysics Data System (ADS)

    Shi, X.; Dibike, Y. B.; Coulibaly, P.

    2004-05-01

    Climate change impact studies on watershed hydrology require reliable data at appropriate spatial and temporal resolution. However, the outputs of the current global climate models (GCMs) cannot be used directly because GCM do not provide hourly or daily precipitation and temperature reliable enough for hydrological modeling. Nevertheless, we can get more reliable data corresponding to future climate scenarios derived from GCM outputs using the so called 'downscaling techniques'. This study applies Genetic Programming (GP) based technique to downscale daily precipitation and temperature values at the Chute-du-Diable basin of the Saguenay watershed in Canada. In applying GP downscaling technique, the objective is to find a relationship between the large-scale predictor variables (NCEP data which provide daily information concerning the observed large-scale state of the atmosphere) and the predictand (meteorological data which describes conditions at the site scale). The selection of the most relevant predictor variables is achieved using the Pearson's coefficient of determination ( R2) (between the large-scale predictor variables and the daily meteorological data). In this case, the period (1961 - 2000) is identified to represent the current climate condition. For the forty years of data, the first 30 years (1961-1990) are considered for calibrating the models while the remaining ten years of data (1991-2000) are used to validate those models. In general, the R2 between the predictor variables and each predictand is very low in case of precipitation compared to that of maximum and minimum temperature. Moreover, the strength of individual predictors varies for every month and for each GP grammar. Therefore, the most appropriate combination of predictors has to be chosen by looking at the output analysis of all the twelve months and the different GP grammars. During the calibration of the GP model for precipitation downscaling, in addition to the mean daily

  13. Genetic rearrangements of six wheat-agropyron cristatum 6P addition lines revealed by molecular markers.

    PubMed

    Han, Haiming; Bai, Li; Su, Junji; Zhang, Jinpeng; Song, Liqiang; Gao, Ainong; Yang, Xinming; Li, Xiuquan; Liu, Weihua; Li, Lihui

    2014-01-01

    Agropyron cristatum (L.) Gaertn. (2n = 4x = 28, PPPP) not only is cultivated as pasture fodder but also could provide many desirable genes for wheat improvement. It is critical to obtain common wheat-A. cristatum alien disomic addition lines to locate the desired genes on the P genome chromosomes. Comparative analysis of the homoeologous relationships between the P genome chromosome and wheat genome chromosomes is a key step in transferring different desirable genes into common wheat and producing the desired alien translocation line while compensating for the loss of wheat chromatin. In this study, six common wheat-A. cristatum disomic addition lines were produced and analyzed by phenotypic examination, genomic in situ hybridization (GISH), SSR markers from the ABD genomes and STS markers from the P genome. Comparative maps, six in total, were generated and demonstrated that all six addition lines belonged to homoeologous group 6. However, chromosome 6P had undergone obvious rearrangements in different addition lines compared with the wheat chromosome, indicating that to obtain a genetic compensating alien translocation line, one should recombine alien chromosomal regions with homoeologous wheat chromosomes. Indeed, these addition lines were classified into four types based on the comparative mapping: 6PI, 6PII, 6PIII, and 6PIV. The different types of chromosome 6P possessed different desirable genes. For example, the 6PI type, containing three addition lines, carried genes conferring high numbers of kernels per spike and resistance to powdery mildew, important traits for wheat improvement. These results may prove valuable for promoting the development of conventional chromosome engineering techniques toward molecular chromosome engineering. PMID:24595330

  14. Genetically Engineered Mouse Models of Pituitary Tumors

    PubMed Central

    Cano, David A.; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso

    2014-01-01

    Animal models constitute valuable tools for investigating the pathogenesis of cancer as well as for preclinical testing of novel therapeutics approaches. However, the pathogenic mechanisms of pituitary-tumor formation remain poorly understood, particularly in sporadic adenomas, thus, making it a challenge to model pituitary tumors in mice. Nevertheless, genetically engineered mouse models (GEMMs) of pituitary tumors have provided important insight into pituitary tumor biology. In this paper, we review various GEMMs of pituitary tumors, highlighting their contributions and limitations, and discuss opportunities for research in the field. PMID:25136513

  15. Comprehensive European dietary exposure model (CEDEM) for food additives.

    PubMed

    Tennant, David R

    2016-05-01

    European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

  16. Heritability of heterozygosity offers a new way of understanding why dominant gene action contributes to additive genetic variance.

    PubMed

    Nietlisbach, Pirmin; Hadfield, Jarrod D

    2015-07-01

    Whenever allele frequencies are unequal, nonadditive gene action contributes to additive genetic variance and therefore the resemblance between parents and offspring. The reason for this has not been easy to understand. Here, we present a new single-locus decomposition of additive genetic variance that may give greater intuition about this important result. We show that the contribution of dominant gene action to parent-offspring resemblance only depends on the degree to which the heterozygosity of parents and offspring covary. Thus, dominant gene action only contributes to additive genetic variance when heterozygosity is heritable. Under most circumstances this is the case because individuals with rare alleles are more likely to be heterozygous, and because they pass rare alleles to their offspring they also tend to have heterozygous offspring. When segregating alleles are at equal frequency there are no rare alleles, the heterozygosities of parents and offspring are uncorrelated and dominant gene action does not contribute to additive genetic variance. PMID:26100570

  17. A Genetic Porcine Model of Cancer

    PubMed Central

    Schook, Lawrence B.; Collares, Tiago V.; Hu, Wenping; Liang, Ying; Rodrigues, Fernanda M.; Rund, Laurie A.; Schachtschneider, Kyle M.; Seixas, Fabiana K.; Singh, Kuldeep; Wells, Kevin D.; Walters, Eric M.; Prather, Randall S.; Counter, Christopher M.

    2015-01-01

    The large size of the pig and its similarity in anatomy, physiology, metabolism, and genetics to humans make it an ideal platform to develop a genetically defined, large animal model of cancer. To this end, we created a transgenic “oncopig” line encoding Cre recombinase inducible porcine transgenes encoding KRASG12D and TP53R167H, which represent a commonly mutated oncogene and tumor suppressor in human cancers, respectively. Treatment of cells derived from these oncopigs with the adenovirus encoding Cre (AdCre) led to KRASG12D and TP53R167H expression, which rendered the cells transformed in culture and tumorigenic when engrafted into immunocompromised mice. Finally, injection of AdCre directly into these oncopigs led to the rapid and reproducible tumor development of mesenchymal origin. Transgenic animals receiving AdGFP (green fluorescent protein) did not have any tumor mass formation or altered histopathology. This oncopig line could thus serve as a genetically malleable model for potentially a wide spectrum of cancers, while controlling for temporal or spatial genesis, which should prove invaluable to studies previously hampered by the lack of a large animal model of cancer. PMID:26132737

  18. Genetic demographic networks: Mathematical model and applications.

    PubMed

    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

  19. Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes.

    PubMed

    Travers, L M; Simmons, L W; Garcia-Gonzalez, F

    2016-05-01

    Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes.

  20. Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes.

    PubMed

    Travers, L M; Simmons, L W; Garcia-Gonzalez, F

    2016-05-01

    Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes. PMID:26801640

  1. Very low levels of direct additive genetic variance in fitness and fitness components in a red squirrel population

    PubMed Central

    McFarlane, S Eryn; Gorrell, Jamieson C; Coltman, David W; Humphries, Murray M; Boutin, Stan; McAdam, Andrew G

    2014-01-01

    A trait must genetically correlate with fitness in order to evolve in response to natural selection, but theory suggests that strong directional selection should erode additive genetic variance in fitness and limit future evolutionary potential. Balancing selection has been proposed as a mechanism that could maintain genetic variance if fitness components trade off with one another and has been invoked to account for empirical observations of higher levels of additive genetic variance in fitness components than would be expected from mutation–selection balance. Here, we used a long-term study of an individually marked population of North American red squirrels (Tamiasciurus hudsonicus) to look for evidence of (1) additive genetic variance in lifetime reproductive success and (2) fitness trade-offs between fitness components, such as male and female fitness or fitness in high- and low-resource environments. “Animal model” analyses of a multigenerational pedigree revealed modest maternal effects on fitness, but very low levels of additive genetic variance in lifetime reproductive success overall as well as fitness measures within each sex and environment. It therefore appears that there are very low levels of direct genetic variance in fitness and fitness components in red squirrels to facilitate contemporary adaptation in this population. PMID:24963372

  2. On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis

    PubMed Central

    Li, Bing; Chun, Hyonho; Zhao, Hongyu

    2014-01-01

    We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis. PMID:26401064

  3. Genetic simplex modeling of Eysenck's dimensions of personality in a sample of young Australian twins.

    PubMed

    Gillespie, Nathan A; Evans, David E; Wright, Margie M; Martin, Nicholas G

    2004-12-01

    The relative stability and magnitude of genetic and environmental effects underlying major dimensions of adolescent personality across time were investigated. The Junior Eysenck Personality Questionnaire was administered to over 540 twin pairs at ages 12, 14 and 16 years. Their personality scores were analyzed using genetic simplex modeling which explicitly took into account the longitudinal nature of the data. With the exception of the dimension lie, multivariate model fitting results revealed that familial aggregation was entirely explained by additive genetic effects. Results from simplex model fitting suggest that large proportions of the additive genetic variance observed at ages 14 and 16 years could be explained by genetic effects present at the age of 12 years. There was also evidence for smaller but significant genetic innovations at 14 and 16 years of age for male and female neuroticism, at 14 years for male extraversion, at 14 and 16 years for female psychoticism, and at 14 years for male psychoticism.

  4. Identifying genetically driven clinical phenotypes using linear mixed models

    PubMed Central

    Mosley, Jonathan D.; Witte, John S.; Larkin, Emma K.; Bastarache, Lisa; Shaffer, Christian M.; Karnes, Jason H.; Stein, C. Michael; Phillips, Elizabeth; Hebbring, Scott J.; Brilliant, Murray H.; Mayer, John; Ye, Zhan; Roden, Dan M.; Denny, Joshua C.

    2016-01-01

    We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q<0.05) phenotypes associated with HLA SNP variation and show that hypothyroidism is genetically correlated with Type I diabetes (rG=0.31, s.e. 0.12, P=0.003). We also report novel SNP associations for hypothyroidism near HLA-DQA1/HLA-DQB1 at rs6906021 (combined odds ratio (OR)=1.2 (95% confidence interval (CI): 1.1–1.2), P=9.8 × 10−11) and for polymyalgia rheumatica near C6orf10 at rs6910071 (OR=1.5 (95% CI: 1.3–1.6), P=1.3 × 10−10). Phenome-wide application of GLMMs identifies phenotypes with important genetic drivers, and focusing on these phenotypes can identify novel genetic associations. PMID:27109359

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

    PubMed

    Phillips, Tamara J; Shabani, Shkelzen

    2015-01-01

    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 development of a

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

    PubMed Central

    Phillips, Tamara J.; Shabani, Shkelzen

    2015-01-01

    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 development of a

  7. Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

    NASA Technical Reports Server (NTRS)

    Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

    2013-01-01

    The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

  8. Electroacoustics modeling of piezoelectric welders for ultrasonic additive manufacturing processes

    NASA Astrophysics Data System (ADS)

    Hehr, Adam; Dapino, Marcelo J.

    2016-04-01

    Ultrasonic additive manufacturing (UAM) is a recent 3D metal printing technology which utilizes ultrasonic vibrations from high power piezoelectric transducers to additively weld similar and dissimilar metal foils. CNC machining is used intermittent of welding to create internal channels, embed temperature sensitive components, sensors, and materials, and for net shaping parts. Structural dynamics of the welder and work piece influence the performance of the welder and part quality. To understand the impact of structural dynamics on UAM, a linear time-invariant model is used to relate system shear force and electric current inputs to the system outputs of welder velocity and voltage. Frequency response measurements are combined with in-situ operating measurements of the welder to identify model parameters and to verify model assumptions. The proposed LTI model can enhance process consistency, performance, and guide the development of improved quality monitoring and control strategies.

  9. An Additional Symmetry in the Weinberg-Salam Model

    SciTech Connect

    Bakker, B.L.G.; Veselov, A.I.; Zubkov, M.A.

    2005-06-01

    An additional Z{sub 6} symmetry hidden in the fermion and Higgs sectors of the Standard Model has been found recently. It has a singular nature and is connected to the centers of the SU(3) and SU(2) subgroups of the gauge group. A lattice regularization of the Standard Model was constructed that possesses this symmetry. In this paper, we report our results on the numerical simulation of its electroweak sector.

  10. Genetic demixing and evolution in linear stepping stone models

    NASA Astrophysics Data System (ADS)

    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

  11. Modeling uranium transport in acidic contaminated groundwater with base addition

    SciTech Connect

    Zhang, Fan; Luo, Wensui; Parker, Jack C.; Brooks, Scott C; Watson, David B; Jardine, Philip; Gu, Baohua

    2011-01-01

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  12. Modeling uranium transport in acidic contaminated groundwater with base addition.

    PubMed

    Zhang, Fan; Luo, Wensui; Parker, Jack C; Brooks, Scott C; Watson, David B; Jardine, Philip M; Gu, Baohua

    2011-06-15

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO(3)(-), SO(4)(2-), U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  13. Large genetic animal models of Huntington's Disease.

    PubMed

    Morton, A Jennifer; Howland, David S

    2013-01-01

    The dominant nature of the Huntington's disease gene mutation has allowed genetic models to be developed in multiple species, with the mutation causing an abnormal neurological phenotype in all animals in which it is expressed. Many different rodent models have been generated. The most widely used of these, the transgenic R6/2 mouse, carries the mutation in a fragment of the human huntingtin gene and has a rapidly progressive and fatal neurological phenotype with many relevant pathological changes. Nevertheless, their rapid decline has been frequently questioned in the context of a disease that takes years to manifest in humans, and strenuous efforts have been made to make rodent models that are genetically more 'relevant' to the human condition, including full length huntingtin gene transgenic and knock-in mice. While there is no doubt that we have learned, and continue to learn much from rodent models, their usefulness is limited by two species constraints. First, the brains of rodents differ significantly from humans in both their small size and their neuroanatomical organization. Second, rodents have much shorter lifespans than humans. Here, we review new approaches taken to these challenges in the development of models of Huntington's disease in large brained, long-lived animals. We discuss the need for such models, and how they might be used to fill specific niches in preclinical Huntington's disease research, particularly in testing gene-based therapeutics. We discuss the advantages and disadvantages of animals in which the prodromal period of disease extends over a long time span. We suggest that there is considerable 'value added' for large animal models in preclinical Huntington's disease research.

  14. Using Set Model for Learning Addition of Integers

    ERIC Educational Resources Information Center

    Lestari, Umi Puji; Putri, Ratu Ilma Indra; Hartono, Yusuf

    2015-01-01

    This study aims to investigate how set model can help students' understanding of addition of integers in fourth grade. The study has been carried out to 23 students and a teacher of IVC SD Iba Palembang in January 2015. This study is a design research that also promotes PMRI as the underlying design context and activity. Results showed that the…

  15. Testing Nested Additive, Multiplicative, and General Multitrait-Multimethod Models.

    ERIC Educational Resources Information Center

    Coenders, Germa; Saris, Willem E.

    2000-01-01

    Provides alternatives to the definitions of additive and multiplicative method effects in multitrait-multimethod data given by D. Campbell and E. O'Connell (1967). The alternative definitions can be formulated by means of constraints in the parameters of the correlated uniqueness model (H. Marsh, 1989). (SLD)

  16. Toxicological safety assessment of genetically modified Bacillus thuringiensis with additional N-acyl homoserine lactonase gene.

    PubMed

    Peng, Donghai; Zhou, Chenfei; Chen, Shouwen; Ruan, Lifang; Yu, Ziniu; Sun, Ming

    2008-01-01

    The aim of the present study is to evaluate the toxicology safety to mammals of a genetically modified (GM) Bacillus thuringiensis with an additional N-acyl homoserine lactones gene (aiiA), which possesses insecticidal activity together with restraint of bacterial pathogenicity and is intended for use as a multifunctional biopesticide. Safety assessments included an acute oral toxicity test and 28-d animal feeding study in Wistar rats, primary eye and dermal irritation in Zealand White rabbits, and delayed contact hypersensitivity in guinea pigs. Tests were conducted using spray-dried powder preparation. This GM product showed toxicity neither in oral acute toxicity test nor in 28-d animal feeding test at a dose of 5,000 mg/kg body weight. During the animal feeding test, there were no significant differences in growth, food and water consumption, hematology, blood biochemical indices, organ weights, and histopathology finding between rats in controls and tested groups. Tested animals in primary eye and dermal irritation and delayed contact hypersensitivity test were also devoid of any toxicity compared to controls. All the above results demonstrated that the GM based multifunctional B. thuringiensis has low toxicity and low eye and dermal irritation and would not cause hypersensitivity to laboratory mammals and therefore could be regarded as safe for use as a pesticide.

  17. Mouse Genetic Models of Human Brain Disorders.

    PubMed

    Leung, Celeste; Jia, Zhengping

    2016-01-01

    Over the past three decades, genetic manipulations in mice have been used in neuroscience as a major approach to investigate the in vivo function of genes and their alterations. In particular, gene targeting techniques using embryonic stem cells have revolutionized the field of mammalian genetics and have been at the forefront in the generation of numerous mouse models of human brain disorders. In this review, we will first examine childhood developmental disorders such as autism, intellectual disability, Fragile X syndrome, and Williams-Beuren syndrome. We will then explore psychiatric disorders such as schizophrenia and lastly, neurodegenerative disorders including Alzheimer's disease and Parkinson's disease. We will outline the creation of these mouse models that range from single gene deletions, subtle point mutations to multi-gene manipulations, and discuss the key behavioral phenotypes of these mice. Ultimately, the analysis of the models outlined in this review will enhance our understanding of the in vivo role and underlying mechanisms of disease-related genes in both normal brain function and brain disorders, and provide potential therapeutic targets and strategies to prevent and treat these diseases. PMID:27047540

  18. Mouse Genetic Models of Human Brain Disorders

    PubMed Central

    Leung, Celeste; Jia, Zhengping

    2016-01-01

    Over the past three decades, genetic manipulations in mice have been used in neuroscience as a major approach to investigate the in vivo function of genes and their alterations. In particular, gene targeting techniques using embryonic stem cells have revolutionized the field of mammalian genetics and have been at the forefront in the generation of numerous mouse models of human brain disorders. In this review, we will first examine childhood developmental disorders such as autism, intellectual disability, Fragile X syndrome, and Williams-Beuren syndrome. We will then explore psychiatric disorders such as schizophrenia and lastly, neurodegenerative disorders including Alzheimer’s disease and Parkinson’s disease. We will outline the creation of these mouse models that range from single gene deletions, subtle point mutations to multi-gene manipulations, and discuss the key behavioral phenotypes of these mice. Ultimately, the analysis of the models outlined in this review will enhance our understanding of the in vivo role and underlying mechanisms of disease-related genes in both normal brain function and brain disorders, and provide potential therapeutic targets and strategies to prevent and treat these diseases. PMID:27047540

  19. Automatic reactor model synthesis with genetic programming.

    PubMed

    Dürrenmatt, David J; Gujer, Willi

    2012-01-01

    Successful modeling of wastewater treatment plant (WWTP) processes requires an accurate description of the plant hydraulics. Common methods such as tracer experiments are difficult and costly and thus have limited applicability in practice; engineers are often forced to rely on their experience only. An implementation of grammar-based genetic programming with an encoding to represent hydraulic reactor models as program trees should fill this gap: The encoding enables the algorithm to construct arbitrary reactor models compatible with common software used for WWTP modeling by linking building blocks, such as continuous stirred-tank reactors. Discharge measurements and influent and effluent concentrations are the only required inputs. As shown in a synthetic example, the technique can be used to identify a set of reactor models that perform equally well. Instead of being guided by experience, the most suitable model can now be chosen by the engineer from the set. In a second example, temperature measurements at the influent and effluent of a primary clarifier are used to generate a reactor model. A virtual tracer experiment performed on the reactor model has good agreement with a tracer experiment performed on-site.

  20. Genetically engineered livestock for biomedical models.

    PubMed

    Rogers, Christopher S

    2016-06-01

    To commemorate Transgenic Animal Research Conference X, this review summarizes the recent progress in developing genetically engineered livestock species as biomedical models. The first of these conferences was held in 1997, which turned out to be a watershed year for the field, with two significant events occurring. One was the publication of the first transgenic livestock animal disease model, a pig with retinitis pigmentosa. Before that, the use of livestock species in biomedical research had been limited to wild-type animals or disease models that had been induced or were naturally occurring. The second event was the report of Dolly, a cloned sheep produced by somatic cell nuclear transfer. Cloning subsequently became an essential part of the process for most of the models developed in the last 18 years and is stilled used prominently today. This review is intended to highlight the biomedical modeling achievements that followed those key events, many of which were first reported at one of the previous nine Transgenic Animal Research Conferences. Also discussed are the practical challenges of utilizing livestock disease models now that the technical hurdles of model development have been largely overcome.

  1. Genetically engineered livestock for biomedical models.

    PubMed

    Rogers, Christopher S

    2016-06-01

    To commemorate Transgenic Animal Research Conference X, this review summarizes the recent progress in developing genetically engineered livestock species as biomedical models. The first of these conferences was held in 1997, which turned out to be a watershed year for the field, with two significant events occurring. One was the publication of the first transgenic livestock animal disease model, a pig with retinitis pigmentosa. Before that, the use of livestock species in biomedical research had been limited to wild-type animals or disease models that had been induced or were naturally occurring. The second event was the report of Dolly, a cloned sheep produced by somatic cell nuclear transfer. Cloning subsequently became an essential part of the process for most of the models developed in the last 18 years and is stilled used prominently today. This review is intended to highlight the biomedical modeling achievements that followed those key events, many of which were first reported at one of the previous nine Transgenic Animal Research Conferences. Also discussed are the practical challenges of utilizing livestock disease models now that the technical hurdles of model development have been largely overcome. PMID:26820410

  2. [Questions safety and tendency of using genetically modified microorganisms in food, food additives and food derived].

    PubMed

    Khovaev, A A

    2008-01-01

    In this article analysis questions of using genetically modified microorganisms in manufacture food production, present new GMM used in manufacture -food ferments; results of medical biological appraisal/ microbiological and genetic expert examination/ of food, getting by use microorganisms or there producents with indication modern of control methods.

  3. Explanatory Models of Genetics and Genetic Risk among a Selected Group of Students.

    PubMed

    Goltz, Heather Honoré; Bergman, Margo; Goodson, Patricia

    2016-01-01

    This exploratory qualitative study focuses on how college students conceptualize genetics and genetic risk, concepts essential for genetic literacy (GL) and genetic numeracy (GN), components of overall health literacy (HL). HL is dependent on both the background knowledge and culture of a patient, and lower HL is linked to increased morbidity and mortality for a number of chronic health conditions (e.g., diabetes and cancer). A purposive sample of 86 students from three Southwestern universities participated in eight focus groups. The sample ranged in age from 18 to 54 years, and comprised primarily of female (67.4%), single (74.4%), and non-White (57%) participants, none of whom were genetics/biology majors. A holistic-content approach revealed broad categories concerning participants' explanatory models (EMs) of genetics and genetic risk. Participants' EMs were grounded in highly contextualized narratives that only partially overlapped with biomedical models. While higher education levels should be associated with predominately knowledge-based EM of genetic risk, this study shows that even in well-educated populations cultural factors can dominate. Study findings reveal gaps in how this sample of young adults obtains, processes, and understands genetic/genomic concepts. Future studies should assess how individuals with low GL and GN obtain and process genetics and genetic risk information and incorporate this information into health decision making. Future work should also address the interaction of communication between health educators, providers, and genetic counselors, to increase patient understanding of genetic risk. PMID:27376052

  4. Explanatory Models of Genetics and Genetic Risk among a Selected Group of Students

    PubMed Central

    Goltz, Heather Honoré; Bergman, Margo; Goodson, Patricia

    2016-01-01

    This exploratory qualitative study focuses on how college students conceptualize genetics and genetic risk, concepts essential for genetic literacy (GL) and genetic numeracy (GN), components of overall health literacy (HL). HL is dependent on both the background knowledge and culture of a patient, and lower HL is linked to increased morbidity and mortality for a number of chronic health conditions (e.g., diabetes and cancer). A purposive sample of 86 students from three Southwestern universities participated in eight focus groups. The sample ranged in age from 18 to 54 years, and comprised primarily of female (67.4%), single (74.4%), and non-White (57%) participants, none of whom were genetics/biology majors. A holistic-content approach revealed broad categories concerning participants’ explanatory models (EMs) of genetics and genetic risk. Participants’ EMs were grounded in highly contextualized narratives that only partially overlapped with biomedical models. While higher education levels should be associated with predominately knowledge-based EM of genetic risk, this study shows that even in well-educated populations cultural factors can dominate. Study findings reveal gaps in how this sample of young adults obtains, processes, and understands genetic/genomic concepts. Future studies should assess how individuals with low GL and GN obtain and process genetics and genetic risk information and incorporate this information into health decision making. Future work should also address the interaction of communication between health educators, providers, and genetic counselors, to increase patient understanding of genetic risk. PMID:27376052

  5. Estimating classification images with generalized linear and additive models.

    PubMed

    Knoblauch, Kenneth; Maloney, Laurence T

    2008-12-22

    Conventional approaches to modeling classification image data can be described in terms of a standard linear model (LM). We show how the problem can be characterized as a Generalized Linear Model (GLM) with a Bernoulli distribution. We demonstrate via simulation that this approach is more accurate in estimating the underlying template in the absence of internal noise. With increasing internal noise, however, the advantage of the GLM over the LM decreases and GLM is no more accurate than LM. We then introduce the Generalized Additive Model (GAM), an extension of GLM that can be used to estimate smooth classification images adaptively. We show that this approach is more robust to the presence of internal noise, and finally, we demonstrate that GAM is readily adapted to estimation of higher order (nonlinear) classification images and to testing their significance.

  6. The system-resonance approach in modeling genetic structures.

    PubMed

    Petoukhov, Sergey V

    2016-01-01

    The founder of the theory of resonance in structural chemistry Linus Pauling established the importance of resonance patterns in organization of living systems. Any living organism is a great chorus of coordinated oscillatory processes. From the formal point of view, biological organism is an oscillatory system with a great number of degrees of freedom. Such systems are studied in the theory of oscillations using matrix mathematics of their resonance characteristics. This study is devoted to a new approach for modeling genetically inherited structures and processes in living organisms using mathematical tools of the theory of resonances. This approach reveals hidden relationships in a number of genetic phenomena and gives rise to a new class of bio-mathematical models, which contribute to a convergence of biology with physics and informatics. In addition some relationships of molecular-genetic ensembles with mathematics of noise-immunity coding of information in modern communications technology are shown. Perspectives of applications of the phenomena of vibrational mechanics for modeling in biology are discussed. PMID:26545937

  7. Genetically engineered livestock: ethical use for food and medical models.

    PubMed

    Garas, Lydia C; Murray, James D; Maga, Elizabeth A

    2015-01-01

    Recent advances in the production of genetically engineered (GE) livestock have resulted in a variety of new transgenic animals with desirable production and composition changes. GE animals have been generated to improve growth efficiency, food composition, and disease resistance in domesticated livestock species. GE animals are also used to produce pharmaceuticals and as medical models for human diseases. The potential use of these food animals for human consumption has prompted an intense debate about food safety and animal welfare concerns with the GE approach. Additionally, public perception and ethical concerns about their use have caused delays in establishing a clear and efficient regulatory approval process. Ethically, there are far-reaching implications of not using genetically engineered livestock, at a detriment to both producers and consumers, as use of this technology can improve both human and animal health and welfare.

  8. Additions to Mars Global Reference Atmospheric Model (MARS-GRAM)

    NASA Technical Reports Server (NTRS)

    Justus, C. G.; James, Bonnie

    1992-01-01

    Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification was also made which allows heights to go 'below' local terrain height and return 'realistic' pressure, density, and temperature, and not the surface values, as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local 'valley' areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch versions of Mars-GRAM are presented.

  9. Additions to Mars Global Reference Atmospheric Model (Mars-GRAM)

    NASA Technical Reports Server (NTRS)

    Justus, C. G.

    1991-01-01

    Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification has also been made which allows heights to go below local terrain height and return realistic pressure, density, and temperature (not the surface values) as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local valley areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch version of Mars-GRAM are presented.

  10. Evolvability of individual traits in a multivariate context: partitioning the additive genetic variance into common and specific components.

    PubMed

    McGuigan, Katrina; Blows, Mark W

    2010-07-01

    Genetic covariation among multiple traits will bias the direction of evolution. Although a trait's phenotypic context is crucial for understanding evolutionary constraints, the evolutionary potential of one (focal) trait, rather than the whole phenotype, is often of interest. The extent to which a focal trait can evolve independently depends on how much of the genetic variance in that trait is unique. Here, we present a hypothesis-testing framework for estimating the genetic variance in a focal trait that is independent of variance in other traits. We illustrate our analytical approach using two Drosophila bunnanda trait sets: a contact pheromone system comprised of cuticular hydrocarbons (CHCs), and wing shape, characterized by relative warps of vein position coordinates. Only 9% of the additive genetic variation in CHCs was trait specific, suggesting individual traits are unlikely to evolve independently. In contrast, most (72%) of the additive genetic variance in wing shape was trait specific, suggesting relative warp representations of wing shape could evolve independently. The identification of genetic variance in focal traits that is independent of other traits provides a way of studying the evolvability of individual traits within the broader context of the multivariate phenotype.

  11. Genetic variation and prediction of additive and nonadditive genetic effects for six carcass traits in an Angus-Brahman multibreed herd.

    PubMed

    Elzo, M A; West, R L; Johnson, D D; Wakeman, D L

    1998-07-01

    Estimates of covariances and sire expected progeny differences of additive and nonadditive genetic effects for six carcass traits were obtained using records from 486 straightbred and crossbred steers from 121 sires born between 1989 and 1995 in the Angus-Brahman multibreed herd of the University of Florida. Steers were slaughtered at a similar carcass composition end point. Covariances were estimated by REML procedures, using a generalized expectation-maximization algorithm applied to multibreed populations. Straightbred and crossbred estimates of heritabilities and additive genetic correlations were within ranges found in the literature for steers slaughtered on an age- or weight-constant basis for hot carcass weight, longissimus muscle area, and shear force but equal to or less than the lower bound of these ranges for fat-related traits. Maximum values of interactibilities (i.e., ratios of nonadditive variances to phenotypic variances in the F1) and nonadditive genetic correlations were smaller than heritabilities and additive genetic correlations in straightbreds and crossbred groups. Sire additive and total direct genetic predictions for longissimus muscle area, marbling, and shear force tended to decrease with the fraction of Brahman alleles, whereas those for hot carcass weight and fat thickness over the longissimus were higher, and those for kidney fat were lower in straightbreds and F1 than in other crossbred groups. Nonadditive genetic predictions were similar across sire groups of all Angus and Brahman fractions. These results suggest that slaughtering steers on a similar carcass composition basis reduces variability of fat-related traits while retaining variability for non-fat-related traits comparable to slaughtering steers on a similar age or weight basis. Selection for carcass traits within desirable (narrow) ranges and slaughter of steers at similar compositional end point seems to be a good combination to help produce meat products of consistent

  12. Genetic variation and prediction of additive and nonadditive genetic effects for six carcass traits in an Angus-Brahman multibreed herd.

    PubMed

    Elzo, M A; West, R L; Johnson, D D; Wakeman, D L

    1998-07-01

    Estimates of covariances and sire expected progeny differences of additive and nonadditive genetic effects for six carcass traits were obtained using records from 486 straightbred and crossbred steers from 121 sires born between 1989 and 1995 in the Angus-Brahman multibreed herd of the University of Florida. Steers were slaughtered at a similar carcass composition end point. Covariances were estimated by REML procedures, using a generalized expectation-maximization algorithm applied to multibreed populations. Straightbred and crossbred estimates of heritabilities and additive genetic correlations were within ranges found in the literature for steers slaughtered on an age- or weight-constant basis for hot carcass weight, longissimus muscle area, and shear force but equal to or less than the lower bound of these ranges for fat-related traits. Maximum values of interactibilities (i.e., ratios of nonadditive variances to phenotypic variances in the F1) and nonadditive genetic correlations were smaller than heritabilities and additive genetic correlations in straightbreds and crossbred groups. Sire additive and total direct genetic predictions for longissimus muscle area, marbling, and shear force tended to decrease with the fraction of Brahman alleles, whereas those for hot carcass weight and fat thickness over the longissimus were higher, and those for kidney fat were lower in straightbreds and F1 than in other crossbred groups. Nonadditive genetic predictions were similar across sire groups of all Angus and Brahman fractions. These results suggest that slaughtering steers on a similar carcass composition basis reduces variability of fat-related traits while retaining variability for non-fat-related traits comparable to slaughtering steers on a similar age or weight basis. Selection for carcass traits within desirable (narrow) ranges and slaughter of steers at similar compositional end point seems to be a good combination to help produce meat products of consistent

  13. Genetic predisposition to coronary heart disease and stroke using an additive genetic risk score: a population-based study in Greece

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Objective: To determine the extent to which the risk for incident coronary heart disease (CHD) increases in relation to a genetic risk score (GRS) that additively integrates the influence of high-risk alleles in nine documented single nucleotide polymorphisms (SNPs) for CHD, and to examine whether t...

  14. Genetic transformation of the model green alga Chlamydomonas reinhardtii.

    PubMed

    Neupert, Juliane; Shao, Ning; Lu, Yinghong; Bock, Ralph

    2012-01-01

    Over the past three decades, the single-celled green alga Chlamydomonas reinhardtii has become an invaluable model organism in plant biology and an attractive production host in biotechnology. The genetic transformation of Chlamydomonas is relatively simple and efficient, but achieving high expression levels of foreign genes has remained challenging. Here, we provide working protocols for algal cultivation and transformation as well as for selection and analysis of transgenic algal clones. We focus on two commonly used transformation methods for Chlamydomonas: glass bead-assisted transformation and particle gun-mediated (biolistic) transformation. In addition, we describe available tools for promoting efficient transgene expression and highlight important considerations for designing transformation vectors.

  15. Backbone Additivity in the Transfer Model of Protein Solvation

    SciTech Connect

    Hu, Char Y.; Kokubo, Hironori; Lynch, Gillian C.; Bolen, D Wayne; Pettitt, Bernard M.

    2010-05-01

    The transfer model implying additivity of the peptide backbone free energy of transfer is computationally tested. Molecular dynamics simulations are used to determine the extent of change in transfer free energy (ΔGtr) with increase in chain length of oligoglycine with capped end groups. Solvation free energies of oligoglycine models of varying lengths in pure water and in the osmolyte solutions, 2M urea and 2M trimethylamine N-oxide (TMAO), were calculated from simulations of all atom models, and ΔGtr values for peptide backbone transfer from water to the osmolyte solutions were determined. The results show that the transfer free energies change linearly with increasing chain length, demonstrating the principle of additivity, and provide values in reasonable agreement with experiment. The peptide backbone transfer free energy contributions arise from van der Waals interactions in the case of transfer to urea, but from electrostatics on transfer to TMAO solution. The simulations used here allow for the calculation of the solvation and transfer free energy of longer oligoglycine models to be evaluated than is currently possible through experiment. The peptide backbone unit computed transfer free energy of –54 cal/mol/Mcompares quite favorably with –43 cal/mol/M determined experimentally.

  16. Perceptions of Latinas on the Traditional Prenatal Genetic Counseling Model.

    PubMed

    Thompson, Stephanie; Noblin, Sarah Jane; Lemons, Jennifer; Peterson, Susan K; Carreno, Carlos; Harbison, Andrea

    2015-08-01

    The traditional genetic counseling model encompasses an individualized counseling session that includes the presentation of information about genes, chromosomes, personalized risk assessment, and genetic testing and screening options. Counselors are challenged to balance the provision of enough basic genetic information to ensure clients' understanding of the genetic condition in question with a personalized discussion of what this information means to them. This study explored the perceptions Latinas have about prenatal genetic counseling sessions and aimed to determine if they had preferences about the delivery of care. Data were collected through focus groups and one-on-one, semi-structured interviews of 25 Spanish speaking Latinas who received genetic counseling during their current pregnancy. We implemented grounded theory to evaluate participant responses, and were able to identify common emergent themes. Several themes were identified including an overall satisfaction with their prenatal genetic counseling appointment, desire for a healthy baby, peace of mind following their appointment, lack of desire for invasive testing, and faith in God. Several participants stated a preference for group genetic counseling over the traditional individual genetic counseling model. Our data indicate that Latinas value the information presented at prenatal genetic counseling appointments despite disinterest in pursuing genetic testing or screening and suggest that group prenatal genetic counseling may be an effective alternative to the traditional genetic counseling model in the Latina population. PMID:25475921

  17. Perceptions of Latinas on the Traditional Prenatal Genetic Counseling Model.

    PubMed

    Thompson, Stephanie; Noblin, Sarah Jane; Lemons, Jennifer; Peterson, Susan K; Carreno, Carlos; Harbison, Andrea

    2015-08-01

    The traditional genetic counseling model encompasses an individualized counseling session that includes the presentation of information about genes, chromosomes, personalized risk assessment, and genetic testing and screening options. Counselors are challenged to balance the provision of enough basic genetic information to ensure clients' understanding of the genetic condition in question with a personalized discussion of what this information means to them. This study explored the perceptions Latinas have about prenatal genetic counseling sessions and aimed to determine if they had preferences about the delivery of care. Data were collected through focus groups and one-on-one, semi-structured interviews of 25 Spanish speaking Latinas who received genetic counseling during their current pregnancy. We implemented grounded theory to evaluate participant responses, and were able to identify common emergent themes. Several themes were identified including an overall satisfaction with their prenatal genetic counseling appointment, desire for a healthy baby, peace of mind following their appointment, lack of desire for invasive testing, and faith in God. Several participants stated a preference for group genetic counseling over the traditional individual genetic counseling model. Our data indicate that Latinas value the information presented at prenatal genetic counseling appointments despite disinterest in pursuing genetic testing or screening and suggest that group prenatal genetic counseling may be an effective alternative to the traditional genetic counseling model in the Latina population.

  18. Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

    NASA Technical Reports Server (NTRS)

    Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

    2015-01-01

    The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition

  19. Genetic Algorithm Approaches to Prebiobiotic Chemistry Modeling

    NASA Technical Reports Server (NTRS)

    Lohn, Jason; Colombano, Silvano

    1997-01-01

    We model an artificial chemistry comprised of interacting polymers by specifying two initial conditions: a distribution of polymers and a fixed set of reversible catalytic reactions. A genetic algorithm is used to find a set of reactions that exhibit a desired dynamical behavior. Such a technique is useful because it allows an investigator to determine whether a specific pattern of dynamics can be produced, and if it can, the reaction network found can be then analyzed. We present our results in the context of studying simplified chemical dynamics in theorized protocells - hypothesized precursors of the first living organisms. Our results show that given a small sample of plausible protocell reaction dynamics, catalytic reaction sets can be found. We present cases where this is not possible and also analyze the evolved reaction sets.

  20. Competitive speciation in quantitative genetic models.

    PubMed

    Drossel, B; Mckane, A

    2000-06-01

    We study sympatric speciation due to competition in an environment with a broad distribution of resources. We assume that the trait under selection is a quantitative trait, and that mating is assortative with respect to this trait. Our model alternates selection according to Lotka-Volterra-type competition equations, with reproduction using the ideas of quantitative genetics. The recurrence relations defined by these equations are studied numerically and analytically. We find that when a population enters a new environment, with a broad distribution of unexploited food sources, the population distribution broadens under a variety of conditions, with peaks at the edge of the distribution indicating the formation of subpopulations. After a long enough time period, the population can split into several subpopulations with little gene flow between them. PMID:10816369

  1. Genetic models of poljes in Sicily

    NASA Astrophysics Data System (ADS)

    Di Maggio, Cipriano; Madonia, Giuliana; Vattano, Marco; De Waele, Jo

    2016-04-01

    Geomorphological and geological studies have been carried out to contribute to the recognition of controlling causes and to the definition of genetic models for poljes of Sicily. A polje is a kilometric closed depression developed mainly on karst rocks, with a conspicuously flat and alluviated bottom affected by intermittent flooding. A polje is usually characterised by relatively steep slopes enclosing an almost perfectly horizontal floor, caused by lateral solution planation related to flooding events. The origin of a polje is due to dissolution of the land surface, although geological structure generally influences its genesis. These large depressions are often elongated according to the direction of main faults, in consequence of a control due to tectonics or to differential erosion. The performed researches have shown the existence of at least seven poljes located along the north-western (chain zone) and the southern (deformed foredeep zone) areas of Sicily. These large karst depressions are developed on Mesozoic limestone/dolomitic rocks within the chain zone and on Messinian gypsum rocks within the deformed foredeep zone. They are up to 4 km in length, can reach surfaces of 3-8 km2 and are around hundred metres deep, with steep slopes and a flat bottom. Generally, they are open, occasionally active depressions and their genesis seems to be strongly controlled by structure. In particular, the studied poljes occur in two different geological/geomorphological settings: a) in graben-like tectonic depressions, where important fault slopes/scarps border the flat bottom; b) in complex depressions controlled by structure, where wide fault line slopes/scarps or large inclined degraded structural surfaces mark the poljes. Finally, landscape analysis leads to the proposition of two main genetic models in which the development of poljes is primarily due to tectonics or differential erosion followed by dissolution.

  2. The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance.

    PubMed

    Forsberg, Simon K G; Andreatta, Matthew E; Huang, Xin-Yuan; Danku, John; Salt, David E; Carlborg, Örjan

    2015-11-01

    Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or "missing heritability". Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

  3. The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

    PubMed Central

    Forsberg, Simon K. G.; Andreatta, Matthew E.; Huang, Xin-Yuan; Danku, John; Salt, David E.; Carlborg, Örjan

    2015-01-01

    Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations. PMID:26599497

  4. Sensitivity analysis of geometric errors in additive manufacturing medical models.

    PubMed

    Pinto, Jose Miguel; Arrieta, Cristobal; Andia, Marcelo E; Uribe, Sergio; Ramos-Grez, Jorge; Vargas, Alex; Irarrazaval, Pablo; Tejos, Cristian

    2015-03-01

    Additive manufacturing (AM) models are used in medical applications for surgical planning, prosthesis design and teaching. For these applications, the accuracy of the AM models is essential. Unfortunately, this accuracy is compromised due to errors introduced by each of the building steps: image acquisition, segmentation, triangulation, printing and infiltration. However, the contribution of each step to the final error remains unclear. We performed a sensitivity analysis comparing errors obtained from a reference with those obtained modifying parameters of each building step. Our analysis considered global indexes to evaluate the overall error, and local indexes to show how this error is distributed along the surface of the AM models. Our results show that the standard building process tends to overestimate the AM models, i.e. models are larger than the original structures. They also show that the triangulation resolution and the segmentation threshold are critical factors, and that the errors are concentrated at regions with high curvatures. Errors could be reduced choosing better triangulation and printing resolutions, but there is an important need for modifying some of the standard building processes, particularly the segmentation algorithms.

  5. Addition Table of Colours: Additive and Subtractive Mixtures Described Using a Single Reasoning Model

    ERIC Educational Resources Information Center

    Mota, A. R.; Lopes dos Santos, J. M. B.

    2014-01-01

    Students' misconceptions concerning colour phenomena and the apparent complexity of the underlying concepts--due to the different domains of knowledge involved--make its teaching very difficult. We have developed and tested a teaching device, the addition table of colours (ATC), that encompasses additive and subtractive mixtures in a single…

  6. Experimental Population Genetics in the Introductory Genetics Laboratory Using "Drosophila" as a Model Organism

    ERIC Educational Resources Information Center

    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…

  7. A Study of Additive Noise Model for Robust Speech Recognition

    NASA Astrophysics Data System (ADS)

    Awatade, Manisha H.

    2011-12-01

    A model of how speech amplitude spectra are affected by additive noise is studied. Acoustic features are extracted based on the noise robust parts of speech spectra without losing discriminative information. An existing two non-linear processing methods, harmonic demodulation and spectral peak-to-valley ratio locking, are designed to minimize mismatch between clean and noisy speech features. Previously studied methods, including peak isolation [1], do not require noise estimation and are effective in dealing with both stationary and non-stationary noise.

  8. Additive Manufacturing of Medical Models--Applications in Rhinology.

    PubMed

    Raos, Pero; Klapan, Ivica; Galeta, Tomislav

    2015-09-01

    In the paper we are introducing guidelines and suggestions for use of 3D image processing SW in head pathology diagnostic and procedures for obtaining physical medical model by additive manufacturing/rapid prototyping techniques, bearing in mind the improvement of surgery performance, its maximum security and faster postoperative recovery of patients. This approach has been verified in two case reports. In the treatment we used intelligent classifier-schemes for abnormal patterns using computer-based system for 3D-virtual and endoscopic assistance in rhinology, with appropriate visualization of anatomy and pathology within the nose, paranasal sinuses, and scull base area.

  9. A Tri-part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning About Authentic Genetics Dilemmas

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

    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 features of a reasoning task may influence how students apply content knowledge as they generate and support arguments. Understanding how students apply content knowledge to reason about authentic and complex issues is important for considering instructional practices that best support student thinking and reasoning. In this conceptual report, we present a tri-part model for genetics literacy that embodies the relationships between content knowledge use, argumentation quality, and the role of situational features in reasoning to support genetics literacy. Using illustrative examples from an interview study with early career undergraduate students majoring in the biological sciences and late career undergraduate students majoring in genetics, we provide insights into undergraduate student reasoning about complex genetics issues and discuss implications for teaching and learning. We further discuss the need for research about how the tri-part model of genetics literacy can be used to explore students' thinking and reasoning abilities in genetics.

  10. Multiscale Modeling of Powder Bed-Based Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Markl, Matthias; Körner, Carolin

    2016-07-01

    Powder bed fusion processes are additive manufacturing technologies that are expected to induce the third industrial revolution. Components are built up layer by layer in a powder bed by selectively melting confined areas, according to sliced 3D model data. This technique allows for manufacturing of highly complex geometries hardly machinable with conventional technologies. However, the underlying physical phenomena are sparsely understood and difficult to observe during processing. Therefore, an intensive and expensive trial-and-error principle is applied to produce components with the desired dimensional accuracy, material characteristics, and mechanical properties. This review presents numerical modeling approaches on multiple length scales and timescales to describe different aspects of powder bed fusion processes. In combination with tailored experiments, the numerical results enlarge the process understanding of the underlying physical mechanisms and support the development of suitable process strategies and component topologies.

  11. Multiscale Modeling of Powder Bed–Based Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Markl, Matthias; Körner, Carolin

    2016-07-01

    Powder bed fusion processes are additive manufacturing technologies that are expected to induce the third industrial revolution. Components are built up layer by layer in a powder bed by selectively melting confined areas, according to sliced 3D model data. This technique allows for manufacturing of highly complex geometries hardly machinable with conventional technologies. However, the underlying physical phenomena are sparsely understood and difficult to observe during processing. Therefore, an intensive and expensive trial-and-error principle is applied to produce components with the desired dimensional accuracy, material characteristics, and mechanical properties. This review presents numerical modeling approaches on multiple length scales and timescales to describe different aspects of powder bed fusion processes. In combination with tailored experiments, the numerical results enlarge the process understanding of the underlying physical mechanisms and support the development of suitable process strategies and component topologies.

  12. Genetically modified mouse models in studies of luteinising hormone action.

    PubMed

    Huhtaniemi, Ilpo; Ahtiainen, Petteri; Pakarainen, Tomi; Rulli, Susana B; Zhang, Fu-Ping; Poutanen, Matti

    2006-06-27

    Numerous genetically modified mouse models have recently been developed for the study of the pituitary-gonadal interactions. They include spontaneous or engineered knockouts (KO) of the gonadotrophin-releasing hormone (GnRH) and its receptor, the gonadotrophin common-alpha(Calpha), luteinising hormone (LH) beta and follicle-stimulating hormone (FSH) beta subunits, and the two gonadotrophin receptors (R), LHR and FSHR. In addition, there are also transgenic (TG) mice overexpressing gonadotrophin subunits and producing supraphysiological levels of these hormones. These models have offered relevant phenocopies for similar mutations in humans and to a great extent expanded our knowledge on normal and pathological functions of the hypothalamic-pituitary-gonadal (HPG) axis. The purpose of this article is to review some of our recent findings on two such mouse models, the LHR KO mouse (LuRKO), and the hCG overexpressing TG mouse (hCG+).

  13. WATEQ3 geochemical model: thermodynamic data for several additional solids

    SciTech Connect

    Krupka, K.M.; Jenne, E.A.

    1982-09-01

    Geochemical models such as WATEQ3 can be used to model the concentrations of water-soluble pollutants that may result from the disposal of nuclear waste and retorted oil shale. However, for a model to competently deal with these water-soluble pollutants, an adequate thermodynamic data base must be provided that includes elements identified as important in modeling these pollutants. To this end, several minerals and related solid phases were identified that were absent from the thermodynamic data base of WATEQ3. In this study, the thermodynamic data for the identified solids were compiled and selected from several published tabulations of thermodynamic data. For these solids, an accepted Gibbs free energy of formation, ..delta..G/sup 0//sub f,298/, was selected for each solid phase based on the recentness of the tabulated data and on considerations of internal consistency with respect to both the published tabulations and the existing data in WATEQ3. For those solids not included in these published tabulations, Gibbs free energies of formation were calculated from published solubility data (e.g., lepidocrocite), or were estimated (e.g., nontronite) using a free-energy summation method described by Mattigod and Sposito (1978). The accepted or estimated free energies were then combined with internally consistent, ancillary thermodynamic data to calculate equilibrium constants for the hydrolysis reactions of these minerals and related solid phases. Including these values in the WATEQ3 data base increased the competency of this geochemical model in applications associated with the disposal of nuclear waste and retorted oil shale. Additional minerals and related solid phases that need to be added to the solubility submodel will be identified as modeling applications continue in these two programs.

  14. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  15. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... increased risk for breast cancer, including individuals with BRCA1 or BRCA2 gene mutations. B is 33 years... reimbursement. Following an established policy, the plan asks B for evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for...

  16. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  17. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  18. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  19. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... increased risk for breast cancer, including individuals with BRCA1 or BRCA2 gene mutations. B is 33 years... reimbursement. Following an established policy, the plan asks B for evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for...

  20. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  1. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... increased risk for breast cancer, including individuals with BRCA1 or BRCA2 gene mutations. B is 33 years... reimbursement. Following an established policy, the plan asks B for evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for...

  2. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  3. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  4. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... increased risk for breast cancer, including individuals with BRCA1 or BRCA2 gene mutations. B is 33 years... reimbursement. Following an established policy, the plan asks B for evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for...

  5. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... increased risk for breast cancer, including individuals with BRCA1 or BRCA2 gene mutations. B is 33 years... reimbursement. Following an established policy, the plan asks B for evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for...

  6. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  7. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  8. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 40, or at age 30 for those with increased risk for breast cancer, including individuals with BRCA1 or... evidence of increased risk of breast cancer, such as the results of a genetic test or a family history of breast cancer, before the claim for the mammogram is paid. This policy is applied uniformly to...

  9. Comprehensive Neurocognitive Endophenotyping Strategies for Mouse Models of Genetic Disorders

    PubMed Central

    Hunsaker, Michael R.

    2012-01-01

    There is a need for refinement of the current behavioral phenotyping methods for mouse models of genetic disorders. The current approach is to perform a behavioral screen using standardized tasks to define a broad phenotype of the model. This phenotype is then compared to what is known concerning the disorder being modeled. The weakness inherent in this approach is twofold: First, the tasks that make up these standard behavioral screens do not model specific behaviors associated with a given genetic mutation but rather phenotypes affected in various genetic disorders; secondly, these behavioral tasks are insufficiently sensitive to identify subtle phenotypes. An alternate phenotyping strategy is to determine the core behavioral phenotypes of the genetic disorder being studied and develop behavioral tasks to evaluate specific hypotheses concerning the behavioral consequences of the genetic mutation. This approach emphasizes direct comparisons between the mouse and human that facilitate the development of neurobehavioral biomarkers or quantitative outcome measures for studies of genetic disorders across species. PMID:22266125

  10. Genetic Models of Sensorimotor Gating: Relevance to Neuropsychiatric Disorders

    PubMed Central

    Weber, Martin; Geyer, Mark A.

    2012-01-01

    Sensorimotor gating, or the ability of a sensory event to suppress a motor response, can be measured operationally via prepulse inhibition (PPI) of the startle response. PPI is deficient in schizophrenia patients as well as other neuropsychiatric disorders, can be measured across species, and has been used widely as a translational tool in preclinical neuropharmacological and genetic research. First developed to assess drug effects in pharmacological and developmental models, PPI has become one of the standard behavioral measures in genetic models of schizophrenia and other neuropsychiatric disorders that exhibit PPI deficits. In this chapter we review the literature on genetic models of sensorimotor gating and discuss the utility of PPI as a tool in phenotyping mutant mouse models. We highlight the approaches to genetic mouse models of neuropsychiatric disease, discuss some of the important caveats to these approaches, and provide a comprehensive table covering the more recent genetic models that have evaluated PPI. PMID:22367921

  11. [Critical of the additive model of the randomized controlled trial].

    PubMed

    Boussageon, Rémy; Gueyffier, François; Bejan-Angoulvant, Theodora; Felden-Dominiak, Géraldine

    2008-01-01

    Randomized, double-blind, placebo-controlled clinical trials are currently the best way to demonstrate the clinical effectiveness of drugs. Its methodology relies on the method of difference (John Stuart Mill), through which the observed difference between two groups (drug vs placebo) can be attributed to the pharmacological effect of the drug being tested. However, this additive model can be questioned in the event of statistical interactions between the pharmacological and the placebo effects. Evidence in different domains has shown that the placebo effect can influence the effect of the active principle. This article evaluates the methodological, clinical and epistemological consequences of this phenomenon. Topics treated include extrapolating results, accounting for heterogeneous results, demonstrating the existence of several factors in the placebo effect, the necessity to take these factors into account for given symptoms or pathologies, as well as the problem of the "specific" effect.

  12. No Additional Prognostic Value of Genetic Information in the Prediction of Vascular Events after Cerebral Ischemia of Arterial Origin: The PROMISe Study

    PubMed Central

    Achterberg, Sefanja; Kappelle, L. Jaap; de Bakker, Paul I. W.; Traylor, Matthew; Algra, Ale

    2015-01-01

    Background Patients who have suffered from cerebral ischemia have a high risk of recurrent vascular events. Predictive models based on classical risk factors typically have limited prognostic value. Given that cerebral ischemia has a heritable component, genetic information might improve performance of these risk models. Our aim was to develop and compare two models: one containing traditional vascular risk factors, the other also including genetic information. Methods and Results We studied 1020 patients with cerebral ischemia and genotyped them with the Illumina Immunochip. Median follow-up time was 6.5 years; the annual incidence of new ischemic events (primary outcome, n=198) was 3.0%. The prognostic model based on classical vascular risk factors had an area under the receiver operating characteristics curve (AUC-ROC) of 0.65 (95% confidence interval 0.61-0.69). When we added a genetic risk score based on prioritized SNPs from a genome-wide association study of ischemic stroke (using summary statistics from the METASTROKE study which included 12389 cases and 62004 controls), the AUC-ROC remained the same. Similar results were found for the secondary outcome ischemic stroke. Conclusions We found no additional value of genetic information in a prognostic model for the risk of ischemic events in patients with cerebral ischemia of arterial origin. This is consistent with a complex, polygenic architecture, where many genes of weak effect likely act in concert to influence the heritable risk of an individual to develop (recurrent) vascular events. At present, genetic information cannot help clinicians to distinguish patients at high risk for recurrent vascular events. PMID:25906364

  13. Genetic and Environmental Bases of Reading and Spelling: A Unified Genetic Dual Route Model

    ERIC Educational Resources Information Center

    Bates, Timothy C.; Castles, Anne; Luciano, Michelle; Wright, Margaret J.; Coltheart, Max; Martin, Nicholas G.

    2007-01-01

    We develop and test a dual-route model of genetic effects on reading aloud and spelling, based on irregular and non-word reading and spelling performance assessed in 1382 monozygotic and dizygotic twins. As in earlier research, most of the variance in reading was due to genetic effects. However, there were three more specific conclusions: the…

  14. A Developmental-Genetic Model of Alcoholism: Implications for Genetic Research.

    ERIC Educational Resources Information Center

    Devor, Eric J.

    1994-01-01

    Research for biological-genetic markers of alcoholism is discussed in context of a multifactorial, heterogeneous, developmental model. Suggested that strategies used in linkage and association studies will require modification. Also suggested several extant associations of genetic markers represent true secondary interactive phenomena that alter…

  15. Functional-mixed effects models for candidate genetic mapping in imaging genetic studies.

    PubMed

    Lin, Ja-An; Zhu, Hongtu; Mihye, Ahn; Sun, Wei; Ibrahim, Joseph G

    2014-12-01

    The aim of this paper is to develop a functional-mixed effects modeling (FMEM) framework for the joint analysis of high-dimensional imaging data in a large number of locations (called voxels) of a three-dimensional volume with a set of genetic markers and clinical covariates. Our FMEM is extremely useful for efficiently carrying out the candidate gene approaches in imaging genetic studies. FMEM consists of two novel components including a mixed effects model for modeling nonlinear genetic effects on imaging phenotypes by introducing the genetic random effects at each voxel and a jumping surface model for modeling the variance components of the genetic random effects and fixed effects as piecewise smooth functions of the voxels. Moreover, FMEM naturally accommodates the correlation structure of the genetic markers at each voxel, while the jumping surface model explicitly incorporates the intrinsically spatial smoothness of the imaging data. We propose a novel two-stage adaptive smoothing procedure to spatially estimate the piecewise smooth functions, particularly the irregular functional genetic variance components, while preserving their edges among different piecewise-smooth regions. We develop weighted likelihood ratio tests and derive their exact approximations to test the effect of the genetic markers across voxels. Simulation studies show that FMEM significantly outperforms voxel-wise approaches in terms of higher sensitivity and specificity to identify regions of interest for carrying out candidate genetic mapping in imaging genetic studies. Finally, FMEM is used to identify brain regions affected by three candidate genes including CR1, CD2AP, and PICALM, thereby hoping to shed light on the pathological interactions between these candidate genes and brain structure and function.

  16. A Genetic Model for Neurodevelopmental Disease

    PubMed Central

    Coe, Bradley P.; Girirajan, Santhosh; Eichler, Evan E.

    2012-01-01

    The genetic basis of neurodevelopmental and neuropsychiatric diseases has been advanced by the discovery of large and recurrent copy number variants significantly enriched in cases when compared to controls. The pattern of this variation strongly implies that rare variants contribute significantly to neurological disease; that different genes will be responsible for similar diseases in different families; and that the same “primary” genetic lesions can result in a different disease outcome depending potentially on the genetic background. Next-generation sequencing technologies are beginning to broaden the spectrum of disease-causing variation and provide specificity by pinpointing both genes and pathways for future diagnostics and therapeutics. PMID:22560351

  17. Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

    PubMed

    Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

    2014-01-01

    We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

  18. Additive genetic variation for tolerance to estrogen pollution in natural populations of Alpine whitefish (Coregonus sp., Salmonidae)

    PubMed Central

    Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus

    2014-01-01

    The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution. PMID:25553069

  19. Additive genetic variation for tolerance to estrogen pollution in natural populations of Alpine whitefish (Coregonus sp., Salmonidae).

    PubMed

    Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus

    2014-11-01

    The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution. PMID:25553069

  20. Toward Developing Genetic Algorithms to Aid in Critical Infrastructure Modeling

    SciTech Connect

    Not Available

    2007-05-01

    Today’s society relies upon an array of complex national and international infrastructure networks such as transportation, telecommunication, financial and energy. Understanding these interdependencies is necessary in order to protect our critical infrastructure. The Critical Infrastructure Modeling System, CIMS©, examines the interrelationships between infrastructure networks. CIMS© development is sponsored by the National Security Division at the Idaho National Laboratory (INL) in its ongoing mission for providing critical infrastructure protection and preparedness. A genetic algorithm (GA) is an optimization technique based on Darwin’s theory of evolution. A GA can be coupled with CIMS© to search for optimum ways to protect infrastructure assets. This includes identifying optimum assets to enforce or protect, testing the addition of or change to infrastructure before implementation, or finding the optimum response to an emergency for response planning. This paper describes the addition of a GA to infrastructure modeling for infrastructure planning. It first introduces the CIMS© infrastructure modeling software used as the modeling engine to support the GA. Next, the GA techniques and parameters are defined. Then a test scenario illustrates the integration with CIMS© and the preliminary results.

  1. Genetic patchiness in European eel adults evidenced by molecular genetics and population dynamics modelling.

    PubMed

    Pujolar, José Martin; Bevacqua, Daniele; Andrello, Marco; Capoccioni, Fabrizio; Ciccotti, Eleonora; De Leo, Giulio A; Zane, Lorenzo

    2011-02-01

    Disentangling the demographic processes that determine the genetic structure of a given species is a fundamental question in conservation and management. In the present study, the population structure of the European eel was examined with a multidisciplinary approach combining the fields of molecular genetics and population dynamics modelling. First, we analyzed a total of 346 adult specimens of known age collected in three separate sample sites using a large panel of 22 EST-linked microsatellite loci. Second, we developed a European eel-specific model to unravel the demographic mechanisms that can produce the level of genetic differentiation estimated by molecular markers. This is the first study that reveals a pattern of genetic patchiness in maturing adults of the European eel. A highly significant genetic differentiation was observed among samples that did not follow an Isolation-by-Distance or Isolation-by-Time pattern. The observation of genetic patchiness in adults is likely to result from a limited parental contribution to each spawning event as suggested by our modelling approach. The value of genetic differentiation found is predicted by the model when reproduction occurs in a limited number of spawning events isolated from each other in time or space, with an average of 130-375 breeders in each spawning event. Unpredictability in spawning success may have important consequences for the life-history evolution of the European eel, including a bet-hedging strategy (distributing reproductive efforts over time) which could in turn guarantee successful reproduction of some adults.

  2. GWAS of human bitter taste perception identifies new loci and reveals additional complexity of bitter taste genetics

    PubMed Central

    Ledda, Mirko; Kutalik, Zoltán; Souza Destito, Maria C.; Souza, Milena M.; Cirillo, Cintia A.; Zamboni, Amabilene; Martin, Nathalie; Morya, Edgard; Sameshima, Koichi; Beckmann, Jacques S.; le Coutre, Johannes; Bergmann, Sven; Genick, Ulrich K.

    2014-01-01

    Human perception of bitterness displays pronounced interindividual variation. This phenotypic variation is mirrored by equally pronounced genetic variation in the family of bitter taste receptor genes. To better understand the effects of common genetic variations on human bitter taste perception, we conducted a genome-wide association study on a discovery panel of 504 subjects and a validation panel of 104 subjects from the general population of São Paulo in Brazil. Correction for general taste-sensitivity allowed us to identify a SNP in the cluster of bitter taste receptors on chr12 (10.88– 11.24 Mb, build 36.1) significantly associated (best SNP: rs2708377, P = 5.31 × 10−13, r2 = 8.9%, β = −0.12, s.e. = 0.016) with the perceived bitterness of caffeine. This association overlaps with—but is statistically distinct from—the previously identified SNP rs10772420 influencing the perception of quinine bitterness that falls in the same bitter taste cluster. We replicated this association to quinine perception (P = 4.97 × 10−37, r2 = 23.2%, β = 0.25, s.e. = 0.020) and additionally found the effect of this genetic locus to be concentration specific with a strong impact on the perception of low, but no impact on the perception of high concentrations of quinine. Our study, thus, furthers our understanding of the complex genetic architecture of bitter taste perception. PMID:23966204

  3. GWAS of human bitter taste perception identifies new loci and reveals additional complexity of bitter taste genetics.

    PubMed

    Ledda, Mirko; Kutalik, Zoltán; Souza Destito, Maria C; Souza, Milena M; Cirillo, Cintia A; Zamboni, Amabilene; Martin, Nathalie; Morya, Edgard; Sameshima, Koichi; Beckmann, Jacques S; le Coutre, Johannes; Bergmann, Sven; Genick, Ulrich K

    2014-01-01

    Human perception of bitterness displays pronounced interindividual variation. This phenotypic variation is mirrored by equally pronounced genetic variation in the family of bitter taste receptor genes. To better understand the effects of common genetic variations on human bitter taste perception, we conducted a genome-wide association study on a discovery panel of 504 subjects and a validation panel of 104 subjects from the general population of São Paulo in Brazil. Correction for general taste-sensitivity allowed us to identify a SNP in the cluster of bitter taste receptors on chr12 (10.88- 11.24 Mb, build 36.1) significantly associated (best SNP: rs2708377, P = 5.31 × 10(-13), r(2) = 8.9%, β = -0.12, s.e. = 0.016) with the perceived bitterness of caffeine. This association overlaps with-but is statistically distinct from-the previously identified SNP rs10772420 influencing the perception of quinine bitterness that falls in the same bitter taste cluster. We replicated this association to quinine perception (P = 4.97 × 10(-37), r(2) = 23.2%, β = 0.25, s.e. = 0.020) and additionally found the effect of this genetic locus to be concentration specific with a strong impact on the perception of low, but no impact on the perception of high concentrations of quinine. Our study, thus, furthers our understanding of the complex genetic architecture of bitter taste perception.

  4. Genetically engineered humanized mouse models for preclinical antibody studies.

    PubMed

    Proetzel, Gabriele; Wiles, Michael V; Roopenian, Derry C

    2014-04-01

    The use of genetic engineering has vastly improved our capabilities to create animal models relevant in preclinical research. With the recent advances in gene-editing technologies, it is now possible to very rapidly create highly tunable mouse models as needs arise. Here, we provide an overview of genetic engineering methods, as well as the development of humanized neonatal Fc receptor (FcRn) models and their use for monoclonal antibody in vivo studies.

  5. Cognitive Modelling and the Behaviour Genetics of Reading

    ERIC Educational Resources Information Center

    Castles, Anne; Bates, Timothy; Coltheart, Max; Luciano, Michelle; Martin, Nicholas G.

    2006-01-01

    While it is well known that reading is highly heritable, less has been understood about the bases of these genetic influences. In this paper, we review the research that we have been conducting in recent years to examine genetic and environmental influences on the particular reading processes specified in the "dual-route" cognitive model of…

  6. Developing robotic behavior using a genetic programming model

    SciTech Connect

    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.

  7. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

    PubMed Central

    Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

    2015-01-01

    A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre’s polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre’s polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from −0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from −0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits. PMID:26323397

  8. Percolation model with an additional source of disorder

    NASA Astrophysics Data System (ADS)

    Kundu, Sumanta; Manna, S. S.

    2016-06-01

    The ranges of transmission of the mobiles in a mobile ad hoc network are not uniform in reality. They are affected by the temperature fluctuation in air, obstruction due to the solid objects, even the humidity difference in the environment, etc. How the varying range of transmission of the individual active elements affects the global connectivity in the network may be an important practical question to ask. Here a model of percolation phenomena, with an additional source of disorder, is introduced for a theoretical understanding of this problem. As in ordinary percolation, sites of a square lattice are occupied randomly with probability p . Each occupied site is then assigned a circular disk of random value R for its radius. A bond is defined to be occupied if and only if the radii R1 and R2 of the disks centered at the ends satisfy a certain predefined condition. In a very general formulation, one divides the R1-R2 plane into two regions by an arbitrary closed curve. One defines a point within one region as representing an occupied bond; otherwise it is a vacant bond. The study of three different rules under this general formulation indicates that the percolation threshold always varies continuously. This threshold has two limiting values, one is pc(sq) , the percolation threshold for the ordinary site percolation on the square lattice, and the other is unity. The approach of the percolation threshold to its limiting values are characterized by two exponents. In a special case, all lattice sites are occupied by disks of random radii R ∈{0 ,R0} and a percolation transition is observed with R0 as the control variable, similar to the site occupation probability.

  9. Percolation model with an additional source of disorder.

    PubMed

    Kundu, Sumanta; Manna, S S

    2016-06-01

    The ranges of transmission of the mobiles in a mobile ad hoc network are not uniform in reality. They are affected by the temperature fluctuation in air, obstruction due to the solid objects, even the humidity difference in the environment, etc. How the varying range of transmission of the individual active elements affects the global connectivity in the network may be an important practical question to ask. Here a model of percolation phenomena, with an additional source of disorder, is introduced for a theoretical understanding of this problem. As in ordinary percolation, sites of a square lattice are occupied randomly with probability p. Each occupied site is then assigned a circular disk of random value R for its radius. A bond is defined to be occupied if and only if the radii R_{1} and R_{2} of the disks centered at the ends satisfy a certain predefined condition. In a very general formulation, one divides the R_{1}-R_{2} plane into two regions by an arbitrary closed curve. One defines a point within one region as representing an occupied bond; otherwise it is a vacant bond. The study of three different rules under this general formulation indicates that the percolation threshold always varies continuously. This threshold has two limiting values, one is p_{c}(sq), the percolation threshold for the ordinary site percolation on the square lattice, and the other is unity. The approach of the percolation threshold to its limiting values are characterized by two exponents. In a special case, all lattice sites are occupied by disks of random radii R∈{0,R_{0}} and a percolation transition is observed with R_{0} as the control variable, similar to the site occupation probability.

  10. Percolation model with an additional source of disorder.

    PubMed

    Kundu, Sumanta; Manna, S S

    2016-06-01

    The ranges of transmission of the mobiles in a mobile ad hoc network are not uniform in reality. They are affected by the temperature fluctuation in air, obstruction due to the solid objects, even the humidity difference in the environment, etc. How the varying range of transmission of the individual active elements affects the global connectivity in the network may be an important practical question to ask. Here a model of percolation phenomena, with an additional source of disorder, is introduced for a theoretical understanding of this problem. As in ordinary percolation, sites of a square lattice are occupied randomly with probability p. Each occupied site is then assigned a circular disk of random value R for its radius. A bond is defined to be occupied if and only if the radii R_{1} and R_{2} of the disks centered at the ends satisfy a certain predefined condition. In a very general formulation, one divides the R_{1}-R_{2} plane into two regions by an arbitrary closed curve. One defines a point within one region as representing an occupied bond; otherwise it is a vacant bond. The study of three different rules under this general formulation indicates that the percolation threshold always varies continuously. This threshold has two limiting values, one is p_{c}(sq), the percolation threshold for the ordinary site percolation on the square lattice, and the other is unity. The approach of the percolation threshold to its limiting values are characterized by two exponents. In a special case, all lattice sites are occupied by disks of random radii R∈{0,R_{0}} and a percolation transition is observed with R_{0} as the control variable, similar to the site occupation probability. PMID:27415234

  11. Genetic and Epigenetic Changes in Oilseed Rape (Brassica napus L.) Extracted from Intergeneric Allopolyploid and Additions with Orychophragmus

    PubMed Central

    Gautam, Mayank; Dang, Yanwei; Ge, Xianhong; Shao, Yujiao; Li, Zaiyun

    2016-01-01

    Allopolyploidization with the merger of the genomes from different species has been shown to be associated with genetic and epigenetic changes. But the maintenance of such alterations related to one parental species after the genome is extracted from the allopolyploid remains to be detected. In this study, the genome of Brassica napus L. (2n = 38, genomes AACC) was extracted from its intergeneric allohexaploid (2n = 62, genomes AACCOO) with another crucifer Orychophragmus violaceus (2n = 24, genome OO), by backcrossing and development of alien addition lines. B. napus-type plants identified in the self-pollinated progenies of nine monosomic additions were analyzed by the methods of amplified fragment length polymorphism, sequence-specific amplified polymorphism, and methylation-sensitive amplified polymorphism. They showed modifications to certain extents in genomic components (loss and gain of DNA segments and transposons, introgression of alien DNA segments) and DNA methylation, compared with B. napus donor. The significant differences in the changes between the B. napus types extracted from these additions likely resulted from the different effects of individual alien chromosomes. Particularly, the additions which harbored the O. violaceus chromosome carrying dominant rRNA genes over those of B. napus tended to result in the development of plants which showed fewer changes, suggesting a role of the expression levels of alien rRNA genes in genomic stability. These results provided new cues for the genetic alterations in one parental genome that are maintained even after the genome becomes independent. PMID:27148282

  12. Genetic and Epigenetic Changes in Oilseed Rape (Brassica napus L.) Extracted from Intergeneric Allopolyploid and Additions with Orychophragmus.

    PubMed

    Gautam, Mayank; Dang, Yanwei; Ge, Xianhong; Shao, Yujiao; Li, Zaiyun

    2016-01-01

    Allopolyploidization with the merger of the genomes from different species has been shown to be associated with genetic and epigenetic changes. But the maintenance of such alterations related to one parental species after the genome is extracted from the allopolyploid remains to be detected. In this study, the genome of Brassica napus L. (2n = 38, genomes AACC) was extracted from its intergeneric allohexaploid (2n = 62, genomes AACCOO) with another crucifer Orychophragmus violaceus (2n = 24, genome OO), by backcrossing and development of alien addition lines. B. napus-type plants identified in the self-pollinated progenies of nine monosomic additions were analyzed by the methods of amplified fragment length polymorphism, sequence-specific amplified polymorphism, and methylation-sensitive amplified polymorphism. They showed modifications to certain extents in genomic components (loss and gain of DNA segments and transposons, introgression of alien DNA segments) and DNA methylation, compared with B. napus donor. The significant differences in the changes between the B. napus types extracted from these additions likely resulted from the different effects of individual alien chromosomes. Particularly, the additions which harbored the O. violaceus chromosome carrying dominant rRNA genes over those of B. napus tended to result in the development of plants which showed fewer changes, suggesting a role of the expression levels of alien rRNA genes in genomic stability. These results provided new cues for the genetic alterations in one parental genome that are maintained even after the genome becomes independent. PMID:27148282

  13. Genetically Engineered Mouse Models for Studying Inflammatory Bowel Disease

    PubMed Central

    Mizoguchi, Atsushi; Takeuchi, Takahito; Himuro, Hidetomo; Okada, Toshiyuki; Mizoguchi, Emiko

    2015-01-01

    Inflammatory bowel disease (IBD) is a chronic intestinal inflammatory condition that is mediated by very complex mechanisms controlled by genetic, immune, and environmental factors. More than 74 kinds of genetically engineered mouse strains have been established since 1993 for studying IBD. Although mouse models cannot fully reflect human IBD, they have provided significant contributions for not only understanding the mechanism, but also developing new therapeutic means for IBD. Indeed, 20 kinds of genetically engineered mouse models carry the susceptibility genes identified in human IBD, and the functions of some other IBD susceptibility genes have also been dissected out using mouse models. Cutting-edge technologies such as cell-specific and inducible knockout systems, which were recently employed to mouse IBD models, have further enhanced the ability of investigators to provide important and unexpected rationales for developing new therapeutic strategies for IBD. In this review article, we briefly introduce 74 kinds of genetically engineered mouse models that spontaneously develop intestinal inflammation. PMID:26387641

  14. Additional records of metazoan parasites from Caribbean marine mammals, including genetically identified anisakid nematodes.

    PubMed

    Colón-Llavina, Marlene M; Mignucci-Giannoni, Antonio A; Mattiucci, Simonetta; Paoletti, Michela; Nascetti, Giuseppe; Williams, Ernest H

    2009-10-01

    Studies of marine mammal parasites in the Caribbean are scarce. An assessment for marine mammal endo- and ectoparasites from Puerto Rico and the Virgin Islands, but extending to other areas of the Caribbean, was conducted between 1989 and 1994. The present study complements the latter and enhances identification of anisakid nematodes using molecular markers. Parasites were collected from 59 carcasses of stranded cetaceans and manatees from 1994 to 2006, including Globicephala macrorhynchus, Kogia breviceps, Kogia sima, Lagenodelphis hosei, Mesoplodon densirostris, Peponocephala electra, Stenella longirostris, Steno bredanensis, Trichechus manatus. Tursiops truncatus, and Ziphius cavirostris. Sixteen species of endoparasitic helminthes were morphologically identified, including two species of acanthocephalans (Bolbosoma capitatum, Bolbosoma vasculosum), nine species of nematodes (Anisakis sp., Anisakis brevispiculata, Anisakis paggiae, Anisakis simplex, Anisakis typica, Anisakis ziphidarium, Crassicauda anthonyi, Heterocheilus tunicatus, Pseudoterranova ceticola), two species of cestodes (Monorygma grimaldi, Phyllobothrium delphini), and three species of trematodes (Chiorchis groschafti, Pulmonicola cochleotrema, Monoligerum blairi). The nematodes belonging to the genus Anisakis recovered in some stranded animals were genetically identified to species level based on their sequence analysis of mitochondrial DNA (629 bp of mtDNA cox 2). A total of five new host records and six new geographic records are presented. PMID:19582477

  15. Additional records of metazoan parasites from Caribbean marine mammals, including genetically identified anisakid nematodes.

    PubMed

    Colón-Llavina, Marlene M; Mignucci-Giannoni, Antonio A; Mattiucci, Simonetta; Paoletti, Michela; Nascetti, Giuseppe; Williams, Ernest H

    2009-10-01

    Studies of marine mammal parasites in the Caribbean are scarce. An assessment for marine mammal endo- and ectoparasites from Puerto Rico and the Virgin Islands, but extending to other areas of the Caribbean, was conducted between 1989 and 1994. The present study complements the latter and enhances identification of anisakid nematodes using molecular markers. Parasites were collected from 59 carcasses of stranded cetaceans and manatees from 1994 to 2006, including Globicephala macrorhynchus, Kogia breviceps, Kogia sima, Lagenodelphis hosei, Mesoplodon densirostris, Peponocephala electra, Stenella longirostris, Steno bredanensis, Trichechus manatus. Tursiops truncatus, and Ziphius cavirostris. Sixteen species of endoparasitic helminthes were morphologically identified, including two species of acanthocephalans (Bolbosoma capitatum, Bolbosoma vasculosum), nine species of nematodes (Anisakis sp., Anisakis brevispiculata, Anisakis paggiae, Anisakis simplex, Anisakis typica, Anisakis ziphidarium, Crassicauda anthonyi, Heterocheilus tunicatus, Pseudoterranova ceticola), two species of cestodes (Monorygma grimaldi, Phyllobothrium delphini), and three species of trematodes (Chiorchis groschafti, Pulmonicola cochleotrema, Monoligerum blairi). The nematodes belonging to the genus Anisakis recovered in some stranded animals were genetically identified to species level based on their sequence analysis of mitochondrial DNA (629 bp of mtDNA cox 2). A total of five new host records and six new geographic records are presented.

  16. Hyperbolic value addition and general models of animal choice.

    PubMed

    Mazur, J E

    2001-01-01

    Three mathematical models of choice--the contextual-choice model (R. Grace, 1994), delay-reduction theory (N. Squires & E. Fantino, 1971), and a new model called the hyperbolic value-added model--were compared in their ability to predict the results from a wide variety of experiments with animal subjects. When supplied with 2 or 3 free parameters, all 3 models made fairly accurate predictions for a large set of experiments that used concurrent-chain procedures. One advantage of the hyperbolic value-added model is that it is derived from a simpler model that makes accurate predictions for many experiments using discrete-trial adjusting-delay procedures. Some results favor the hyperbolic value-added model and delay-reduction theory over the contextual-choice model, but more data are needed from choice situations for which the models make distinctly different predictions.

  17. Statistical Inference of Biometrical Genetic Model With Cultural Transmission.

    PubMed

    Guo, Xiaobo; Ji, Tian; Wang, Xueqin; Zhang, Heping; Zhong, Shouqiang

    2013-01-01

    Twin and family studies establish the foundation for studying the genetic, environmental and cultural transmission effects for phenotypes. In this work, we make use of the well established statistical methods and theory for mixed models to assess cultural transmission in twin and family studies. Specifically, we address two critical yet poorly understood issues: the model identifiability in assessing cultural transmission for twin and family data and the biases in the estimates when sub-models are used. We apply our models and theory to two real data sets. A simulation is conducted to verify the bias in the estimates of genetic effects when the working model is a sub-model. PMID:24660046

  18. Genetic prerequisites for additive or synergistic actions of 5-fluorocytosine and fluconazole in baker's yeast.

    PubMed

    Paluszynski, John P; Klassen, Roland; Meinhardt, Friedhelm

    2008-10-01

    During applications of 5-fluorocytosine (5FC) and fluconazole (FLC), additive or synergistic action may even occur when primary resistance to 5FC is established. Here, we analysed conjoint drug action in Saccharomyces cerevisiae strains deficient in genes known to be essential for 5FC or FLC function. Despite clear primary resistance, residual 5FC activity and additive 5FC+FLC action in cells lacking cytosine permease (Fcy2p) or uracil phosphoribosyl transferase (Fur1p) were detected. In contrast, Deltafcy1 mutants, lacking cytosine deaminase, became entirely resistant to 5FC, concomitantly losing 5FC+FLC additivity. Disruption of the orotate phosphoribosyltransferase gene (URA5) in the wild-type led to low-level 5FC tolerance, while an alternative orotate phosphoribosyltransferase, encoded by URA10, contributed to 5FC toxicity only in the Deltaura5 background. Remarkably, combination of Deltaura5 and Deltafur1 resulted in complete 5FC resistance. Thus, yeast orotate phosphoribosyltransferases are involved in 5FC metabolism. Similarly, disruption of the ergosterol Delta(5,6)-desaturase-encoding gene ERG3 resulted only in partial resistance to FLC, and concomitantly a synergistic effect with 5FC became evident. Full resistance to FLC occurred in Deltaerg3 Deltaerg11 double mutants and, simultaneously, synergism or even an additive effect with FLC and 5FC was no longer discernible. Since the majority of spontaneously occurring resistant yeast clones displayed residual sensitivity to either 5FC or FLC and those strains responded to combined drug treatment in a predictable manner, careful resistance profiling based on the findings reported here may help to address yeast infections by combined application of antimycotic compounds.

  19. Behavioral phenotypes of genetic mouse models of autism.

    PubMed

    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.

  20. Behavioral phenotypes of genetic mouse models of autism

    PubMed Central

    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. PMID:26403076

  1. Testing Departure from Additivity in Tukey’s Model using Shrinkage: Application to a Longitudinal Setting

    PubMed Central

    Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A.; Park, Sung Kyun; Kardia, Sharon L.R.; Allison, Matthew A.; Vokonas, Pantel S.; Chen, Jinbo; Diez-Roux, Ana V.

    2014-01-01

    While there has been extensive research developing gene-environment interaction (GEI) methods in case-control studies, little attention has been given to sparse and efficient modeling of GEI in longitudinal studies. In a two-way table for GEI with rows and columns as categorical variables, a conventional saturated interaction model involves estimation of a specific parameter for each cell, with constraints ensuring identifiability. The estimates are unbiased but are potentially inefficient because the number of parameters to be estimated can grow quickly with increasing categories of row/column factors. On the other hand, Tukey’s one degree of freedom (df) model for non-additivity treats the interaction term as a scaled product of row and column main effects. Due to the parsimonious form of interaction, the interaction estimate leads to enhanced efficiency and the corresponding test could lead to increased power. Unfortunately, Tukey’s model gives biased estimates and low power if the model is misspecified. When screening multiple GEIs where each genetic and environmental marker may exhibit a distinct interaction pattern, a robust estimator for interaction is important for GEI detection. We propose a shrinkage estimator for interaction effects that combines estimates from both Tukey’s and saturated interaction models and use the corresponding Wald test for testing interaction in a longitudinal setting. The proposed estimator is robust to misspecification of interaction structure. We illustrate the proposed methods using two longitudinal studies — the Normative Aging Study and the Multi-Ethnic Study of Atherosclerosis. PMID:25112650

  2. Genetic association studies in complex disease: disentangling additional predisposing loci from associated neutral loci using a constrained - permutation approach.

    PubMed

    Spijker, G T; Nolte, I M; Jansen, R C; Te Meerman, G J

    2005-01-01

    In the process of genetically mapping a complex disease, the question may arise whether a certain polymorphism is the only causal variant in a region. A number of methods can answer this question, but unfortunately these methods are optimal for bi-allelic loci only. We wanted to develop a method that is more suited for multi-allelic loci, such as microsatellite markers. We propose the Additional Disease Loci Test (ADLT): the alleles at an additional locus are permuted within the subsample of haplotypes that have identical alleles at the predisposing locus. The hypothesis being tested is, whether the predisposing locus is the sole factor predisposing to the trait that is in LD with the additional locus under study. We applied ADLT to simulated datasets and a published dataset on Type 1 Diabetes, genotyped for microsatellite markers in the HLA-region. The method showed the expected number of false-positive results in the absence of additional loci, but proved to be more powerful than existing methods in the presence of additional disease loci. ADLT was especially superior in datasets with less LD or with multiple predisposing alleles. We conclude that the ADLT can be useful in identifying additional disease loci.

  3. Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

    PubMed

    Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

    2015-03-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

  4. Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

    PubMed Central

    Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

    2015-01-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

  5. Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

    PubMed

    Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

    2015-03-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

  6. Using Generalized Additive Models to Analyze Single-Case Designs

    ERIC Educational Resources Information Center

    Shadish, William; Sullivan, Kristynn

    2013-01-01

    Many analyses for single-case designs (SCDs)--including nearly all the effect size indicators-- currently assume no trend in the data. Regression and multilevel models allow for trend, but usually test only linear trend and have no principled way of knowing if higher order trends should be represented in the model. This paper shows how Generalized…

  7. How Pupils Use a Model for Abstract Concepts in Genetics

    ERIC Educational Resources Information Center

    Venville, Grady; Donovan, Jenny

    2008-01-01

    The purpose of this research was to explore the way pupils of different age groups use a model to understand abstract concepts in genetics. Pupils from early childhood to late adolescence were taught about genes and DNA using an analogical model (the wool model) during their regular biology classes. Changing conceptual understandings of the…

  8. Additive genetic and heterosis effects in crosses among cattle breeds of British, European and Zebu origin.

    PubMed

    Peacock, F M; Koger, M; Olson, T A; Crockett, J R

    1981-05-01

    Breed and heterosis effects for maternal and calf components for weaning traits were measured in the progeny of Angus (A), Brahman (B) and Charolais (C) sires mated to A, B, C and reciprocal AB, AC and BC dams. Additive breed effects for the calf component for weaning weight were -3.0 +/- 3.2, -26.6 +/- 3.1 and 29.6 +/- 3.3 kg for A, B and C, respectively. Corresponding maternal breed effects were -1.7 +/- 2.4, 7.8 +/- 2.3 and -6.1 +/- 2.6 kilograms. Heterosis effects on weaning weight for the calf component were 21.2 +/- 3.6 for AB, 1.4 +/- 3.7 for AC and 16.5 +/- 3.4 for BC crosses, while heterosis levels for the maternal component were 28.9 +/- 2.7 for AB, 16.5 +/- 3.2 for AC and 18.7 +/- 2.9 kg for BC dams. The corresponding estimates for condition scores tended to parallel those for weaning weight. Approximate relative production efficiency rates were computed for the different mating groups as (calf weight divided by cow weight) x weaning rate. These values were .34 for purebred matings, .36 for purebred dams raising F1 calves, .40 for F1 cows raising backcross calves and .43 for F1 dams raising three breed crossbred calves.

  9. Additive Manufacturing of Anatomical Models from Computed Tomography Scan Data.

    PubMed

    Gür, Y

    2014-12-01

    The purpose of the study presented here was to investigate the manufacturability of human anatomical models from Computed Tomography (CT) scan data via a 3D desktop printer which uses fused deposition modelling (FDM) technology. First, Digital Imaging and Communications in Medicine (DICOM) CT scan data were converted to 3D Standard Triangle Language (STL) format by using In Vaselius digital imaging program. Once this STL file is obtained, a 3D physical version of the anatomical model can be fabricated by a desktop 3D FDM printer. As a case study, a patient's skull CT scan data was considered, and a tangible version of the skull was manufactured by a 3D FDM desktop printer. During the 3D printing process, the skull was built using acrylonitrile-butadiene-styrene (ABS) co-polymer plastic. The printed model showed that the 3D FDM printing technology is able to fabricate anatomical models with high accuracy. As a result, the skull model can be used for preoperative surgical planning, medical training activities, implant design and simulation to show the potential of the FDM technology in medical field. It will also improve communication between medical stuff and patients. Current result indicates that a 3D desktop printer which uses FDM technology can be used to obtain accurate anatomical models.

  10. Additive Manufacturing of Anatomical Models from Computed Tomography Scan Data.

    PubMed

    Gür, Y

    2014-12-01

    The purpose of the study presented here was to investigate the manufacturability of human anatomical models from Computed Tomography (CT) scan data via a 3D desktop printer which uses fused deposition modelling (FDM) technology. First, Digital Imaging and Communications in Medicine (DICOM) CT scan data were converted to 3D Standard Triangle Language (STL) format by using In Vaselius digital imaging program. Once this STL file is obtained, a 3D physical version of the anatomical model can be fabricated by a desktop 3D FDM printer. As a case study, a patient's skull CT scan data was considered, and a tangible version of the skull was manufactured by a 3D FDM desktop printer. During the 3D printing process, the skull was built using acrylonitrile-butadiene-styrene (ABS) co-polymer plastic. The printed model showed that the 3D FDM printing technology is able to fabricate anatomical models with high accuracy. As a result, the skull model can be used for preoperative surgical planning, medical training activities, implant design and simulation to show the potential of the FDM technology in medical field. It will also improve communication between medical stuff and patients. Current result indicates that a 3D desktop printer which uses FDM technology can be used to obtain accurate anatomical models. PMID:26336695

  11. How much additional model complexity do the use of catchment hydrological signatures, additional data and expert knowledge warrant?

    NASA Astrophysics Data System (ADS)

    Hrachowitz, M.; Fovet, O.; RUIZ, L.; Gascuel-odoux, C.; Savenije, H.

    2013-12-01

    In the frequent absence of sufficient suitable data to constrain hydrological models, it is not uncommon to represent catchments at a range of scales by lumped model set-ups. Although process heterogeneity can average out on the catchment scale to generate simple catchment integrated responses whose general flow features can frequently be reproduced by lumped models, these models often fail to get details of the flow pattern as well as catchment internal dynamics, such as groundwater level changes, right to a sufficient degree, resulting in considerable predictive uncertainty. Traditionally, models are constrained by only one or two objectives functions, which does not warrant more than a handful of parameters to avoid elevated predictive uncertainty, thereby preventing more complex model set-ups accounting for increased process heterogeneity. In this study it was tested how much additional process heterogeneity is warranted in models when optimizing the model calibration strategy, using additional data and expert knowledge. Long-term timeseries of flow and groundwater levels for small nested experimental catchments in French Brittany with considerable differences in geology, topography and flow regime were used in this study to test which degree of model process heterogeneity is warranted with increased availability of information. In a first step, as a benchmark, the system was treated as one lumped entity and the model was trained based only on its ability to reproduce the hydrograph. Although it was found that the overall modelled flow generally reflects the observed flow response quite well, the internal system dynamics could not be reproduced. In further steps the complexity of this model was gradually increased, first by adding a separate riparian reservoir to the lumped set-up and then by a semi-distributed set-up, allowing for independent, parallel model structures, representing the contrasting nested catchments. Although calibration performance increased

  12. Genetic testing and mental health: the model of Huntington disease.

    PubMed

    Williams, J K; Schutte, D L

    2000-01-01

    Genetic aspects of mental health disorders are being identified through human genome and family research. Gene discovery makes diagnostic and presymptomatic testing possible. The discovery of a gene mutation for Huntington Disease (HD) enables at-risk persons to request presymptomatic genetic testing. When HD genetic testing is offered through HD testing centers, a multi-visit protocol is followed in which education and counseling are provided for persons considering the option to have HD gene testing. A case study illustrates the clinical and ethical issues regarding privacy and disclosure as well as the personal and family consequences of gene mutation knowledge. Analysis of the impact of genetic knowledge on persons being tested for HD provides a model for the integration of emerging genetic information into mental health nursing practice for other mental health disorders.

  13. Biological detoxification of the mycotoxin deoxynivalenol and its use in genetically engineered crops and feed additives.

    PubMed

    Karlovsky, Petr

    2011-08-01

    Deoxynivalenol (DON) is the major mycotoxin produced by Fusarium fungi in grains. Food and feed contaminated with DON pose a health risk to humans and livestock. The risk can be reduced by enzymatic detoxification. Complete mineralization of DON by microbial cultures has rarely been observed and the activities turned out to be unstable. The detoxification of DON by reactions targeting its epoxide group or hydroxyl on carbon 3 is more feasible. Microbial strains that de-epoxidize DON under anaerobic conditions have been isolated from animal digestive system. Feed additives claimed to de-epoxidize trichothecenes enzymatically are on the market but their efficacy has been disputed. A new detoxification pathway leading to 3-oxo-DON and 3-epi-DON was discovered in taxonomically unrelated soil bacteria from three continents; the enzymes involved remain to be identified. Arabidopsis, tobacco, wheat, barley, and rice were engineered to acetylate DON on carbon 3. In wheat expressing DON acetylation activity, the increase in resistance against Fusarium head blight was only moderate. The Tri101 gene from Fusarium sporotrichioides was used; Fusarium graminearum enzyme which possesses higher activity towards DON would presumably be a better choice. Glycosylation of trichothecenes occurs in plants, contributing to the resistance of wheat to F. graminearum infection. Marker-assisted selection based on the trichothecene-3-O-glucosyltransferase gene can be used in breeding for resistance. Fungal acetyltransferases and plant glucosyltransferases targeting carbon 3 of trichothecenes remain promising candidates for engineering resistance against Fusarium head blight. Bacterial enzymes catalyzing oxidation, epimerization, and less likely de-epoxidation of DON may extend this list in future.

  14. Addition of Diffusion Model to MELCOR and Comparison with Data

    SciTech Connect

    Brad Merrill; Richard Moore; Chang Oh

    2004-06-01

    A chemical diffusion model was incorporated into the thermal-hydraulics package of the MELCOR Severe Accident code (Reference 1) for analyzing air ingress events for a very high temperature gas-cooled reactor.

  15. Tetrahymena as a Unicellular Model Eukaryote: Genetic and Genomic Tools.

    PubMed

    Ruehle, Marisa D; Orias, Eduardo; Pearson, Chad G

    2016-06-01

    Tetrahymena thermophila is a ciliate model organism whose study has led to important discoveries and insights into both conserved and divergent biological processes. In this review, we describe the tools for the use of Tetrahymena as a model eukaryote, including an overview of its life cycle, orientation to its evolutionary roots, and methodological approaches to forward and reverse genetics. Recent genomic tools have expanded Tetrahymena's utility as a genetic model system. With the unique advantages that Tetrahymena provide, we argue that it will continue to be a model organism of choice.

  16. Tetrahymena as a Unicellular Model Eukaryote: Genetic and Genomic Tools.

    PubMed

    Ruehle, Marisa D; Orias, Eduardo; Pearson, Chad G

    2016-06-01

    Tetrahymena thermophila is a ciliate model organism whose study has led to important discoveries and insights into both conserved and divergent biological processes. In this review, we describe the tools for the use of Tetrahymena as a model eukaryote, including an overview of its life cycle, orientation to its evolutionary roots, and methodological approaches to forward and reverse genetics. Recent genomic tools have expanded Tetrahymena's utility as a genetic model system. With the unique advantages that Tetrahymena provide, we argue that it will continue to be a model organism of choice. PMID:27270699

  17. Non-additive model for specific heat of electrons

    NASA Astrophysics Data System (ADS)

    Anselmo, D. H. A. L.; Vasconcelos, M. S.; Silva, R.; Mello, V. D.

    2016-10-01

    By using non-additive Tsallis entropy we demonstrate numerically that one-dimensional quasicrystals, whose energy spectra are multifractal Cantor sets, are characterized by an entropic parameter, and calculate the electronic specific heat, where we consider a non-additive entropy Sq. In our method we consider an energy spectra calculated using the one-dimensional tight binding Schrödinger equation, and their bands (or levels) are scaled onto the [ 0 , 1 ] interval. The Tsallis' formalism is applied to the energy spectra of Fibonacci and double-period one-dimensional quasiperiodic lattices. We analytically obtain an expression for the specific heat that we consider to be more appropriate to calculate this quantity in those quasiperiodic structures.

  18. Genetic algorithms for modelling and optimisation

    NASA Astrophysics Data System (ADS)

    McCall, John

    2005-12-01

    Genetic algorithms (GAs) are a heuristic search and optimisation technique inspired by natural evolution. They have been successfully applied to a wide range of real-world problems of significant complexity. This paper is intended as an introduction to GAs aimed at immunologists and mathematicians interested in immunology. We describe how to construct a GA and the main strands of GA theory before speculatively identifying possible applications of GAs to the study of immunology. An illustrative example of using a GA for a medical optimal control problem is provided. The paper also includes a brief account of the related area of artificial immune systems.

  19. Additional Research Needs to Support the GENII Biosphere Models

    SciTech Connect

    Napier, Bruce A.; Snyder, Sandra F.; Arimescu, Carmen

    2013-11-30

    In the course of evaluating the current parameter needs for the GENII Version 2 code (Snyder et al. 2013), areas of possible improvement for both the data and the underlying models have been identified. As the data review was implemented, PNNL staff identified areas where the models can be improved both to accommodate the locally significant pathways identified and also to incorporate newer models. The areas are general data needs for the existing models and improved formulations for the pathway models. It is recommended that priorities be set by NRC staff to guide selection of the most useful improvements in a cost-effective manner. Suggestions are made based on relatively easy and inexpensive changes, and longer-term more costly studies. In the short term, there are several improved model formulations that could be applied to the GENII suite of codes to make them more generally useful. • Implementation of the separation of the translocation and weathering processes • Implementation of an improved model for carbon-14 from non-atmospheric sources • Implementation of radon exposure pathways models • Development of a KML processor for the output report generator module data that are calculated on a grid that could be superimposed upon digital maps for easier presentation and display • Implementation of marine mammal models (manatees, seals, walrus, whales, etc.). Data needs in the longer term require extensive (and potentially expensive) research. Before picking any one radionuclide or food type, NRC staff should perform an in-house review of current and anticipated environmental analyses to select “dominant” radionuclides of interest to allow setting of cost-effective priorities for radionuclide- and pathway-specific research. These include • soil-to-plant uptake studies for oranges and other citrus fruits, and • Development of models for evaluation of radionuclide concentration in highly-processed foods such as oils and sugars. Finally, renewed

  20. Generalized population models and the nature of genetic drift.

    PubMed

    Der, Ricky; Epstein, Charles L; Plotkin, Joshua B

    2011-09-01

    The Wright-Fisher model of allele dynamics forms the basis for most theoretical and applied research in population genetics. Our understanding of genetic drift, and its role in suppressing the deterministic forces of Darwinian selection has relied on the specific form of sampling inherent to the Wright-Fisher model and its diffusion limit. Here we introduce and analyze a broad class of forward-time population models that share the same mean and variance as the Wright-Fisher model, but may otherwise differ. The proposed class unifies and further generalizes a number of population-genetic processes of recent interest, including the Λ and Cannings processes. Even though these models all have the same variance effective population size, they encode a rich diversity of alternative forms of genetic drift, with significant consequences for allele dynamics. We characterize in detail the behavior of standard population-genetic quantities across this family of generalized models. Some quantities, such as heterozygosity, remain unchanged; but others, such as neutral absorption times and fixation probabilities under selection, deviate by orders of magnitude from the Wright-Fisher model. We show that generalized population models can produce startling phenomena that differ qualitatively from classical behavior - such as assured fixation of a new mutant despite the presence of genetic drift. We derive the forward-time continuum limits of the generalized processes, analogous to Kimura's diffusion limit of the Wright-Fisher process, and we discuss their relationships to the Kingman and non-Kingman coalescents. Finally, we demonstrate that some non-diffusive, generalized models are more likely, in certain respects, than the Wright-Fisher model itself, given empirical data from Drosophila populations.

  1. The Ising model in physics and statistical genetics.

    PubMed

    Majewski, J; Li, H; Ott, J

    2001-10-01

    Interdisciplinary communication is becoming a crucial component of the present scientific environment. Theoretical models developed in diverse disciplines often may be successfully employed in solving seemingly unrelated problems that can be reduced to similar mathematical formulation. The Ising model has been proposed in statistical physics as a simplified model for analysis of magnetic interactions and structures of ferromagnetic substances. Here, we present an application of the one-dimensional, linear Ising model to affected-sib-pair (ASP) analysis in genetics. By analyzing simulated genetics data, we show that the simplified Ising model with only nearest-neighbor interactions between genetic markers has statistical properties comparable to much more complex algorithms from genetics analysis, such as those implemented in the Allegro and Mapmaker-Sibs programs. We also adapt the model to include epistatic interactions and to demonstrate its usefulness in detecting modifier loci with weak individual genetic contributions. A reanalysis of data on type 1 diabetes detects several susceptibility loci not previously found by other methods of analysis.

  2. C elegans: a model for exploring the genetics of fat storage.

    PubMed

    McKay, Renée M; McKay, James P; Avery, Leon; Graff, Jonathan M

    2003-01-01

    To gain insights into the genetic cascades that regulate fat biology, we evaluated C. elegans as an appropriate model organism. We generated worms that lack two transcription factors, SREBP and C/EBP, crucial for formation of mammalian fat. Worms deficient in either of these genes displayed a lipid-depleted phenotype-pale, skinny, larval-arrested worms that lack fat stores. On the basis of this phenotype, we used a reverse genetic screen to identify several additional genes that play a role in worm lipid storage. Two of the genes encode components of the mitochondrial respiratory chain (MRC). When the MRC was inhibited chemically in worms or in a mammalian adipocyte model, fat accumulation was markedly reduced. A third encodes lpd-3, whose homolog is also required for fat storage in a mammalian model. These data suggest that C. elegans is a genetically tractable model to study the mechanisms that underlie the biology of fat-storing tissues.

  3. The addition of algebraic turbulence modeling to program LAURA

    NASA Astrophysics Data System (ADS)

    Cheatwood, F. Mcneil; Thompson, R. A.

    1993-04-01

    The Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) is modified to allow the calculation of turbulent flows. This is accomplished using the Cebeci-Smith and Baldwin-Lomax eddy-viscosity models in conjunction with the thin-layer Navier-Stokes options of the program. Turbulent calculations can be performed for both perfect-gas and equilibrium flows. However, a requirement of the models is that the flow be attached. It is seen that for slender bodies, adequate resolution of the boundary-layer gradients may require more cells in the normal direction than a laminar solution, even when grid stretching is employed. Results for axisymmetric and three-dimensional flows are presented. Comparison with experimental data and other numerical results reveal generally good agreement, except in the regions of detached flow.

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

    PubMed

    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.

  5. Practical implications for genetic modeling in the genomics era

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...

  6. Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

    PubMed

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

    2015-11-22

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

  7. Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

    PubMed

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

    2015-11-22

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

  8. Hybrid Mice as Genetic Models of High Alcohol Consumption

    PubMed Central

    Ozburn, A. R.; Walker, D.; Ahmed, S.; Belknap, J. K.; Harris, R. A.

    2011-01-01

    We showed that F1 hybrid genotypes may provide a broader variety of ethanol drinking phenotypes than the inbred progenitor strains used to create the hybrids (Blednov et al. in Alcohol Clin Exp Res 29:1949–1958–2005). To extend this work, we characterized alcohol consumption as well as intake of other tastants (saccharin, quinine and sodium chloride) in five inbred strains of mice (FVB, SJL, B6, BUB, NZB) and in their reciprocal F1 hybrids with B6 (FVBxB6; B6xFVB; NZBxB6; B6xNZB; BUBxB6; B6xBUB; SJLxB6; B6xSJL). We also compared ethanol intake in these mice for several concentrations before and after two periods of abstinence. F1 hybrid mice derived from the crosses of B6 and FVB and also B6 and SJL drank higher levels of ethanol than their progenitor strains, demonstrating overdominance for two-bottle choice drinking test. The B6 and NZB hybrid showed additivity in two-bottle choice drinking, whereas the hybrid of B6 and BUB demonstrated full or complete dominance. Genealogical origin, as well as non-alcohol taste preferences (sodium chloride), predicted ethanol consumption. Mice derived from the crosses of B6 and FVB showed high sustained alcohol preference and the B6 and NZB hybrids showed reduced alcohol preference after periods of abstinence. These new genetic models offer some advantages over inbred strains because they provide high, sustained, alcohol intake, and should allow mapping of loci important for the genetic architecture of these traits. PMID:19798565

  9. A computational model for sex-specific genetic architecture of complex traits in humans: Implications for mapping pain sensitivity

    PubMed Central

    Wang, Chenguang; Cheng, Yun; Liu, Tian; Li, Qin; Fillingim, Roger B; Wallace, Margaret R; Staud, Roland; Kaplan, Lee; Wu, Rongling

    2008-01-01

    Understanding differences in the genetic architecture of complex traits between the two sexes has significant implications for evolutionary studies and clinical diagnosis. However, our knowledge about sex-specific genetic architecture is limited largely because of a lack of analytical models that can detect and quantify the effects of sex on the complexity of quantitative genetic variation. Here, we derived a statistical model for mapping DNA sequence variants that contribute to sex-specific differences in allele frequencies, linkage disequilibria, and additive and dominance genetic effects due to haplotype diversity. This model allows a genome-wide search for functional haplotypes and the estimation and test of haplotype by sex interactions and sex-specific heritability. The model, validated by simulation studies, was used to detect sex-specific functional haplotypes that encode a pain sensitivity trait in humans. The model could have important implications for mapping complex trait genes and studying the detailed genetic architecture of sex-specific differences. PMID:18416828

  10. Software reliability: Additional investigations into modeling with replicated experiments

    NASA Technical Reports Server (NTRS)

    Nagel, P. M.; Schotz, F. M.; Skirvan, J. A.

    1984-01-01

    The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

  11. [Improvement of genetics teaching using literature-based learning model].

    PubMed

    Liang, Liang; Shiqian, Liang; Hongyan, Qin; Yong, Ji; Hua, Han

    2015-06-01

    Genetics is one of the most important courses for undergraduate students majoring in life science. In recent years, new knowledge and technologies are continually updated with deeper understanding of life science. However, the teaching model of genetics is still based on theoretical instruction, which makes the abstract principles hard to understand by students and directly affects the teaching effect. Thus, exploring a new teaching model is necessary. We have carried out a new teaching model, literature-based learning, in the course on Microbial Genetics for undergraduate students majoring in biotechnology since 2010. Here we comprehensively analyzed the implementation and application value of this model including pre-course knowledge, how to choose professional literature, how to organize teaching process and the significance of developing this new teaching model for students and teachers. Our literature-based learning model reflects the combination of "cutting-edge" and "classic" and makes book knowledge easy to understand, which improves students' learning effect, stimulates their interests, expands their perspectives and develops their ability. This practice provides novel insight into exploring new teaching model of genetics and cultivating medical talents capable of doing both basic and clinical research in the "precision medicine" era.

  12. Genetic variance of tolerance and the toxicant threshold model.

    PubMed

    Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

    2012-04-01

    A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change.

  13. The modified ultrasound pattern sum score mUPSS as additional diagnostic tool for genetically distinct hereditary neuropathies.

    PubMed

    Grimm, Alexander; Rasenack, Maria; Athanasopoulou, Ioanna M; Dammeier, Nele Maria; Lipski, Christina; Wolking, Stefan; Vittore, Debora; Décard, Bernhard F; Axer, Hubertus

    2016-02-01

    The objective of this study is to evaluate the nerve ultrasound characteristics in genetically distinct inherited neuropathies, the value of the modified ultrasound pattern sum score (mUPSS) to differentiate between the subtypes and the correlation of ultrasound with nerve conduction studies (NCS), disease duration and severity. All patients underwent a standardized neurological examination, ultrasound, and NCS. In addition, genetic testing was performed. Consequently, mUPSS was applied, which is a sum-score of cross-sectional areas (CSA) at predefined anatomical points in different nerves. 31 patients were included (10xCharcot-Marie-Tooth (CMT)1a, 3xCMT1b, 3xCMTX, 9xCMT2, 6xHNPP [Hereditary neuropathy with liability to pressure palsies]). Generalized, homogeneous nerve enlargement and significantly increased UPS scores emphasized the diagnosis of demyelinating neuropathy, particularly CMT1a and CMT1b. The amount of enlargement did not depend on disease duration, symptom severity, height and weight. In CMTX the nerves were enlarged, as well, however, only in the roots and lower limbs, most prominent in men. In CMT2 no significant enlargement was detectable. In HNPP the CSA values were increased at entrapped sites, and not elsewhere. However, a distinction from CMT1, which also showed enlarged CSA values at entrapment sites, was only possible by calculating the entrapment ratios and entrapment score. The mUPSS allowed distinction between CMT1a (increased UPS scores, entrapment ratios <1.0) and HNPP (low UPS scores, entrapment ratios >1.4), while CMT1b and CMTX showed intermediate UPS types and entrapment ratios <1.0. Although based on few cases, ultrasound revealed consistent and homogeneous nerve alteration in certain inherited neuropathies. The modified UPSS is a quantitative tool, which may provide useful information for diagnosis, differentiation and follow-up evaluation in addition to NCS and molecular testing.

  14. A model for monitoring of Hsp90-buffered genetic variations

    NASA Astrophysics Data System (ADS)

    Kozeko, Liudmyla

    Genetic material of terrestrial organisms can be considerably injured by cosmic rays and UV-radiation in the space environment. Organisms onboard are also exposed to the entire complex of negative physical factors which can generate genetic variations and affect morphogenesis. However, species phenotypes must be robust to genetic variation, requiring "buffering" systems to ensure normal development. The molecular chaperone Hsp90 can serve as such "a buffer". It is important in the maturation and conformational regulation of a diverse set of signal transducers. The requirement of many principal regulatory proteins for Hsp90 renders entire metabolic pathways sensitive to impairment of its function. So inhibition of Hsp90 function can open cryptic genetic variations and produce morphological changes. In this paper, we present a model for monitoring of cryptic Hsp90-buffered genetic variations arising during exposure to space and spaceflight factors. This model has been developed with Arabidopsis thaliana seeds gathered in natural habitats with high anthropogenic pressure and wild type (Col-0) seeds subjected to negative influences (UV, heavy metals) experimentally. The phenotypic traits of early seedlings grown under reduction of Hsp90 activity were characterized to estimate Hsp90-buffered genetic variations. Geldanamycin was used as an inhibitor of Hsp90 function.

  15. Oxidative Stress in Genetic Mouse Models of Parkinson's Disease

    PubMed Central

    Varçin, Mustafa; Bentea, Eduard; Michotte, Yvette; Sarre, Sophie

    2012-01-01

    There is extensive evidence in Parkinson's disease of a link between oxidative stress and some of the monogenically inherited Parkinson's disease-associated genes. This paper focuses on the importance of this link and potential impact on neuronal function. Basic mechanisms of oxidative stress, the cellular antioxidant machinery, and the main sources of cellular oxidative stress are reviewed. Moreover, attention is given to the complex interaction between oxidative stress and other prominent pathogenic pathways in Parkinson's disease, such as mitochondrial dysfunction and neuroinflammation. Furthermore, an overview of the existing genetic mouse models of Parkinson's disease is given and the evidence of oxidative stress in these models highlighted. Taken into consideration the importance of ageing and environmental factors as a risk for developing Parkinson's disease, gene-environment interactions in genetically engineered mouse models of Parkinson's disease are also discussed, highlighting the role of oxidative damage in the interplay between genetic makeup, environmental stress, and ageing in Parkinson's disease. PMID:22829959

  16. Additional Developments in Atmosphere Revitalization Modeling and Simulation

    NASA Technical Reports Server (NTRS)

    Coker, Robert F.; Knox, James C.; Cummings, Ramona; Brooks, Thomas; Schunk, Richard G.; Gomez, Carlos

    2013-01-01

    NASA's Advanced Exploration Systems (AES) program is developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit. These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by evaluating structured sorbents, seeking more robust pelletized sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach. This paper describes the continuing development of atmosphere revitalization models and simulations in support of the Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project within the AES program.

  17. Additional Developments in Atmosphere Revitalization Modeling and Simulation

    NASA Technical Reports Server (NTRS)

    Coker, Robert F.; Knox, James C.; Cummings, Ramona; Brooks, Thomas; Schunk, Richard G.

    2013-01-01

    NASA's Advanced Exploration Systems (AES) program is developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit. These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by evaluating structured sorbents, seeking more robust pelletized sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach. This paper describes the continuing development of atmosphere revitalization models and simulations in support of the Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM)

  18. Model-free Estimation of Recent Genetic Relatedness

    PubMed Central

    Conomos, Matthew P.; Reiner, Alexander P.; Weir, Bruce S.; Thornton, Timothy A.

    2016-01-01

    Genealogical inference from genetic data is essential for a variety of applications in human genetics. In genome-wide and sequencing association studies, for example, accurate inference on both recent genetic relatedness, such as family structure, and more distant genetic relatedness, such as population structure, is necessary for protection against spurious associations. Distinguishing familial relatedness from population structure with genotype data, however, is difficult because both manifest as genetic similarity through the sharing of alleles. Existing approaches for inference on recent genetic relatedness have limitations in the presence of population structure, where they either (1) make strong and simplifying assumptions about population structure, which are often untenable, or (2) require correct specification of and appropriate reference population panels for the ancestries in the sample, which might be unknown or not well defined. Here, we propose PC-Relate, a model-free approach for estimating commonly used measures of recent genetic relatedness, such as kinship coefficients and IBD sharing probabilities, in the presence of unspecified structure. PC-Relate uses principal components calculated from genome-screen data to partition genetic correlations among sampled individuals due to the sharing of recent ancestors and more distant common ancestry into two separate components, without requiring specification of the ancestral populations or reference population panels. In simulation studies with population structure, including admixture, we demonstrate that PC-Relate provides accurate estimates of genetic relatedness and improved relationship classification over widely used approaches. We further demonstrate the utility of PC-Relate in applications to three ancestrally diverse samples that vary in both size and genealogical complexity. PMID:26748516

  19. Genetics

    MedlinePlus

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  20. ENU mutagenesis to generate genetically modified rat models.

    PubMed

    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.

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

    PubMed Central

    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

  2. Transferability of regional permafrost disturbance susceptibility modelling using generalized linear and generalized additive models

    NASA Astrophysics Data System (ADS)

    Rudy, Ashley C. A.; Lamoureux, Scott F.; Treitz, Paul; van Ewijk, Karin Y.

    2016-07-01

    To effectively assess and mitigate risk of permafrost disturbance, disturbance-prone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape characteristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Peninsula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed locations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) > 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Additionally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results indicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of disturbances were

  3. Rapid SAR target modeling through genetic inheritance mechanism

    NASA Astrophysics Data System (ADS)

    Bala, Jerzy; Pachowicz, Peter W.; Vafaie, Halleh

    1997-07-01

    The paper presents a methodology and GETP experimental system for rapid SAR target signature generation from limited initial sensory data. The methodology exploits and integrates the following four processes: (1) analysis of initial SAR image signatures and their transformation into higher-level blob representation, (2) blob modeling, (3) genetic inheritance modeling to generate new instances of a target model in blob representation, and (4) synthesis of new SAR signatures from genetically evolved blob data. The GETP system takes several SAR signatures of the target and transforms each signature into more general scattered blob graphs, where each blob represents local energy cluster. A single graph node is describe by blob relative position, confidence, and iconic data. Graph data is forwarded to the genetic modeling process while blob image is stored in a catalog. Genetic inheritance is applied to the initial population of graph data. New graph models of the target are generated and evaluated. Selected graph variations are forwarded to the synthesis process. The synthesis process restores target signature from a given graph and a catalog of blobs. The background is synthesized to complement the signature. Initial experimental results are illustrated with 64 X 32 image sections of a tank.

  4. Dissecting genetic and environmental mutation signatures with model organisms.

    PubMed

    Segovia, Romulo; Tam, Annie S; Stirling, Peter C

    2015-08-01

    Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon.

  5. Dissecting genetic and environmental mutation signatures with model organisms.

    PubMed

    Segovia, Romulo; Tam, Annie S; Stirling, Peter C

    2015-08-01

    Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon. PMID:25940384

  6. Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

    PubMed

    Forutan, M; Ansari Mahyari, S; Sargolzaei, M

    2015-02-01

    Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection.

  7. Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

    PubMed

    Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

    2012-08-01

    compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

  8. Is Structural Equation Modeling Advantageous for the Genetic Improvement of Multiple Traits?

    PubMed Central

    Valente, Bruno D.; Rosa, Guilherme J. M.; Gianola, Daniel; Wu, Xiao-Lin; Weigel, Kent

    2013-01-01

    Structural equation models (SEMs) are multivariate specifications capable of conveying causal relationships among traits. Although these models offer insights into how phenotypic traits relate to each other, it is unclear whether and how they can improve multiple-trait selection. Here, we explored concepts involved in SEMs, seeking for benefits that could be brought to breeding programs, relative to the standard multitrait model (MTM) commonly used. Genetic effects pertaining to SEMs and MTMs have distinct meanings. In SEMs, they represent genetic effects acting directly on each trait, without mediation by other traits in the model; in MTMs they express overall genetic effects on each trait, equivalent to lumping together direct and indirect genetic effects discriminated by SEMs. However, in breeding programs the goal is selecting candidates that produce offspring with best phenotypes, regardless of how traits are causally associated, so overall additive genetic effects are the matter. Thus, no information is lost in standard settings by using MTM-based predictions, even if traits are indeed causally associated. Nonetheless, causal information allows predicting effects of external interventions. One may be interested in predictions for scenarios where interventions are performed, e.g., artificially defining the value of a trait, blocking causal associations, or modifying their magnitudes. We demonstrate that with information provided by SEMs, predictions for these scenarios are possible from data recorded under no interventions. Contrariwise, MTMs do not provide information for such predictions. As livestock and crop production involves interventions such as management practices, SEMs may be advantageous in many settings. PMID:23608193

  9. Modeling the cardiovascular system using a nonlinear additive autoregressive model with exogenous input

    NASA Astrophysics Data System (ADS)

    Riedl, M.; Suhrbier, A.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.

    2008-07-01

    The parameters of heart rate variability and blood pressure variability have proved to be useful analytical tools in cardiovascular physics and medicine. Model-based analysis of these variabilities additionally leads to new prognostic information about mechanisms behind regulations in the cardiovascular system. In this paper, we analyze the complex interaction between heart rate, systolic blood pressure, and respiration by nonparametric fitted nonlinear additive autoregressive models with external inputs. Therefore, we consider measurements of healthy persons and patients suffering from obstructive sleep apnea syndrome (OSAS), with and without hypertension. It is shown that the proposed nonlinear models are capable of describing short-term fluctuations in heart rate as well as systolic blood pressure significantly better than similar linear ones, which confirms the assumption of nonlinear controlled heart rate and blood pressure. Furthermore, the comparison of the nonlinear and linear approaches reveals that the heart rate and blood pressure variability in healthy subjects is caused by a higher level of noise as well as nonlinearity than in patients suffering from OSAS. The residue analysis points at a further source of heart rate and blood pressure variability in healthy subjects, in addition to heart rate, systolic blood pressure, and respiration. Comparison of the nonlinear models within and among the different groups of subjects suggests the ability to discriminate the cohorts that could lead to a stratification of hypertension risk in OSAS patients.

  10. Resolving Conflicts: Modeling Genetic Control of Plant Morphogenesis.

    PubMed

    Coen, Enrico; Rebocho, Alexandra B

    2016-09-26

    Computational modeling of tissue morphogenesis reveals how spatiotemporal patterns of gene activity control tissue shape by introducing several types of tissue conflict. These conflicts reflect genetic modulation of processes that influence the cellular mechanical properties and may underlie the enormous diversity of forms that have evolved in plants and animals. PMID:27676429

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 mod...

  12. Assessment of the dynamics of microparasite infections in genetically homogeneous and heterogeneous populations using a stochastic epidemic model.

    PubMed

    Nath, M; Woolliams, J A; Bishop, S C

    2008-08-01

    The aim of this paper was to explore the effect of genetic heterogeneity in host resistance to infection on the population-level risks and outcomes of epidemics. This was done using a stochastic epidemiological model in which the model parameters were assumed to be genetically controlled traits of the host. A finite locus model was explored, with a gene controlling the transmission coefficient (i.e., host susceptibility to infection) and a gene controlling the recovery period. Both genes were simulated to have 2 alleles with underlying additive or dominance inheritance and an independent assortment of alleles. The model was parameterized for a viral pig disease (transmissible gastroenteritis), and complete homogeneous mixing among genotypes was assumed. Mean population genotype dramatically affected epidemic outcomes, and subtle effects of heterogeneity on epidemic properties were also observed. Genetic variation in the transmission coefficient led to probabilities of epidemics occurring that were slightly greater than expected, but genetic variation in the recovery rate had no such effect. Epidemics were generally less severe in genetically heterogeneous populations than expected from the constituent subpopulations. Furthermore, the genotype of the initial infected animal had a marked effect on epidemic probabilities, particularly when genetic variation was for recovery rate. The results of this model provide useful information to determine the optimum population structures and to exploit genetic variation in resistance to infection. Applications of the proposed model in genetically heterogeneous populations for identifying practical disease management strategies are also discussed.

  13. Genetic animal models of dystonia: common features and diversities.

    PubMed

    Richter, Franziska; Richter, Angelika

    2014-10-01

    Animal models are pivotal for studies of pathogenesis and treatment of disorders of the central nervous system which in its complexity cannot yet be modeled in vitro or using computer simulations. The choice of a specific model to test novel therapeutic strategies for a human disease should be based on validity of the model for the approach: does the model reflect symptoms, pathogenesis and treatment response present in human patients? In the movement disorder dystonia, prior to the availability of genetically engineered mice, spontaneous mutants were chosen based on expression of dystonic features, including abnormal muscle contraction, movements and postures. Recent discovery of a number of genes and gene products involved in dystonia initiated research on pathogenesis of the disorder, and the creation of novel models based on gene mutations. Here we present a review of current models of dystonia, with a focus on genetic rodent models, which will likely be first choice in the future either for pathophysiological or for preclinical drug testing or both. In order to help selection of a model depending on expression of a specific feature of dystonia, this review is organized by symptoms and current knowledge of pathogenesis of dystonia. We conclude that albeit there is increasing need for research on pathogenesis of the disease and development of improved models, current models do replicate features of dystonia and are useful tools to develop urgently demanded treatment for this debilitating disorder.

  14. Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes.

    PubMed Central

    Gianola, Daniel; Sorensen, Daniel

    2004-01-01

    Multivariate models are of great importance in theoretical and applied quantitative genetics. We extend quantitative genetic theory to accommodate situations in which there is linear feedback or recursiveness between the phenotypes involved in a multivariate system, assuming an infinitesimal, additive, model of inheritance. It is shown that structural parameters defining a simultaneous or recursive system have a bearing on the interpretation of quantitative genetic parameter estimates (e.g., heritability, offspring-parent regression, genetic correlation) when such features are ignored. Matrix representations are given for treating a plethora of feedback-recursive situations. The likelihood function is derived, assuming multivariate normality, and results from econometric theory for parameter identification are adapted to a quantitative genetic setting. A Bayesian treatment with a Markov chain Monte Carlo implementation is suggested for inference and developed. When the system is fully recursive, all conditional posterior distributions are in closed form, so Gibbs sampling is straightforward. If there is feedback, a Metropolis step may be embedded for sampling the structural parameters, since their conditional distributions are unknown. Extensions of the model to discrete random variables and to nonlinear relationships between phenotypes are discussed. PMID:15280252

  15. Metabolic Profiles and Genetic Diversity of Denitrifying Communities in Activated Sludge after Addition of Methanol or Ethanol†

    PubMed Central

    Hallin, Sara; Throbäck, Ingela Noredal; Dicksved, Johan; Pell, Mikael

    2006-01-01

    External carbon sources can enhance denitrification rates and thus improve nitrogen removal in wastewater treatment plants. The effects of adding methanol and ethanol on the genetic and metabolic diversity of denitrifying communities in activated sludge were compared using a pilot-scale plant with two parallel lines. A full-scale plant receiving the same municipal wastewater, but without external carbon source addition, was the reference. Metabolic profiles obtained from potential denitrification rates with 10 electron donors showed that the denitrifying communities altered their preferences for certain compounds after supplementation with methanol or ethanol and that methanol had the greater impact. Clone libraries of nirK and nirS genes, encoding the two different nitrite reductases in denitrifiers, revealed that methanol also increased the diversity of denitrifiers of the nirS type, which indicates that denitrifiers favored by methanol were on the rise in the community. This suggests that there might be a niche differentiation between nirS and nirK genotypes during activated sludge processes. The composition of nirS genotypes also varied greatly among all samples, whereas the nirK communities were more stable. The latter was confirmed by denaturing gradient gel electrophoresis of nirK communities on all sampling occasions. Our results support earlier hypotheses that the compositions of denitrifier communities change during predenitrification processes when external carbon sources are added, although no severe effect could be observed from an operational point of view. PMID:16885297

  16. The Analysis of Quantitative Traits for Simple Genetic Models from Parental, F1 and Backcross Data

    PubMed Central

    Elston, R. C.; Stewart, John

    1973-01-01

    The following models are considered for the genetic determination of quantitative traits: segregation at one locus, at two linked loci, at any number of equal and additive unlinked loci, and at one major locus and an indefinite number of equal and additive loci. In each case an appropriate likelihood is given for data on parental, F1 and backcross individuals, assuming that the environmental variation is normally distributed. Methods of testing and comparing the various models are presented, and methods are suggested for the simultaneous analysis of two or more traits. PMID:4711900

  17. A genetic animal model of differential sensitivity to methamphetamine reinforcement

    PubMed Central

    Shabani, Shkelzen; Dobbs, Lauren K; Ford, Matthew M; Mark, Gregory P; Finn, Deborah A; Phillips, Tamara J

    2012-01-01

    Sensitivity to reinforcement from methamphetamine (MA) likely influences risk for MA addiction, and genetic differences are one source of individual variation. Generation of two sets of selectively bred mouse lines for high and low MA drinking has shown that genetic factors influence MA intake, and pronounced differences in sensitivity to rewarding and aversive effects of MA play a significant role. Further validation of these lines as a unique genetic model relevant to MA addiction was obtained using operant methods to study MA reinforcement. High and low MA drinking line mice were used to test the hypotheses that: 1) oral and intracerebroventricular (ICV) MA serve as behavioral reinforcers, and 2) MA exhibits greater reinforcing efficacy in high than low MA drinking mice. Operant responses resulted in access to an MA or non-MA drinking tube or intracranial delivery of MA. Behavioral activation consequent to orally consumed MA was determined. MA available for consumption maintained higher levels of reinforced instrumental responding in high than low MA drinking line mice, and MA intake in the oral operant procedure was greater in high than low MA drinking line mice. Behavioral activation was associated with amount of MA consumed during operant sessions. High line mice delivered more MA via ICV infusion than did low line mice across a range of doses. Thus, genetic risk factors play a critical role in the reinforcing efficacy of MA and the oral self-administration procedure is suitable for delineating genetic contributions to MA reinforcement. PMID:22280875

  18. Genetic Models of PGC-1 and Glucose Metabolism and Homeostasis

    PubMed Central

    Rowe, Glenn C.; Arany, Zolt

    2013-01-01

    Type II diabetes and its complications are a tremendous health burden throughout the world. Our understanding of the changes that lead to glucose imbalance and insulin resistance and ultimately diabetes remain incompletely understood. Many signaling and transcriptional pathways have been identified as being important to maintain normal glucose balance, including that of the peroxisome proliferator activated receptor gamma coactivator (PGC-1) family. This family of transcriptional coactivators strongly regulates mitochondrial and metabolic biology in numerous organs. The use of genetic models of PGC-1s, including both tissue-specific overexpression and knock-out models, has helped to reveal the specific roles that these coactivators play in each tissue. This review will thus focus on the PGC-1s and recently developed genetic rodent models that have highlighted the importance of these molecules in maintaining normal glucose homeostasis. PMID:24057597

  19. Genetic implanted fuzzy model for water saturation determination

    NASA Astrophysics Data System (ADS)

    Bagheripour, Parisa; Asoodeh, Mojtaba

    2014-04-01

    The portion of rock pore volume occupied with non-hydrocarbon fluids is called water saturation, which plays a significant role in reservoir description and management. Accurate water saturation, directly measured from special core analysis is highly expensive and time consuming. Furthermore, indirect measurements of water saturation from well log interpretation such as empirical correlations or statistical methods do not provide satisfying results. Recent works showed that fuzzy logic is a robust tool for handling geosciences problems which provide more reliable results compared with empirical correlations or statistical methods. This study goes further to improve fuzzy logic for enhancing accuracy of final prediction. It employs hybrid genetic algorithm-pattern search technique instead of widely held subtractive clustering approach for setting up fuzzy rules and for extracting optimal parameters involved in computational structure of fuzzy model. The proposed strategy, called genetic implanted fuzzy model, was used to formulate conventional well log data, including sonic transit time, neutron porosity, formation bulk density, true resistivity, and gamma ray into water saturation, obtained from subtractive clustering approach. Results indicated genetic implanted fuzzy model performed more satisfyingly compared with traditional fuzzy logic model. The propounded model was successfully applied to one of Iranian carbonate reservoir rocks.

  20. The stewardship model: current viability for genetic biobank practice development.

    PubMed

    Williams, Pamela Holtzclaw; Schepp, Karen; McGrath, Barbara; Mitchell, Pamela

    2010-01-01

    The "stewardship model" of ethics relationships is a conceptual framework initially proposed by Jeffers in Advances in Nursing Science, 24(2), 2001. It conceptualized ethical responsibilities in the practice of systematic collection and storage of biospecimens in biobanks for future healthcare genetic research. Since the article's publication 8 years ago, genetic biobanks have grown in number around the world and discernible biobank relational conceptualizations were published. Nursing leadership adopted competency standards for all genetic nursing practices. The involvement of nurses has increased and is projected for further significant increase as biobank practices emerge from research into clinical care settings. This assessment of current viability of this previously established stewardship model offers fresh insights to existing and future nursing research and practice. The purpose of this article was to analyze the original stewardship model's components, the relational parties, and characteristics; by contrasting those with proposed conceptualizations and existing biobank practices developed subsequent to its publication. The model's current viability and theoretical development status are assessed for its ability to support a future nursing evidence base for best practices. Proposals for the model's expansion are suggested.

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

    PubMed

    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.

  2. Additive transgene expression and genetic introgression in multiple green-fluorescent protein transgenic crop x weed hybrid generations.

    PubMed

    Halfhill, M D; Millwood, R J; Weissinger, A K; Warwick, S I; Stewart, C N

    2003-11-01

    The level of transgene expression in crop x weed hybrids and the degree to which crop-specific genes are integrated into hybrid populations are important factors in assessing the potential ecological and agricultural risks of gene flow associated with genetic engineering. The average transgene zygosity and genetic structure of transgenic hybrid populations change with the progression of generations, and the green fluorescent protein (GFP) transgene is an ideal marker to quantify transgene expression in advancing populations. The homozygous T(1) single-locus insert GFP/ Bacillus thuringiensis (Bt) transgenic canola ( Brassica napus, cv Westar) with two copies of the transgene fluoresced twice as much as hemizygous individuals with only one copy of the transgene. These data indicate that the expression of the GFP gene was additive, and fluorescence could be used to determine zygosity status. Several hybrid generations (BC(1)F(1), BC(2)F(1)) were produced by backcrossing various GFP/Bt transgenic canola ( B. napus, cv Westar) and birdseed rape ( Brassica rapa) hybrid generations onto B. rapa. Intercrossed generations (BC(2)F(2) Bulk) were generated by crossing BC(2)F(1) individuals in the presence of a pollinating insect ( Musca domestica L.). The ploidy of plants in the BC(2)F(2) Bulk hybrid generation was identical to the weedy parental species, B. rapa. AFLP analysis was used to quantify the degree of B. napus introgression into multiple backcross hybrid generations with B. rapa. The F(1) hybrid generations contained 95-97% of the B. napus-specific AFLP markers, and each successive backcross generation demonstrated a reduction of markers resulting in the 15-29% presence in the BC(2)F(2) Bulk population. Average fluorescence of each successive hybrid generation was analyzed, and homozygous canola lines and hybrid populations that contained individuals homozygous for GFP (BC(2)F(2) Bulk) demonstrated significantly higher fluorescence than hemizygous hybrid

  3. Additive transgene expression and genetic introgression in multiple green-fluorescent protein transgenic crop x weed hybrid generations.

    PubMed

    Halfhill, M D; Millwood, R J; Weissinger, A K; Warwick, S I; Stewart, C N

    2003-11-01

    The level of transgene expression in crop x weed hybrids and the degree to which crop-specific genes are integrated into hybrid populations are important factors in assessing the potential ecological and agricultural risks of gene flow associated with genetic engineering. The average transgene zygosity and genetic structure of transgenic hybrid populations change with the progression of generations, and the green fluorescent protein (GFP) transgene is an ideal marker to quantify transgene expression in advancing populations. The homozygous T(1) single-locus insert GFP/ Bacillus thuringiensis (Bt) transgenic canola ( Brassica napus, cv Westar) with two copies of the transgene fluoresced twice as much as hemizygous individuals with only one copy of the transgene. These data indicate that the expression of the GFP gene was additive, and fluorescence could be used to determine zygosity status. Several hybrid generations (BC(1)F(1), BC(2)F(1)) were produced by backcrossing various GFP/Bt transgenic canola ( B. napus, cv Westar) and birdseed rape ( Brassica rapa) hybrid generations onto B. rapa. Intercrossed generations (BC(2)F(2) Bulk) were generated by crossing BC(2)F(1) individuals in the presence of a pollinating insect ( Musca domestica L.). The ploidy of plants in the BC(2)F(2) Bulk hybrid generation was identical to the weedy parental species, B. rapa. AFLP analysis was used to quantify the degree of B. napus introgression into multiple backcross hybrid generations with B. rapa. The F(1) hybrid generations contained 95-97% of the B. napus-specific AFLP markers, and each successive backcross generation demonstrated a reduction of markers resulting in the 15-29% presence in the BC(2)F(2) Bulk population. Average fluorescence of each successive hybrid generation was analyzed, and homozygous canola lines and hybrid populations that contained individuals homozygous for GFP (BC(2)F(2) Bulk) demonstrated significantly higher fluorescence than hemizygous hybrid

  4. Monthly pan evaporation modeling using linear genetic programming

    NASA Astrophysics Data System (ADS)

    Guven, Aytac; Kisi, Ozgur

    2013-10-01

    This study compares the accuracy of linear genetic programming (LGP), fuzzy genetic (FG), adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN) and Stephens-Stewart (SS) methods in modeling pan evaporations. Monthly climatic data including solar radiation, air temperature, relative humidity, wind speed and pan evaporation from Antalya and Mersin stations, in Turkey are used in the study. The study composed of two parts. First part of the study focuses the comparison of LGP models with those of the FG, ANFIS, ANN and SS models in estimating pan evaporations of Antalya and Mersin stations, separately. From the comparison results, the LGP models are found to be better than the other models. Comparison of LGP models with the other models in estimating pan evaporations of the Mersin Station by using both stations' inputs is focused in the second part of the study. The results indicate that the LGP models better accuracy than the FG, ANFIS, ANN and SS models. It is seen that the pan evaporations can be successfully estimated by the LGP method.

  5. Current Progress of Genetically Engineered Pig Models for Biomedical Research

    PubMed Central

    Gün, Gökhan

    2014-01-01

    Abstract The first transgenic pigs were generated for agricultural purposes about three decades ago. Since then, the micromanipulation techniques of pig oocytes and embryos expanded from pronuclear injection of foreign DNA to somatic cell nuclear transfer, intracytoplasmic sperm injection-mediated gene transfer, lentiviral transduction, and cytoplasmic injection. Mechanistically, the passive transgenesis approach based on random integration of foreign DNA was developed to active genetic engineering techniques based on the transient activity of ectopic enzymes, such as transposases, recombinases, and programmable nucleases. Whole-genome sequencing and annotation of advanced genome maps of the pig complemented these developments. The full implementation of these tools promises to immensely increase the efficiency and, in parallel, to reduce the costs for the generation of genetically engineered pigs. Today, the major application of genetically engineered pigs is found in the field of biomedical disease modeling. It is anticipated that genetically engineered pigs will increasingly be used in biomedical research, since this model shows several similarities to humans with regard to physiology, metabolism, genome organization, pathology, and aging. PMID:25469311

  6. Estimates of genetic parameters for growth traits in Brahman cattle using random regression and multitrait models.

    PubMed

    Bertipaglia, T S; Carreño, L O D; Aspilcueta-Borquis, R R; Boligon, A A; Farah, M M; Gomes, F J; Machado, C H C; Rey, F S B; da Fonseca, R

    2015-08-01

    Random regression models (RRM) and multitrait models (MTM) were used to estimate genetic parameters for growth traits in Brazilian Brahman cattle and to compare the estimated breeding values obtained by these 2 methodologies. For RRM, 78,641 weight records taken between 60 and 550 d of age from 16,204 cattle were analyzed, and for MTM, the analysis consisted of 17,385 weight records taken at the same ages from 12,925 cattle. All models included the fixed effects of contemporary group and the additive genetic, maternal genetic, and animal permanent environmental effects and the quadratic effect of age at calving (AAC) as covariate. For RRM, the AAC was nested in the animal's age class. The best RRM considered cubic polynomials and the residual variance heterogeneity (5 levels). For MTM, the weights were adjusted for standard ages. For RRM, additive heritability estimates ranged from 0.42 to 0.75, and for MTM, the estimates ranged from 0.44 to 0.72 for both models at 60, 120, 205, 365, and 550 d of age. The maximum maternal heritability estimate (0.08) was at 140 d for RRM, but for MTM, it was highest at weaning (0.09). The magnitude of the genetic correlations was generally from moderate to high. The RRM adequately modeled changes in variance or covariance with age, and provided there was sufficient number of samples, increased accuracy in the estimation of the genetic parameters can be expected. Correlation of bull classifications were different in both methods and at all the ages evaluated, especially at high selection intensities, which could affect the response to selection. PMID:26440161

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

    ERIC Educational Resources Information Center

    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…

  8. Additive genetic variation in resistance of Nile tilapia (Oreochromis niloticus) to Streptococcus iniae and S. agalactiae capsular type Ib: is genetic resistance correlated?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Streptococcus (S.) iniae and S. agalactiae are both economically important Gram positive bacterial pathogens affecting the globally farmed tilapia (Oreochromis spp.). Historically control of these bacteria in tilapia culture has included biosecurity, therapeutants and vaccination strategies. Genet...

  9. Genetic variants associated with neurodegenerative Alzheimer disease in natural models.

    PubMed

    Salazar, Claudia; Valdivia, Gonzalo; Ardiles, Álvaro O; Ewer, John; Palacios, Adrián G

    2016-01-01

    The use of transgenic models for the study of neurodegenerative diseases has made valuable contributions to the field. However, some important limitations, including protein overexpression and general systemic compensation for the missing genes, has caused researchers to seek natural models that show the main biomarkers of neurodegenerative diseases during aging. Here we review some of these models-most of them rodents, focusing especially on the genetic variations in biomarkers for Alzheimer diseases, in order to explain their relationships with variants associated with the occurrence of the disease in humans. PMID:26919851

  10. Nonlinear Modeling of the Aids Virus Genetic Sequence Evolution

    NASA Astrophysics Data System (ADS)

    Cocho, G.; Gelover-Santiago, A.; Martinez-Mekler, G.; Rodin, A.

    A network of coupled maps is introduced to model the evolution of the genetic sequence of the HIV1 AIDS virus. Within a space of RNA chemical composition, short range interactions correspond to mutations. Ecological constraints generate long range couplings. The resulting equations are of a reaction-diffusion type. Quasi-species with an error threshold emerge from the model dynamics. Predictions relating chemical composition regularity properties with the variability of the HIV RNA sequence agree with a statistical analysis from gene data banks. The model suggests a clue for an alternative therapeutical treatment.

  11. Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

    PubMed

    Santure, Anna W; Spencer, Hamish G

    2006-08-01

    The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components. PMID:16751674

  12. Genetic "code": representations and dynamical models of genetic components and networks.

    PubMed

    Gilman, Alex; Arkin, Adam P

    2002-01-01

    Dynamical modeling of biological systems is becoming increasingly widespread as people attempt to grasp biological phenomena in their full complexity and make sense of an accelerating stream of experimental data. We review a number of recent modeling studies that focus on systems specifically involving gene expression and regulation. These systems include bacterial metabolic operons and phase-variable piliation, bacteriophages T7 and lambda, and interacting networks of eukaryotic developmental genes. A wide range of conceptual and mathematical representations of genetic components and phenomena appears in these works. We discuss these representations in depth and give an overview of the tools currently available for creating and exploring dynamical models. We argue that for modeling to realize its full potential as a mainstream biological research technique the tools must become more general and flexible, and formal, standardized representations of biological knowledge and data must be developed.

  13. A pathway-based analysis provides additional support for an immune-related genetic susceptibility to Parkinson's disease.

    PubMed

    Holmans, Peter; Moskvina, Valentina; Jones, Lesley; Sharma, Manu; Vedernikov, Alexey; Buchel, Finja; Saad, Mohamad; Sadd, Mohamad; Bras, Jose M; Bettella, Francesco; Nicolaou, Nayia; Simón-Sánchez, Javier; Mittag, Florian; Gibbs, J Raphael; Schulte, Claudia; Durr, Alexandra; Guerreiro, Rita; Hernandez, Dena; Brice, Alexis; Stefánsson, Hreinn; Majamaa, Kari; Gasser, Thomas; Heutink, Peter; Wood, Nicholas W; Martinez, Maria; Singleton, Andrew B; Nalls, Michael A; Hardy, John; Morris, Huw R; Williams, Nigel M

    2013-03-01

    Parkinson's disease (PD) is the second most common neurodegenerative disease affecting 1-2% in people >60 and 3-4% in people >80. Genome-wide association (GWA) studies have now implicated significant evidence for association in at least 18 genomic regions. We have studied a large PD-meta analysis and identified a significant excess of SNPs (P < 1 × 10(-16)) that are associated with PD but fall short of the genome-wide significance threshold. This result was independent of variants at the 18 previously implicated regions and implies the presence of additional polygenic risk alleles. To understand how these loci increase risk of PD, we applied a pathway-based analysis, testing for biological functions that were significantly enriched for genes containing variants associated with PD. Analysing two independent GWA studies, we identified that both had a significant excess in the number of functional categories enriched for PD-associated genes (minimum P = 0.014 and P = 0.006, respectively). Moreover, 58 categories were significantly enriched for associated genes in both GWA studies (P < 0.001), implicating genes involved in the 'regulation of leucocyte/lymphocyte activity' and also 'cytokine-mediated signalling' as conferring an increased susceptibility to PD. These results were unaltered by the exclusion of all 178 genes that were present at the 18 genomic regions previously reported to be strongly associated with PD (including the HLA locus). Our findings, therefore, provide independent support to the strong association signal at the HLA locus and imply that the immune-related genetic susceptibility to PD is likely to be more widespread in the genome than previously appreciated.

  14. Sleep and Development in Genetically Tractable Model Organisms.

    PubMed

    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. PMID:27183564

  15. A Family-Centered Model for Sharing Genetic Risk.

    PubMed

    Daly, Mary B

    2015-01-01

    The successes of the Human Genome Project have ushered in a new era of genomic science. To effectively translate these discoveries, it will be critical to improve the communication of genetic risk within families. This will require a systematic approach that accounts for the nature of family relationships and sociocultural beliefs. This paper proposes the application of the Family Systems Illness Model, used in the setting of cancer care, to the evolving field of genomics. PMID:26479564

  16. Types of disease and models for their genetic analysis.

    PubMed

    Elston, R C; Namboodiri, K K

    1980-01-01

    The authors compare schizophrenia with several other diseases and discuss how a few simple models that have already been successfully applied in other cases could be used in the genetic analysis of schizophrenia and MAO activity. Among the diseases discussed are Huntington's disease, xanthomatosis, and diabetes. The authors recommend undertaking multivariate studies of monoamine oxidase, dopamine beta-hydroxylase, and other traits associated with schizophrenia in single, large pedigrees ascertained through schizophrenic probands.

  17. Physiological and genetic analysis of multiple sodium channel variants in a model of genetic absence epilepsy

    PubMed Central

    Oliva, M K; McGarr, T C; Beyer, B J; Gazina, E; Kaplan, D I; Cordeiro, L; Thomas, E; Dib-Hajj, S D; Waxman, S G; Frankel, W N; Petrou, S

    2015-01-01

    In excitatory neurons, SCN2A (NaV1.2) and SCN8A (NaV1.6) sodium channels are enriched at the axon initial segment. NaV1.6 is implicated in several mouse models of absence epilepsy, including a missense mutation identified in a chemical mutagenesis screen (Scn8aV929F). Here, we confirmed the prior suggestion that Scn8aV929F exhibits a striking genetic background-dependent difference in phenotypic severity, observing that spike-wave discharge (SWD) incidence and severity are significantly diminished when Scn8aV929F is fully placed onto the C57BL/6J strain compared with C3H. Examination of sequence differences in NaV subunits between these two inbred strains suggested NaV1.2V752F as a potential source of this modifier effect. Recognising that the spatial co-localisation of the NaV channels at the axon initial segment (AIS) provides a plausible mechanism for functional interaction, we tested this idea by undertaking biophysical characterisation of the variant NaV channels and by computer modelling. NaV1.2V752F functional analysis revealed an overall gain-of-function and for NaV1.6V929F revealed an overall loss-of-function. A biophysically realistic computer model was used to test the idea that interaction between these variant channels at the AIS contributes to the strain background effect. Surprisingly this modelling showed that neuronal excitability is dominated by the properties of NaV1.2V752F due to “functional silencing” of NaV1.6V929F suggesting that these variants do not directly interact. Consequent genetic mapping of the major strain modifier to Chr 7, and not Chr 2 where Scn2a maps, supported this biophysical prediction. While a NaV1.6V929F loss of function clearly underlies absence seizures in this mouse model, the strain background effect is apparently not due to an otherwise tempting Scn2a variant, highlighting the value of combining physiology and genetics to inform and direct each other when interrogating genetic complex traits such as absence

  18. Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

    PubMed Central

    McFadden, David G.; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K.; Song, Xiaoling; Pirun, Mono; Santiago, Philip M.; Kim-Kiselak, Caroline; Platt, James T.; Lee, Emily; Hodges, Emily; Rosebrock, Adam P.; Bronson, Roderick T.; Socci, Nicholas D.; Hannon, Gregory J.; Jacks, Tyler; Varmus, Harold

    2016-01-01

    Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity. PMID:27702896

  19. Additive Manufacturing Modeling and Simulation A Literature Review for Electron Beam Free Form Fabrication

    NASA Technical Reports Server (NTRS)

    Seufzer, William J.

    2014-01-01

    Additive manufacturing is coming into industrial use and has several desirable attributes. Control of the deposition remains a complex challenge, and so this literature review was initiated to capture current modeling efforts in the field of additive manufacturing. This paper summarizes about 10 years of modeling and simulation related to both welding and additive manufacturing. The goals were to learn who is doing what in modeling and simulation, to summarize various approaches taken to create models, and to identify research gaps. Later sections in the report summarize implications for closed-loop-control of the process, implications for local research efforts, and implications for local modeling efforts.

  20. Hierarchical Stochastic Simulation Algorithm for SBML Models of Genetic Circuits.

    PubMed

    Watanabe, Leandro H; Myers, Chris J

    2014-01-01

    This paper describes a hierarchical stochastic simulation algorithm, which has been implemented within iBioSim, a tool used to model, analyze, and visualize genetic circuits. Many biological analysis tools flatten out hierarchy before simulation, but there are many disadvantages associated with this approach. First, the memory required to represent the model can quickly expand in the process. Second, the flattening process is computationally expensive. Finally, when modeling a dynamic cellular population within iBioSim, inlining the hierarchy of the model is inefficient since models must grow dynamically over time. This paper discusses a new approach to handle hierarchy on the fly to make the tool faster and more memory-efficient. This approach yields significant performance improvements as compared to the former flat analysis method.

  1. Vascular Anomalies: From Genetics toward Models for Therapeutic Trials

    PubMed Central

    Uebelhoer, Melanie; Boon, Laurence M.; Vikkula, Miikka

    2012-01-01

    Vascular anomalies are localized abnormalities that occur during vascular development. Several causative genes have been identified not only for inherited but also for some sporadic forms, and the molecular pathways involved are becoming understood. This gives us the opportunity to generate animals carrying the causative genetic defects, which we hope model the phenotype seen in human patients. These models would enable us not only to test known antiangiogenic drugs, but also to develop novel approaches for treatment, directly targeting the mutated protein or molecules implicated in the pathophysiological signaling pathways. PMID:22908197

  2. In Vitro Cultivation of the Hymenoptera Genetic Model, Nasonia

    PubMed Central

    Brucker, Robert M.; Bordenstein, Seth R.

    2012-01-01

    The wasp genus Nasonia is a genetic model with unique advantages for the study of interspecific differences, including haplodiploidy and interfertile species. However, as a parasitoid, Nasonia is confined within a fly host, thus restricting direct observations and manipulation of development over time. Here, we present the first in vitro cultivation method for this system that decouples Nasonia from its host, allowing continuous observations from embryo to adulthood. Using transwell plates and a simple Nasonia rearing medium, we demonstrate a technique that will significantly expand the utility of the Nasonia model. PMID:23227258

  3. Nature and nurture: environmental influences on a genetic rat model of depression.

    PubMed

    Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

    2016-03-29

    In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or 'nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, 'trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms.

  4. Multiprocessing and Correction Algorithm of 3D-models for Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Anamova, R. R.; Zelenov, S. V.; Kuprikov, M. U.; Ripetskiy, A. V.

    2016-07-01

    This article addresses matters related to additive manufacturing preparation. A layer-by-layer model presentation was developed on the basis of a routing method. Methods for correction of errors in the layer-by-layer model presentation were developed. A multiprocessing algorithm for forming an additive manufacturing batch file was realized.

  5. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

    PubMed

    Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

    2016-01-01

    Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington's genetic assimilation

  6. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation

    PubMed Central

    Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

    2016-01-01

    Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother’s old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother’s old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington’s genetic

  7. Genetic aspects of autism spectrum disorders: insights from animal models.

    PubMed

    Banerjee, Swati; Riordan, Maeveen; Bhat, Manzoor A

    2014-01-01

    Autism spectrum disorders (ASDs) 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 toward 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. PMID:24605088

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

    PubMed Central

    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

  9. Genetic analysis of carcass traits in beef cattle using random regression models.

    PubMed

    Englishby, T M; Banos, G; Moore, K L; Coffey, M P; Evans, R D; Berry, D P

    2016-04-01

    Livestock mature at different rates depending, in part, on their genetic merit; therefore, the optimal age at slaughter for progeny of certain sires may differ. The objective of the present study was to examine sire-level genetic profiles for carcass weight, carcass conformation, and carcass fat in cattle of multiple beef and dairy breeds, including crossbreeds. Slaughter records from 126,214 heifers and 124,641 steers aged between 360 and 1,200 d and from 86,089 young bulls aged between 360 and 720 d were used in the analysis; animals were from 15,127 sires. Variance components for each trait across age at slaughter were generated using sire random regression models that included quadratic polynomials for fixed and random effects; heterogeneous residual variances were assumed across ages. Heritability estimates across genders ranged from 0.08 (±0.02) to 0.34 (±0.02) for carcass weight, from 0.24 (±0.02) to 0.42 (±0.01) for conformation, and from 0.16 (±0.03) to 0.40 (±0.02) for fat score. Genetic correlations within each trait across ages weakened as the interval between ages compared lengthened but were all >0.64, suggesting a similar genetic background for each trait across different ages. Eigenvalues and eigenfunctions of the additive genetic covariance matrix revealed genetic variability among animals in their growth profiles for carcass traits, although most of the genetic variability was associated with the height of the growth profile. At the same age, a positive genetic correlation (0.60 to 0.78; SE ranged from 0.01 to 0.04) existed between carcass weight and conformation, whereas negative genetic correlations existed between fatness and both conformation (-0.46 to 0.08; SE ranged from 0.02 to 0.09) and carcass weight (-0.48 to -0.16; SE ranged from 0.02 to 0.14) at the same age. The estimated genetic parameters in the present study indicate genetic variability in the growth trajectory in cattle, which can be exploited through breeding programs and

  10. Modeling Leukemogenesis in the Zebrafish Using Genetic and Xenograft Models.

    PubMed

    Rajan, Vinothkumar; Dellaire, Graham; Berman, Jason N

    2016-01-01

    The zebrafish is a widely accepted model to study leukemia. The major advantage of studying leukemogenesis in zebrafish is attributed to its short life cycle and superior imaging capacity. This chapter highlights using transgenic- and xenograft-based models in zebrafish to study a specific leukemogenic mutation and analyze therapeutic responses in vivo. PMID:27464808

  11. Additive influence of genetic predisposition and conventional risk factors in the incidence of coronary heart disease: a population-based study in Greece

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-‘environment’ joint actions on CHD for severa...

  12. Modeling monthly pan evaporations using fuzzy genetic approach

    NASA Astrophysics Data System (ADS)

    Kişi, Özgür; Tombul, Mustafa

    2013-01-01

    SummaryThis study investigates the ability of fuzzy genetic (FG) approach in estimation of monthly pan evaporations. Various monthly climatic data, that are, solar radiation, air temperature, relative humidity and wind speed from two stations, Antalya and Mersin, in Mediterranean Region of Turkey, were used as inputs to the FG technique so as to estimate monthly pan evaporations. In the first part of the study, FG models were compared with neuro-fuzzy (ANFIS), artificial neural networks (ANNs) and Stephens-Stewart (SS) methods in estimating pan evaporations of Antalya and Mersin stations, separately. Comparison of the models revealed that the FG models generally performed better than the ANFIS, ANN and SS models. In the second part of the study, models were compared to each other in two different applications. In the first application the input data of Antalya Station were used as inputs to the models to estimate pan evaporation data of Mersin Station. The pan evaporation data of Mersin Station were estimated using the input data of Antalya and Mersin stations in the second application. Comparison results indicated that the FG models performed better than the ANFIS and ANN models. Comparison of the accuracy of the applied models in estimating total pan evaporations showed that the FG model provided the closest estimate. It was concluded that monthly pan evaporations could be successfully estimated by the FG approach.

  13. Suspended sediment modeling using genetic programming and soft computing techniques

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Dailr, Ali Hosseinzadeh; Cimen, Mesut; Shiri, Jalal

    2012-07-01

    SummaryModeling suspended sediment load is an important factor in water resources engineering as it crucially affects the design and management of water resources structures. In this study the genetic programming (GP) technique was applied for estimating the daily suspended sediment load in two stations in Cumberland River in U.S. Daily flow and sediment data from 1972 to 1989 were used to train and test the applied genetic programming models. The effect of various GP operators on sediment load estimation was investigated. The optimal fitness function, operator functions, linking function and learning algorithm were obtained for modeling daily suspended sediment. The GP estimates were compared with those of the Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Networks (ANNs) and Support Vector Machine (SVM) results, in term of coefficient of determination, mean absolute error, coefficient of residual mass and variance accounted for. The comparison results indicated that the GP is superior to the ANFIS, ANN and SVM models in estimating daily suspended sediment load.

  14. Random regression models for the estimation of genetic and environmental covariance functions for growth traits in Santa Ines sheep.

    PubMed

    Sarmento, J L R; Torres, R A; Sousa, W H; Lôbo, R N B; Albuquerque, L G; Lopes, P S; Santos, N P S; Bignard, A B

    2016-01-01

    Polynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz's Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573 provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studied.

  15. Random regression models for the estimation of genetic and environmental covariance functions for growth traits in Santa Ines sheep.

    PubMed

    Sarmento, J L R; Torres, R A; Sousa, W H; Lôbo, R N B; Albuquerque, L G; Lopes, P S; Santos, N P S; Bignard, A B

    2016-01-01

    Polynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz's Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573 provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studied. PMID:27323203

  16. Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

    PubMed Central

    Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

    2016-01-01

    Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

  17. A murine tumor progression model for pancreatic cancer recapitulating the genetic alterations of the human disease

    PubMed Central

    Wagner, Martin; Greten, Florian R.; Weber, Christoph K.; Koschnick, Stefan; Mattfeldt, Torsten; Deppert, Wolfgang; Kern, Horst; Adler, Guido; Schmid, Roland M.

    2001-01-01

    This study describes a tumor progression model for ductal pancreatic cancer in mice overexpressing TGF-α. Activation of Ras and Erk causes induction of cyclin D1-Cdk4 without increase of cyclin E or PCNA in ductal lesions. Thus, TGF-α is able to promote progression throughout G1, but not S phase. Crossbreeding with p53 null mice accelerates tumor development in TGF-α transgenic mice dramatically. In tumors developing in these mice, biallelic deletion of Ink4a/Arf or LOH of the Smad4 locus is found suggesting that loci in addition to p53 are involved in antitumor activities. We conclude that these genetic events are critical for pancreatic tumor formation in mice. This model recapitulates pathomorphological features and genetic alterations of the human disease. PMID:11159909

  18. Understanding the roles of FAK in cancer: inhibitors, genetic models, and new insights.

    PubMed

    Yoon, Hyunho; Dehart, Joshua P; Murphy, James M; Lim, Ssang-Taek Steve

    2015-02-01

    Focal adhesion kinase (FAK) is a protein tyrosine kinase that regulates cellular adhesion, motility, proliferation and survival in various types of cells. Interestingly, FAK is activated and/or overexpressed in advanced cancers, and promotes cancer progression and metastasis. For this reason, FAK became a potential therapeutic target in cancer, and small molecule FAK inhibitors have been developed and are being tested in clinical phase trials. These inhibitors have demonstrated to be effective by inducing tumor cell apoptosis in addition to reducing metastasis and angiogenesis. Furthermore, several genetic FAK mouse models have made advancements in understanding the specific role of FAK both in tumors and in the tumor environment. In this review, we discuss FAK inhibitors as well as genetic mouse models to provide mechanistic insights into FAK signaling and its potential in cancer therapy.

  19. Toward a biaxial model of "bipolar" affective disorders: further exploration of genetic, molecular and cellular substrates.

    PubMed

    Askland, Kathleen

    2006-08-01

    Current epidemiologic and genetic evidence strongly supports the heritability of bipolar disease. Inconsistencies across linkage and association analyses have been primarily interpreted as suggesting polygenic, nonMendelian and variably-penetrant inheritance (i.e., in terms of interacting disease models). An equally-likely explanation for this genetic complexity is that trait, locus and allelic heterogeneities (i.e., a heterogeneous disease model) are primarily responsible for observed variability at the population level. The two models of genetic complexity are not mutually-exclusive, and are in fact likely to co-exist both in trait determination and disease expression. However, the current model proposes that, while both types of complex genetics are likely central to observable affective trait spectra, inheritance patterns, gross phenotypic categories and treatment-responsiveness in affective disease (as well as the widespread inconsistencies across such studies) may be primarily explained in terms of a heterogeneous disease model. Gene-gene, gene-protein and protein-protein interactions, then, are most likely to serve as trait determinants and 'phenotypic modifiers' rather than as primary pathogenic determinants. Moreover, while locus heterogeneity indicates the presence of multiple susceptibility genes at the population level, it does not necessitate polygenic inheritance at the individual or pedigree level. Rather, it is compatible with the possibility of mono- or bigenic determination of disease susceptibility within individuals/pedigrees. More specifically, the biaxial model proposes that integration of specific findings from genetic linkage and association studies, ion channels research as well as pharmacologic mechanism, phenotypic specificity and effectiveness studies suggests that each gene of potential etiologic significance in primary affective illness might be categorized into one of two classes, according to their primary role in neuronal

  20. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: comparing meta and mega analytical approaches for data pooling

    PubMed Central

    Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E.; Mandl, René C.; Almasy, Laura; Booth, Tom; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Lemaitre, Hervé; Lopez, Lorna; Martin, Nicholas G.; McMahon, Katie L.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Wright, Susan N.; Bastin, Mark E.; McIntosh, Andrew M.; Boomsma, Dorret I.; Kahn, René S.; den Braber, Anouk; de Geus, Eco JC; Deary, Ian J.; Hulshoff Pol, Hilleke E.; Williamson, Douglas E.; Blangero, John; van ’t Ent, Dennis; Thompson, Paul M.; Glahn, David C.

    2014-01-01

    Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9–85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large “mega-family”. We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. PMID:24657781

  1. Genetic variation and selection response in model breeding populations of Brassica rapa following a diversity bottleneck.

    PubMed

    Briggs, William H; Goldman, Irwin L

    2006-01-01

    Domestication and breeding share a common feature of population bottlenecks followed by significant genetic gain. To date, no crop models for investigating the evolution of genetic variance, selection response, and population diversity following bottlenecks have been developed. We developed a model artificial selection system in the laboratory using rapid-cycling Brassica rapa. Responses to 10 cycles of recurrent selection for cotyledon size were compared across a broad population founded with 200 individuals, three bottleneck populations initiated with two individuals each, and unselected controls. Additive genetic variance and heritability were significantly larger in the bottleneck populations prior to selection and this corresponded to a heightened response of bottleneck populations during the first three cycles. However, the overall response was ultimately greater and more sustained in the broad population. AFLP marker analyses revealed the pattern and extent of population subdivision were unaffected by a bottleneck even though the diversity retained in a selection population was significantly limited. Rapid gain in genetically more uniform bottlenecked populations, particularly in the short term, may offer an explanation for why domesticators and breeders have realized significant selection progress over relatively short time periods.

  2. A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection

    PubMed Central

    Sale, Mark; Sherer, Eric A

    2015-01-01

    The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection. PMID:23772792

  3. Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks.

    PubMed

    Zomorrodi, Ali R; Lafontaine Rivera, Jimmy G; Liao, James C; Maranas, Costas D

    2013-09-01

    The ensemble modeling (EM) approach has shown promise in capturing kinetic and regulatory effects in the modeling of metabolic networks. Efficacy of the EM procedure relies on the identification of model parameterizations that adequately describe all observed metabolic phenotypes upon perturbation. In this study, we propose an optimization-based algorithm for the systematic identification of genetic/enzyme perturbations to maximally reduce the number of models retained in the ensemble after each round of model screening. The key premise here is to design perturbations that will maximally scatter the predicted steady-state fluxes over the ensemble parameterizations. We demonstrate the applicability of this procedure for an Escherichia coli metabolic model of central metabolism by successively identifying single, double, and triple enzyme perturbations that cause the maximum degree of flux separation between models in the ensemble. Results revealed that optimal perturbations are not always located close to reaction(s) whose fluxes are measured, especially when multiple perturbations are considered. In addition, there appears to be a maximum number of simultaneous perturbations beyond which no appreciable increase in the divergence of flux predictions is achieved. Overall, this study provides a systematic way of optimally designing genetic perturbations for populating the ensemble of models with relevant model parameterizations.

  4. Genetically Engineered Mouse Models for Drug Development and Preclinical Trials

    PubMed Central

    Lee, Ho

    2014-01-01

    Drug development and preclinical trials are challenging processes and more than 80% to 90% of drug candidates fail to gain approval from the United States Food and Drug Administration. Predictive and efficient tools are required to discover high quality targets and increase the probability of success in the process of new drug development. One such solution to the challenges faced in the development of new drugs and combination therapies is the use of low-cost and experimentally manageable in vivo animal models. Since the 1980’s, scientists have been able to genetically modify the mouse genome by removing or replacing a specific gene, which has improved the identification and validation of target genes of interest. Now genetically engineered mouse models (GEMMs) are widely used and have proved to be a powerful tool in drug discovery processes. This review particularly covers recent fascinating technologies for drug discovery and preclinical trials, targeted transgenesis and RNAi mouse, including application and combination of inducible system. Improvements in technologies and the development of new GEMMs are expected to guide future applications of these models to drug discovery and preclinical trials. PMID:25143803

  5. Estimating genetic parameters in natural populations using the "animal model".

    PubMed Central

    Kruuk, Loeske E B

    2004-01-01

    Estimating the genetic basis of quantitative traits can be tricky for wild populations in natural environments, as environmental variation frequently obscures the underlying evolutionary patterns. I review the recent application of restricted maximum-likelihood "animal models" to multigenerational data from natural populations, and show how the estimation of variance components and prediction of breeding values using these methods offer a powerful means of tackling the potentially confounding effects of environmental variation, as well as generating a wealth of new areas of investigation. PMID:15306404

  6. A Review of Modeling Techniques for Genetic Regulatory Networks

    PubMed Central

    Yaghoobi, Hanif; Haghipour, Siyamak; Hamzeiy, Hossein; Asadi-Khiavi, Masoud

    2012-01-01

    Understanding the genetic regulatory networks, the discovery of interactions between genes and understanding regulatory processes in a cell at the gene level are the major goals of system biology and computational biology. Modeling gene regulatory networks and describing the actions of the cells at the molecular level are used in medicine and molecular biology applications such as metabolic pathways and drug discovery. Modeling these networks is also one of the important issues in genomic signal processing. After the advent of microarray technology, it is possible to model these networks using time–series data. In this paper, we provide an extensive review of methods that have been used on time–series data and represent the features, advantages and disadvantages of each. Also, we classify these methods according to their nature. A parallel study of these methods can lead to the discovery of new synthetic methods or improve previous methods. PMID:23493097

  7. Landscape models for nuclear genetic diversity and genetic structure in white-footed mice (Peromyscus leucopus).

    PubMed

    Taylor, Z S; Hoffman, S M G

    2014-06-01

    Dramatic changes in the North American landscape over the last 12 000 years have shaped the genomes of the small mammals, such as the white-footed mouse (Peromyscus leucopus), which currently inhabit the region. However, very recent interactions of populations with each other and the environment are expected to leave the most pronounced signature on rapidly evolving nuclear microsatellite loci. We analyzed landscape characteristics and microsatellite markers of P. leucopus populations along a transect from southern Ohio to northern Michigan, in order to evaluate hypotheses about the spatial distribution of genetic heterogeneity. Genetic diversity increased to the north and was best approximated by a single-variable model based on habitat availability within a 0.5-km radius of trapping sites. Interpopulation differentiation measured by clustering analysis was highly variable and not significantly related to latitude or habitat availability. Interpopulation differentiation measured as FST values and chord distance was correlated with the proportion of habitat intervening, but was best explained by agricultural distance and by latitude. The observed gradients in diversity and interpopulation differentiation were consistent with recent habitat availability being the major constraint on effective population size in this system, and contradicted the predictions of both the postglacial expansion and core-periphery hypotheses. PMID:24448564

  8. Landscape models for nuclear genetic diversity and genetic structure in white-footed mice (Peromyscus leucopus).

    PubMed

    Taylor, Z S; Hoffman, S M G

    2014-06-01

    Dramatic changes in the North American landscape over the last 12 000 years have shaped the genomes of the small mammals, such as the white-footed mouse (Peromyscus leucopus), which currently inhabit the region. However, very recent interactions of populations with each other and the environment are expected to leave the most pronounced signature on rapidly evolving nuclear microsatellite loci. We analyzed landscape characteristics and microsatellite markers of P. leucopus populations along a transect from southern Ohio to northern Michigan, in order to evaluate hypotheses about the spatial distribution of genetic heterogeneity. Genetic diversity increased to the north and was best approximated by a single-variable model based on habitat availability within a 0.5-km radius of trapping sites. Interpopulation differentiation measured by clustering analysis was highly variable and not significantly related to latitude or habitat availability. Interpopulation differentiation measured as FST values and chord distance was correlated with the proportion of habitat intervening, but was best explained by agricultural distance and by latitude. The observed gradients in diversity and interpopulation differentiation were consistent with recent habitat availability being the major constraint on effective population size in this system, and contradicted the predictions of both the postglacial expansion and core-periphery hypotheses.

  9. Polymorphisms associated with the risk of lung cancer in a healthy Mexican Mestizo population: Application of the additive model for cancer

    PubMed Central

    Pérez-Morales, Rebeca; Méndez-Ramírez, Ignacio; Castro-Hernández, Clementina; Martínez-Ramírez, Ollin C.; Gonsebatt, María Eugenia; Rubio, Julieta

    2011-01-01

    Lung cancer is the leading cause of cancer mortality in Mexico and worldwide. In the past decade, there has been an increase in the number of lung cancer cases in young people, which suggests an important role for genetic background in the etiology of this disease. In this study, we genetically characterized 16 polymorphisms in 12 low penetrance genes (AhR, CYP1A1, CYP2E1, EPHX1, GSTM1, GSTT1, GSTPI, XRCC1, ERCC2, MGMT, CCND1 and TP53) in 382 healthy Mexican Mestizos as the first step in elucidating the genetic structure of this population and identifying high risk individuals. All of the genotypes analyzed were in Hardy-Weinberg equilibrium, but different degrees of linkage were observed for polymorphisms in the CYP1A1 and EPHX1 genes. The genetic variability of this population was distributed in six clusters that were defined based on their genetic characteristics. The use of a polygenic model to assess the additive effect of low penetrance risk alleles identified combinations of risk genotypes that could be useful in predicting a predisposition to lung cancer. Estimation of the level of genetic susceptibility showed that the individual calculated risk value (iCRV) ranged from 1 to 16, with a higher iCRV indicating a greater genetic susceptibility to lung cancer. PMID:22215955

  10. Practical implications for genetic modeling in the genomics era.

    PubMed

    VanRaden, P M

    2016-03-01

    Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, including genetic by environmental interactions and correlations among traits, and accounting for nonadditive inheritance or nonnormal distributions. Data include phenotypes and pedigrees during the last century and genotypes within the last decade. The genomic data can include single nucleotide polymorphisms, quantitative trait loci, insertions, deletions, and haplotypes. Subsets must be selected to reduce computation because total numbers of variants that can be imputed have increased rapidly from thousands to millions. Current computation using 60,671 markers takes just a few days. Nonlinear models can account for the nonnormal distribution of genomic effects, but reliability is usually better than that of linear models only for traits influenced by major genes. Numbers of genotyped animals have also increased rapidly in the joint North American database from a few thousand in 2009 to over 1 million in 2015. Most are young females and will contribute to estimating allele effects in the future, but only about 150,000 have phenotypes so far. Genomic preselection can bias traditional animal models because Mendelian sampling of phenotyped progeny and mates is no longer expected to average zero; however, estimates of bias are small in current US data. Single-step models that combine pedigree and genomic relationships can account for preselection, but approximations are required for affordable computation. Traditional animal models may include all breeds and crossbreds, but most genomic evaluations are still computed within breed. Models that include inbreeding, heterosis, dominance, and interactions can improve predictions for individual matings. Multitrait genomic models may

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

    ERIC Educational Resources Information Center

    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…

  12. The Genetic Counseling Video Project (GCVP): models of practice.

    PubMed

    Roter, D; Ellington, L; Erby, L Hamby; Larson, S; Dudley, W

    2006-11-15

    Genetic counseling is conceptualized as having both "teaching" and "counseling" functions; however, little is known about how these functions are articulated in routine practice. This study addresses the question by documenting, on videotape, the practices of a national sample of prenatal and cancer genetic counselors (GCs) providing routine pre-test counseling to simulated clients (SCs). One hundred and seventy-seven GCs recruited at two annual conferences of the National Society of Genetic Counselors (NSGC) were randomly assigned to counsel one of six female SCs of varying ethnicity, with or without a spouse, in their specialty. One hundred and fifty-two videotapes were coded with the Roter Interaction Analysis System (RIAS) and both GCs and SCs completed evaluative questionnaires. Two teaching and two counseling patterns of practice emerged from cluster analysis. The teaching patterns included: (1) clinical teaching (31%) characterized by low psychosocial, emotional and facilitative talk, high levels of clinical exchange, and high verbal dominance; and (2) psycho-educational teaching (27%) characterized by high levels of both clinical and psychosocial exchange, low levels of emotional and facilitative talk, and higher verbal dominance. The counseling patterns included: (1) supportive counseling (33%) characterized by low psychosocial and clinical exchange, high levels of emotional and facilitative talk, and low verbal dominance; and (2) psychosocial counseling (9%) with high emotional and facilitative talk, low clinical and high psychosocial exchange, and the lowest verbal dominance. SCs ratings of satisfaction with communication, the counselor's affective demeanor, and the counselor's use of non-verbal skills were highest for the counseling model sessions. Both the teaching and counseling models seem to be represented in routine practice and predict variation in client satisfaction, affective demeanor, and nonverbal effectiveness.

  13. The Genetic Counseling Video Project (GCVP): Models of Practice

    PubMed Central

    Roter, D.; Ellington, L.; Erby, L. Hamby; Larson, S.; W, Dudley

    2009-01-01

    Genetic counseling is conceptualized as having both “teaching” and “counseling” functions; however, little is known about how these functions are articulated in routine practice. This study addresses the question by documenting, on videotape, the practices of a national sample of prenatal and cancer genetic counselors (GCs) providing routine pretest counseling to simulated clients (SCs). 177 GCs recruited at two annual conferences of the National Society of Genetic Counselors (NSGC) were randomly assigned to counsel one of six female SCs of varying ethnicity, with or without a spouse, in their specialty. 152 videotapes were coded with the Roter Interaction Analysis System (RIAS) and both GCs and SCs completed evaluative questionnaires. Two teaching and two counseling patterns of practice emerged from cluster analysis. The teaching patterns included: (1) Clinical teaching (31%) characterized by low psychosocial, emotional and facilitative talk, high levels of clinical exchange, and high verbal dominance; and (2) Psycho-educational teaching (27%) characterized by high levels of both clinical and psychosocial exchange, low levels of emotional and facilitative talk, and higher verbal dominance. The counseling patterns included: (1) Supportive counseling (33%) characterized by low psychosocial and clinical exchange, high levels of emotional and facilitative talk, and low verbal dominance; and (2) Psychosocial counseling (9%) with high emotional and facilitative talk, low clinical and high psychosocial exchange, and the lowest verbal dominance. SCs ratings of satisfaction with communication, the counselor’s affective demeanor, and the counselor’s use of nonverbal skills were highest for the counseling model sessions. Both the teaching and counseling models seem to be represented in routine practice and predict variation in client satisfaction. PMID:16941666

  14. PGD for cystic fibrosis patients and couples at risk of an additional genetic disorder combined with 24-chromosome aneuploidy testing.

    PubMed

    Rechitsky, Svetlana; Verlinsky, Oleg; Kuliev, Anver

    2013-05-01

    Preimplantation genetic diagnosis (PGD) for inherited disorders is presently applied for more than 300 different conditions. The most frequent PGD indication is cystic fibrosis (CF), the largest series of which is reviewed here, totalling 404 PGD cycles. This involved testing for 52 different CFTR mutations with almost half of the cases (195/404 cycles) performed for ΔF508 mutation, one-quarter (103/404 cycles) for six other frequent mutations and only a few for the remaining 45 CFTR mutations. There were 44 PGD cycles performed for 25 CF-affected homozygous or double-heterozygous CF patients (18 male and seven female partners), which involved testing simultaneously for three mutations, resulting in birth of 13 healthy CF-free children and no misdiagnosis. PGD was also performed for six couples at a combined risk of producing offspring with CF and another genetic disorder. Concomitant testing for CFTR and other mutations resulted in birth of six healthy children, free of both CF and another genetic disorder in all but one cycle. A total of 96 PGD cycles for CF were performed with simultaneous aneuploidy testing, including microarray-based 24-chromosome analysis, as a comprehensive PGD for two or more conditions in the same biopsy material.

  15. The influence of dispersing additive on the paraffin crystallization in model systems

    NASA Astrophysics Data System (ADS)

    Gorshkov, A. M.; Tien Thang, Pham; Shishmina, L. V.; Chekantseva, L. V.

    2015-11-01

    The work is dedicated to investigation of the influence of dispersing additive on the paraffin crystallization in model systems. A new method to determine the paraffin saturation point of transparent solutions based on the phenomenon of light scattering has been proposed. The linear relationship between the values of critical micelle concentrations of the additive and the quantity of paraffin in solution has been obtained. The influence of the model system composition on the paraffin crystallization has been studied.

  16. Effects of additional food in a delayed predator-prey model.

    PubMed

    Sahoo, Banshidhar; Poria, Swarup

    2015-03-01

    We examine the effects of supplying additional food to predator in a gestation delay induced predator-prey system with habitat complexity. Additional food works in favor of predator growth in our model. Presence of additional food reduces the predatory attack rate to prey in the model. Supplying additional food we can control predator population. Taking time delay as bifurcation parameter the stability of the coexisting equilibrium point is analyzed. Hopf bifurcation analysis is done with respect to time delay in presence of additional food. The direction of Hopf bifurcations and the stability of bifurcated periodic solutions are determined by applying the normal form theory and the center manifold theorem. The qualitative dynamical behavior of the model is simulated using experimental parameter values. It is observed that fluctuations of the population size can be controlled either by supplying additional food suitably or by increasing the degree of habitat complexity. It is pointed out that Hopf bifurcation occurs in the system when the delay crosses some critical value. This critical value of delay strongly depends on quality and quantity of supplied additional food. Therefore, the variation of predator population significantly effects the dynamics of the model. Model results are compared with experimental results and biological implications of the analytical findings are discussed in the conclusion section.

  17. Calibration of Uncertainty Analysis of the SWAT Model Using Genetic Algorithms and Bayesian Model Averaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, the Genetic Algorithms (GA) and Bayesian model averaging (BMA) were combined to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this hybrid method, several SWAT models with different structures are first selected; next GA i...

  18. An Intelligent Model for Pairs Trading Using Genetic Algorithms

    PubMed Central

    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. PMID:26339236

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

    PubMed

    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. PMID:26339236

  20. Genetic dissection of a model complex trait using the Drosophila Synthetic Population Resource

    PubMed Central

    King, Elizabeth G.; Merkes, Chris M.; McNeil, Casey L.; Hoofer, Steven R.; Sen, Saunak; Broman, Karl W.; Long, Anthony D.; Macdonald, Stuart J.

    2012-01-01

    Genetic dissection of complex, polygenic trait variation is a key goal of medical and evolutionary genetics. Attempts to identify genetic variants underlying complex traits have been plagued by low mapping resolution in traditional linkage studies, and an inability to identify variants that cumulatively explain the bulk of standing genetic variation in genome-wide association studies (GWAS). Thus, much of the heritability remains unexplained for most complex traits. Here we describe a novel, freely available resource for the Drosophila community consisting of two sets of recombinant inbred lines (RILs), each derived from an advanced generation cross between a different set of eight highly inbred, completely resequenced founders. The Drosophila Synthetic Population Resource (DSPR) has been designed to combine the high mapping resolution offered by multiple generations of recombination, with the high statistical power afforded by a linkage-based design. Here, we detail the properties of the mapping panel of >1600 genotyped RILs, and provide an empirical demonstration of the utility of the approach by genetically dissecting alcohol dehydrogenase (ADH) enzyme activity. We confirm that a large fraction of the variation in this classic quantitative trait is due to allelic variation at the Adh locus, and additionally identify several previously unknown modest-effect trans-acting QTL (quantitative trait loci). Using a unique property of multiparental linkage mapping designs, for each QTL we highlight a relatively small set of candidate causative variants for follow-up work. The DSPR represents an important step toward the ultimate goal of a complete understanding of the genetics of complex traits in the Drosophila model system. PMID:22496517

  1. Exploring Middle School Students' Understanding of Three Conceptual Models in Genetics

    NASA Astrophysics Data System (ADS)

    Bresler Freidenreich, Hava; Golan Duncan, Ravit; Shea, Nicole

    2011-11-01

    Genetics is the cornerstone of modern biology and a critical aspect of scientific literacy. Research has shown, however, that many high school graduates lack fundamental understandings in genetics necessary to make informed decisions about issues and emerging technologies in this domain, such as genetic screening, genetically modified foods, etc. Genetic literacy entails understanding three interrelated models: a genetic model that describes patterns of genetic inheritance, a meiotic model that describes the process by which genes are segregated into sex cells, and a molecular model that describes the mechanisms that link genotypes to phenotypes within an individual. Currently, much of genetics instruction, especially in terms of the molecular model, occurs at the high school level, and we know little about the ways in which middle school students can reason about these models. Furthermore, we do not know the extent to which carefully designed instruction can help younger students develop coherent and interrelated understandings in genetics. In this paper, we discuss a research study aimed at elucidating middle school students' abilities to reason about the three genetic models. As part of our research, we designed an eight-week inquiry unit that was implemented in a combined sixth- to eighth-grade science classroom. We describe our instructional design and report results based on an analysis of written assessments, clinical interviews, and artifacts of the unit. Our findings suggest that middle school students are able to successfully reason about all three genetic models.

  2. Modeling variation in early life mortality in the western lowland gorilla: Genetic, maternal and other effects.

    PubMed

    Ahsan, Monica H; Blomquist, Gregory E

    2015-06-01

    Uncovering sources of variation in gorilla infant mortality informs conservation and life history research efforts. The international studbook for the western lowland gorilla provides information on a sample of captive gorillas large enough for which to analyze genetic, maternal, and various other effects on early life mortality in this critically endangered species. We assess the importance of variables such as sex, maternal parity, paternal age, and hand rearing with regard to infant survival. We also quantify the proportions of variation in mortality influenced by heritable variation and maternal effects from these pedigree and survival data using variance component estimation. Markov chain Monte Carlo simulations of generalized linear mixed models produce variance component distributions in an animal model framework that employs all pedigree information. Two models, one with a maternal identity component and one with both additive genetic and maternal identity components, estimate variance components for different age classes during the first 2 years of life. This is informative of the extent to which mortality risk factors change over time during gorilla infancy. Our results indicate that gorilla mortality is moderately heritable with the strongest genetic influence just after birth. Maternal effects are most important during the first 6 months of life. Interestingly, hand-reared infants have lower mortality for the first 6 months of life. Aside from hand rearing, we found other predictors commonly used in studies of primate infant mortality to have little influence in these gorilla data.

  3. Modeling variation in early life mortality in the western lowland gorilla: Genetic, maternal and other effects.

    PubMed

    Ahsan, Monica H; Blomquist, Gregory E

    2015-06-01

    Uncovering sources of variation in gorilla infant mortality informs conservation and life history research efforts. The international studbook for the western lowland gorilla provides information on a sample of captive gorillas large enough for which to analyze genetic, maternal, and various other effects on early life mortality in this critically endangered species. We assess the importance of variables such as sex, maternal parity, paternal age, and hand rearing with regard to infant survival. We also quantify the proportions of variation in mortality influenced by heritable variation and maternal effects from these pedigree and survival data using variance component estimation. Markov chain Monte Carlo simulations of generalized linear mixed models produce variance component distributions in an animal model framework that employs all pedigree information. Two models, one with a maternal identity component and one with both additive genetic and maternal identity components, estimate variance components for different age classes during the first 2 years of life. This is informative of the extent to which mortality risk factors change over time during gorilla infancy. Our results indicate that gorilla mortality is moderately heritable with the strongest genetic influence just after birth. Maternal effects are most important during the first 6 months of life. Interestingly, hand-reared infants have lower mortality for the first 6 months of life. Aside from hand rearing, we found other predictors commonly used in studies of primate infant mortality to have little influence in these gorilla data. PMID:25809396

  4. An uncertain revolution: why the rise of a genetic model of mental illness has not increased tolerance.

    PubMed

    Schnittker, Jason

    2008-11-01

    This study uses the 2006 replication of the 1996 General Social Survey Mental Health Module to explore trends in public beliefs about mental illness in the USA. Drawing on three models related to the framing of genetic arguments in popular media, the study attempts to address why tolerance of the mentally ill has not increased, despite the growing popularity of a biomedical view. The key to resolving this paradox lies in understanding how genetic arguments interact with other beliefs about mental illness, as well as the complex ideational implications of genetic frameworks. Genetic arguments have contingent relationships with tolerance. When applied to schizophrenia, genetic arguments are positively associated with fears regarding violence. Indeed, in this regard, attributing schizophrenia to genes is no different from attributing schizophrenia to bad character. However, when applied to depression, genetic arguments are positively associated with social acceptance. In addition to these contingencies, genetic explanations have discontinuous relationships with beliefs regarding treatment. Although genetic arguments are positively associated with recommending medical treatment, they are not associated with the perceived likelihood of improvement. The net result of these assorted relationships is little change in overall levels of tolerance over time. Because of the blunt nature of the forces propelling a biomedical view--including the growing popularity of psychiatric medications--altering beliefs about the etiology of mental illness is unlikely, on its own, to increase tolerance. PMID:18703264

  5. The severity of retinal pathology in homozygous Crb1rd8/rd8 mice is dependent on additional genetic factors.

    PubMed

    Luhmann, Ulrich F O; Carvalho, Livia S; Holthaus, Sophia-Martha Kleine; Cowing, Jill A; Greenaway, Simon; Chu, Colin J; Herrmann, Philipp; Smith, Alexander J; Munro, Peter M G; Potter, Paul; Bainbridge, James W B; Ali, Robin R

    2015-01-01

    Understanding phenotype-genotype correlations in retinal degeneration is a major challenge. Mutations in CRB1 lead to a spectrum of autosomal recessive retinal dystrophies with variable phenotypes suggesting the influence of modifying factors. To establish the contribution of the genetic background to phenotypic variability associated with the Crb1(rd8/rd8) mutation, we compared the retinal pathology of Crb1(rd8/rd8)/J inbred mice with that of two Crb1(rd8/rd8) lines backcrossed with C57BL/6JOlaHsd mice. Topical endoscopic fundal imaging and scanning laser ophthalmoscopy fundus images of all three Crb1(rd8/rd8) lines showed a significant increase in the number of inferior retinal lesions that was strikingly variable between the lines. Optical coherence tomography, semithin, ultrastructural morphology and assessment of inflammatory and vascular marker by immunohistochemistry and quantitative reverse transcriptase-polymerase chain reaction revealed that the lesions were associated with photoreceptor death, Müller and microglia activation and telangiectasia-like vascular remodelling-features that were stable in the inbred, variable in the second, but virtually absent in the third Crb1(rd8/rd8) line, even at 12 months of age. This suggests that the Crb1(rd8/rd8) mutation is necessary, but not sufficient for the development of these degenerative features. By whole-genome SNP analysis of the genotype-phenotype correlation, a candidate region on chromosome 15 was identified. This may carry one or more genetic modifiers for the manifestation of the retinal pathology associated with mutations in Crb1. This study also provides insight into the nature of the retinal vascular lesions that likely represent a clinical correlate for the formation of retinal telangiectasia or Coats-like vasculopathy in patients with CRB1 mutations that are thought to depend on such genetic modifiers.

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

    PubMed

    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. PMID:17098715

  7. Testing a Gender Additive Model: The Role of Body Image in Adolescent Depression

    ERIC Educational Resources Information Center

    Bearman, Sarah Kate; Stice, Eric

    2008-01-01

    Despite consistent evidence that adolescent girls are at greater risk of developing depression than adolescent boys, risk factor models that account for this difference have been elusive. The objective of this research was to examine risk factors proposed by the "gender additive" model of depression that attempts to partially explain the increased…

  8. Quantitative genetic analysis of brain size variation in sticklebacks: support for the mosaic model of brain evolution

    PubMed Central

    Noreikiene, Kristina; Herczeg, Gábor; Gonda, Abigél; Balázs, Gergely; Husby, Arild; Merilä, Juha

    2015-01-01

    The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h2 = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks. PMID:26108633

  9. Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

    PubMed

    Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

    2016-09-01

    Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that

  10. Genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The genus Capsicum represents one of several well characterized Solanaceous genera. A wealth of classical and molecular genetics research is available for the genus. Information gleaned from its cultivated relatives, tomato and potato, provide further insight for basic and applied studies. Early ...

  11. Genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Maintaining genetic variation in wild populations of Arctic organisms is fundamental to the long-term persistence of high latitude biodiversity. Variability is important because it provides options for species to respond to changing environmental conditions and novel challenges such as emerging path...

  12. A new perspective on dark energy modeling via genetic algorithms

    NASA Astrophysics Data System (ADS)

    Nesseris, Savvas; García-Bellido, Juan

    2012-11-01

    We use Genetic Algorithms to extract information from several cosmological probes, such as the type Ia supernovae (SnIa), the Baryon Acoustic Oscillations (BAO) and the growth rate of matter perturbations. This is done by implementing a model independent and bias-free reconstruction of the various scales and distances that characterize the data, like the luminosity dL(z) and the angular diameter distance dA(z) in the SnIa and BAO data, respectively, or the dependence with redshift of the matter density Ωm(a) in the growth rate data, fσ8(z). These quantities can then be used to reconstruct the expansion history of the Universe, and the resulting Dark Energy (DE) equation of state w(z) in the context of FRW models, or the mass radial function ΩM(r) in LTB models. In this way, the reconstruction is completely independent of our prior bias. Furthermore, we use this method to test the Etherington relation, ie the well-known relation between the luminosity and the angular diameter distance, η≡dL(z)/(1+z)2dA(z), which is equal to 1 in metric theories of gravity. We find that the present data seem to suggest a 3-σ deviation from one at redshifts z ~ 0.5. Finally, we present a novel way, within the Genetic Algorithm paradigm, to analytically estimate the errors on the reconstructed quantities by calculating a Path Integral over all possible functions that may contribute to the likelihood. We show that this can be done regardless of the data being correlated or uncorrelated with each other and we also explicitly demonstrate that our approach is in good agreement with other error estimation techniques like the Fisher Matrix approach and the Bootstrap Monte Carlo.

  13. A new perspective on dark energy modeling via genetic algorithms

    SciTech Connect

    Nesseris, Savvas; García-Bellido, Juan E-mail: juan.garciabellido@uam.es

    2012-11-01

    We use Genetic Algorithms to extract information from several cosmological probes, such as the type Ia supernovae (SnIa), the Baryon Acoustic Oscillations (BAO) and the growth rate of matter perturbations. This is done by implementing a model independent and bias-free reconstruction of the various scales and distances that characterize the data, like the luminosity d{sub L}(z) and the angular diameter distance d{sub A}(z) in the SnIa and BAO data, respectively, or the dependence with redshift of the matter density Ω{sub m}(a) in the growth rate data, fσ{sub 8}(z). These quantities can then be used to reconstruct the expansion history of the Universe, and the resulting Dark Energy (DE) equation of state w(z) in the context of FRW models, or the mass radial function Ω{sub M}(r) in LTB models. In this way, the reconstruction is completely independent of our prior bias. Furthermore, we use this method to test the Etherington relation, ie the well-known relation between the luminosity and the angular diameter distance, η≡d{sub L}(z)/(1+z){sup 2}d{sub A}(z), which is equal to 1 in metric theories of gravity. We find that the present data seem to suggest a 3-σ deviation from one at redshifts z ∼ 0.5. Finally, we present a novel way, within the Genetic Algorithm paradigm, to analytically estimate the errors on the reconstructed quantities by calculating a Path Integral over all possible functions that may contribute to the likelihood. We show that this can be done regardless of the data being correlated or uncorrelated with each other and we also explicitly demonstrate that our approach is in good agreement with other error estimation techniques like the Fisher Matrix approach and the Bootstrap Monte Carlo.

  14. Genetic analyses of stillbirth in relation to litter size using random regression models.

    PubMed

    Chen, C Y; Misztal, I; Tsuruta, S; Herring, W O; Holl, J; Culbertson, M

    2010-12-01

    Estimates of genetic parameters for number of stillborns (NSB) in relation to litter size (LS) were obtained with random regression models (RRM). Data were collected from 4 purebred Duroc nucleus farms between 2004 and 2008. Two data sets with 6,575 litters for the first parity (P1) and 6,259 litters for the second to fifth parity (P2-5) with a total of 8,217 and 5,066 animals in the pedigree were analyzed separately. Number of stillborns was studied as a trait on sow level. Fixed effects were contemporary groups (farm-year-season) and fixed cubic regression coefficients on LS with Legendre polynomials. Models for P2-5 included the fixed effect of parity. Random effects were additive genetic effects for both data sets with permanent environmental effects included for P2-5. Random effects modeled with Legendre polynomials (RRM-L), linear splines (RRM-S), and degree 0 B-splines (RRM-BS) with regressions on LS were used. For P1, the order of polynomial, the number of knots, and the number of intervals used for respective models were quadratic, 3, and 3, respectively. For P2-5, the same parameters were linear, 2, and 2, respectively. Heterogeneous residual variances were considered in the models. For P1, estimates of heritability were 12 to 15%, 5 to 6%, and 6 to 7% in LS 5, 9, and 13, respectively. For P2-5, estimates were 15 to 17%, 4 to 5%, and 4 to 6% in LS 6, 9, and 12, respectively. For P1, average estimates of genetic correlations between LS 5 to 9, 5 to 13, and 9 to 13 were 0.53, -0.29, and 0.65, respectively. For P2-5, same estimates averaged for RRM-L and RRM-S were 0.75, -0.21, and 0.50, respectively. For RRM-BS with 2 intervals, the correlation was 0.66 between LS 5 to 7 and 8 to 13. Parameters obtained by 3 RRM revealed the nonlinear relationship between additive genetic effect of NSB and the environmental deviation of LS. The negative correlations between the 2 extreme LS might possibly indicate different genetic bases on incidence of stillbirth.

  15. Genetic programming for evolving due-date assignment models in job shop environments.

    PubMed

    Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

    2014-01-01

    Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

  16. The Triple Code Model for Pancreatic Cancer: Crosstalk Among Genetics, Epigenetics, and Nuclear Structure

    PubMed Central

    Lomberk, Gwen A; Urrutia, Raul

    2015-01-01

    Pancreatic adenocarcinoma (PDAC) is a lethal and painful disease, which has become one of the most frequent causes of death by malignant diseases around the world. Unfortunately, for the most part, this disease remains incurable. Significant advances in the field of genetics, particularly during the last two decades, has led to the proposal of a progression model, by which this cancer evolves by the accumulation of mutations and deletions in key oncogenes and tumor suppressor genes. This model has been remarkably useful for the development of tumor markers as well as elegant animal models. In spite of these strengths, this model does not take into consideration concepts and methodologies that have been derived from the field of epigenetics nor studies in the field of nuclear structure and function. Since our laboratory has been long been an advocate of these changes as critical for the pathobiology of pancreatic cancer, in this article, we describe an updated, more comprehensive model, which includes these concepts. With the widespread utilization of next generation sequencing for identifying both genetic and epigenetic changes genome-wide, we believe that the framework of this model will help to further identify and validate not only more but better markers for pancreatic cancer. In addition, as opposed to genetic changes, epigenetic alterations are amenable to pharmacological manipulations, consequently the familiarization with this model will help to better understand the potential beneficial effects of this type of therapy for this disease. Thus, we are optimistic that this new integrated paradigm will contribute to advance this field of research not only from a mechanistic point of view, but also from a translational one. PMID:26315515

  17. Genetically manipulated mouse models of lung disease: potential and pitfalls

    PubMed Central

    Choi, Alexander J. S.; Owen, Caroline A.; Choi, Augustine M. K.

    2012-01-01

    Gene targeting in mice (transgenic and knockout) has provided investigators with an unparalleled armamentarium in recent decades to dissect the cellular and molecular basis of critical pathophysiological states. Fruitful information has been derived from studies using these genetically engineered mice with significant impact on our understanding, not only of specific biological processes spanning cell proliferation to cell death, but also of critical molecular events involved in the pathogenesis of human disease. This review will focus on the use of gene-targeted mice to study various models of lung disease including airways diseases such as asthma and chronic obstructive pulmonary disease, and parenchymal lung diseases including idiopathic pulmonary fibrosis, pulmonary hypertension, pneumonia, and acute lung injury. We will attempt to review the current technological approaches of generating gene-targeted mice and the enormous dataset derived from these studies, providing a template for lung investigators. PMID:22198907

  18. Model suicide vector for containment of genetically engineered microorganisms.

    PubMed

    Bej, A K; Perlin, M H; Atlas, R M

    1988-10-01

    A model suicide vector (pBAP19h), designed for the potential containment of genetically engineered microorganisms, was made by constructing a plasmid with the hok gene, which codes for a lethal polypeptide, under the control of the lac promoter. The vector plasmid also codes for carbenicillin resistance. In the absence of carbenicillin, induction of the hok gene in vitro caused elimination of all detectable cells containing the suicide vector; pBAP19h-free cells of the culture survived and grew exponentially. In the presence of carbenicillin, however, the number of cells containing pBAP19h initially declined after induction of hok but then multiplied exponentially. The surviving cells still had a fully functional hok gene and had apparently developed resistance to the action of the Hok polypeptide. Thus, high selective pressure against the loss of the suicide vector led to a failure of the system. Soil microcosm experiments confirmed the ability of a suicide vector to restrict the growth of a genetically engineered microorganism in the absence of selective pressure against the loss of the plasmid, with 90 to 99% elimination of hok-bearing cells within 24 h of hok induction. However, some pBAP19h-bearing cells survived in the soil microcosms after hok induction. The surviving cells contained an active hok gene but were not capable of normal growth even after elimination of the hok gene; it appears that a mutation that made them Hok resistant also reduced their capacity for membrane functions needed for energy generation and exponential cell growth. Thus, the model suicide vector was shown to be functional in soil as well as in vitro.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:3060017

  19. Stress, glucocorticoids and absences in a genetic epilepsy model.

    PubMed

    Tolmacheva, Elena A; Oitzl, Melly S; van Luijtelaar, Gilles

    2012-05-01

    Although stress can alter the susceptibility of patients and animal models to convulsive epilepsy, little is known about the role of stress and glucocorticoid hormones in absence epilepsy. We measured the basal and acute stress-induced (foot-shocks: FS) concentrations of corticosterone in WAG/Rij rats, non-epileptic inbred ACI rats and outbred Wistar rats. The WAG/Rij strain is a genetic model for absence epilepsy and comorbidity for depression, which originates from the population of Wistar rats and, therefore, shares their genetic background. In a separate experiment, WAG/Rij rats were exposed to FS on three consecutive days. Electroencephalograms (EEGs) were recorded before and after FS, and the number of absence seizures (spike-wave-discharges, SWDs) was quantified. Both WAG/Rij rats and ACI rats exhibited elevated basal levels of corticosterone and a rapid corticosterone increase in response to acute stress. The WAG/Rij rats also displayed the most rapid normalization of corticosterone during the recovery phase compared to that of ACI and Wistar rats. FS had a biphasic effect on SWDs; an initial suppression was followed by an aggravation of the SWDs. By the third day, this aggravation of seizures was present in the hour preceding FS. This increase in SWDs may arise from anticipatory stress about the upcoming FS. Together, these results suggest that the distinct secretion profile of corticosterone found in WAG/Rij rats may contribute to the severity of the epileptic phenotype. Although the acute stressor results in an initial suppression of SWDs followed by an increase in SWDs, stress prior to a predictable negative event aggravates absences.

  20. Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.

    PubMed

    Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing

    2016-04-01

    Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study. PMID:27027515

  1. Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.

    PubMed

    Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing

    2016-04-01

    Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study.

  2. Comparison of different models for genetic evaluation of egg weight in Mazandaran fowl.

    PubMed

    Zamani, P; Jasouri, M; Moradi, M R

    2015-01-01

    1. The aim of the present study was to compare different models to estimate variance components for egg weight (EW) in laying hens. 2. The data set included 67 542 EW records of 18 245 Mazandaran hens at 24, 28, 30, 32 and 84 weeks of age, during 19 consecutive generations. Variance components were estimated using multi-trait, repeatability, fixed regression and random regression models (MTM, RM, FRM and RRM, respectively) by Average Information-Restricted Maximum Likelihood algorithm (AI-REML). The models were compared based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). 3. The MTM was the best model followed by the Legendre RRMs. A RRM with 2nd degree of fit for fixed regression and 3(rd) and 2(nd) degrees of fit for random regressions of direct additive genetic and permanent environmental effects, respectively, was the best RRM. The FRM and RM were not proper models to fit the data. However, nesting curves within contemporary groups improved the fit of FRM. 4. Heritability estimates for EW by MTM (0.06-0.41) were close to the estimates obtained by the best RRM (0.09-0.45). In both MTM and RRM, positive genetic correlations were estimated for EW records at different ages, with higher correlations for adjacent records. 5. The results suggest that MTM is the best model for EW data, at least when the records are taken at relatively few age points. Though selection based on EW at higher ages might be more precise, 30 or 32 weeks of age could be considered as the most appropriate time points for selection on EW to maximise genetic improvement per time unit.

  3. Nature and nurture: environmental influences on a genetic rat model of depression.

    PubMed

    Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

    2016-01-01

    In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or 'nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, 'trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms. PMID:27023176

  4. Nature and nurture: environmental influences on a genetic rat model of depression

    PubMed Central

    Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

    2016-01-01

    In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or ‘nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, ‘trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms. PMID:27023176

  5. Generalized additive modeling with implicit variable selection by likelihood-based boosting.

    PubMed

    Tutz, Gerhard; Binder, Harald

    2006-12-01

    The use of generalized additive models in statistical data analysis suffers from the restriction to few explanatory variables and the problems of selection of smoothing parameters. Generalized additive model boosting circumvents these problems by means of stagewise fitting of weak learners. A fitting procedure is derived which works for all simple exponential family distributions, including binomial, Poisson, and normal response variables. The procedure combines the selection of variables and the determination of the appropriate amount of smoothing. Penalized regression splines and the newly introduced penalized stumps are considered as weak learners. Estimates of standard deviations and stopping criteria, which are notorious problems in iterative procedures, are based on an approximate hat matrix. The method is shown to be a strong competitor to common procedures for the fitting of generalized additive models. In particular, in high-dimensional settings with many nuisance predictor variables it performs very well. PMID:17156269

  6. Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift.

    PubMed

    Reali, Florencia; Griffiths, Thomas L

    2010-02-01

    Scientists studying how languages change over time often make an analogy between biological and cultural evolution, with words or grammars behaving like traits subject to natural selection. Recent work has exploited this analogy by using models of biological evolution to explain the properties of languages and other cultural artefacts. However, the mechanisms of biological and cultural evolution are very different: biological traits are passed between generations by genes, while languages and concepts are transmitted through learning. Here we show that these different mechanisms can have the same results, demonstrating that the transmission of frequency distributions over variants of linguistic forms by Bayesian learners is equivalent to the Wright-Fisher model of genetic drift. This simple learning mechanism thus provides a justification for the use of models of genetic drift in studying language evolution. In addition to providing an explicit connection between biological and cultural evolution, this allows us to define a 'neutral' model that indicates how languages can change in the absence of selection at the level of linguistic variants. We demonstrate that this neutral model can account for three phenomena: the s-shaped curve of language change, the distribution of word frequencies, and the relationship between word frequencies and extinction rates.

  7. A genetic algorithm based molecular modeling technique for RNA stem-loop structures.

    PubMed Central

    Ogata, H; Akiyama, Y; Kanehisa, M

    1995-01-01

    A new modeling technique for arriving at the three dimensional (3-D) structure of an RNA stem-loop has been developed based on a conformational search by a genetic algorithm and the following refinement by energy minimization. The genetic algorithm simultaneously optimizes a population of conformations in the predefined conformational space and generates 3-D models of RNA. The fitness function to be optimized by the algorithm has been defined to reflect the satisfaction of known conformational constraints. In addition to a term for distance constraints, the fitness function contains a term to constrain each local conformation near to a prepared template conformation. The technique has been applied to the two loops of tRNA, the anticodon loop and the T-loop, and has found good models with small root mean square deviations from the crystal structure. Slightly different models have also been found for the anticodon loop. The analysis of a collection of alternative models obtained has revealed statistical features of local variations at each base position. Images PMID:7533901

  8. Plants with genetically modified events combined by conventional breeding: an assessment of the need for additional regulatory data.

    PubMed

    Pilacinski, W; Crawford, A; Downey, R; Harvey, B; Huber, S; Hunst, P; Lahman, L K; MacIntosh, S; Pohl, M; Rickard, C; Tagliani, L; Weber, N

    2011-01-01

    Crop varieties with multiple GM events combined by conventional breeding have become important in global agriculture. The regulatory requirements in different countries for such products vary considerably, placing an additional burden on regulatory agencies in countries where the submission of additional data is required and delaying the introduction of innovative products to meet agricultural needs. The process of conventional plant breeding has predictably provided safe food and feed products both historically and in the modern era of plant breeding. Thus, previously approved GM events that have been combined by conventional plant breeding and contain GM traits that are not likely to interact in a manner affecting safety should be considered to be as safe as their conventional counterparts. Such combined GM event crop varieties should require little, if any, additional regulatory data to meet regulatory requirements.

  9. Genetic counselor perceptions of genetic counseling session goals: a validation study of the reciprocal-engagement model.

    PubMed

    Hartmann, Julianne E; Veach, Patricia McCarthy; MacFarlane, Ian M; LeRoy, Bonnie S

    2015-04-01

    Although some researchers have attempted to define genetic counseling practice goals, no study has obtained consensus about the goals from a large sample of genetic counselors. The Reciprocal-Engagement Model (REM; McCarthy Veach, Bartels & LeRoy, 2007) articulates 17 goals of genetic counseling practice. The present study investigated whether these goals could be generalized as a model of practice, as determined by a larger group of clinical genetic counselors. Accordingly, 194 genetic counselors were surveyed regarding their opinions about the importance of each goal and their perceptions of how frequently they achieve each goal. Mean importance ratings suggest they viewed every goal as important. Factor analysis of the 17 goals yielded four factors: Understanding and Appreciation, Support and Guidance, Facilitative Decision-Making, and Patient-Centered Education. Patient-Centered Education and Facilitative Decision-Making goals received the highest mean importance ratings. Mean frequency ratings were consistently lower than importance ratings, suggesting genetic counseling goals may be difficult to achieve and/or not applicable in all situations. A number of respondents provided comments about the REM goals that offer insight into factors related to implementing the goals in clinical practice. This study presents preliminary evidence concerning the validity of the goals component of the REM.

  10. A genetic model for gallbladder carcinogenesis and its dissemination

    PubMed Central

    Barreto, S. G.; Dutt, A.; Chaudhary, A.

    2014-01-01

    Gallbladder cancer, although regarded as the most common malignancy of the biliary tract, continues to be associated with a dismal overall survival even in the present day. While complete surgical removal of the tumour offers a good chance of cure, only a fraction of the patients are amenable to curative surgery owing to their delayed presentation. Moreover, the current contribution of adjuvant therapies towards prolonging survival is marginal, at best. Thus, understanding the biology of the disease will not only enable a better appreciation of the pathways of progression but also facilitate the development of an accurate genetic model for gallbladder carcinogenesis and dissemination. This review provides an updated, evidence-based model of the pathways of carcinogenesis in gallbladder cancer and its dissemination. The model proposed could serve as the scaffolding for elucidation of the molecular mechanisms involved in gallbladder carcinogenesis. A better understanding of the pathways involved in gallbladder tumorigenesis will serve to identify patients at risk for the cancer (and who thus could be offered prophylactic cholecystectomy) as well as aid oncologists in planning the most suitable treatment for a particular patient, thereby setting us on the vanguard of transforming the current treatment paradigm for gallbladder cancer. PMID:24705974

  11. Genetic Models for the Study of Luteinizing Hormone Receptor Function

    PubMed Central

    Narayan, Prema

    2015-01-01

    The luteinizing hormone/chorionic gonadotropin receptor (LHCGR) is essential for fertility in men and women. LHCGR binds luteinizing hormone (LH) as well as the highly homologous chorionic gonadotropin. Signaling from LHCGR is required for steroidogenesis and gametogenesis in males and females and for sexual differentiation in the male. The importance of LHCGR in reproductive physiology is underscored by the large number of naturally occurring inactivating and activating mutations in the receptor that result in reproductive disorders. Consequently, several genetically modified mouse models have been developed for the study of LHCGR function. They include targeted deletion of LH and LHCGR that mimic inactivating mutations in hormone and receptor, expression of a constitutively active mutant in LHCGR that mimics activating mutations associated with familial male-limited precocious puberty and transgenic models of LH and hCG overexpression. This review summarizes the salient findings from these models and their utility in understanding the physiological and pathological consequences of loss and gain of function in LHCGR signaling. PMID:26483755

  12. Exploring the possibility of modeling a genetic counseling guideline using agile methodology.

    PubMed

    Choi, Jeeyae

    2013-01-01

    Increased demand of genetic counseling services heightened the necessity of a computerized genetic counseling decision support system. In order to develop an effective and efficient computerized system, modeling of genetic counseling guideline is an essential step. Throughout this pilot study, Agile methodology with United Modeling Language (UML) was utilized to model a guideline. 13 tasks and 14 associated elements were extracted. Successfully constructed conceptual class and activity diagrams revealed that Agile methodology with UML was a suitable tool to modeling a genetic counseling guideline.

  13. Defining Our Clinical Practice: The Identification of Genetic Counseling Outcomes Utilizing the Reciprocal Engagement Model.

    PubMed

    Redlinger-Grosse, Krista; Veach, Patricia McCarthy; Cohen, Stephanie; LeRoy, Bonnie S; MacFarlane, Ian M; Zierhut, Heather

    2016-04-01

    The need for evidence-based medicine, including comparative effectiveness studies and patient-centered outcomes research, has become a major healthcare focus. To date, a comprehensive list of genetic counseling outcomes, as espoused by genetic counselors, has not been established and thus, identification of outcomes unique to genetic counseling services has become a priority for the National Society of Genetic Counselors (NSGC). The purpose of this study was to take a critical first step at identifying a more comprehensive list of genetic counseling outcomes. This paper describes the results of a focus group study using the Reciprocal-Engagement Model (REM) as a framework to characterize patient-centered outcomes of genetic counseling clinical practice. Five focus groups were conducted with 27 peer nominated participants who were clinical genetic counselors, genetic counseling program directors, and/or outcomes researchers in genetic counseling. Members of each focus group were asked to identify genetic counseling outcomes for four to five of the 17 goals of the REM. A theory-driven, thematic analysis of focus group data yielded 194 genetic counseling outcomes across the 17 goals. Participants noted some concerns about how genetic counseling outcomes will be measured and evaluated given varying stakeholders and the long-term nature of genetic concerns. The present results provide a list of outcomes for use in future genetic counseling outcomes research and for empirically-supported clinical interventions.

  14. Vector generalized additive models for extreme rainfall data analysis (study case rainfall data in Indramayu)

    NASA Astrophysics Data System (ADS)

    Utami, Eka Putri Nur; Wigena, Aji Hamim; Djuraidah, Anik

    2016-02-01

    Rainfall pattern are good indicators for potential disasters. Global Circulation Model (GCM) contains global scale information that can be used to predict the rainfall data. Statistical downscaling (SD) utilizes the global scale information to make inferences in the local scale. Essentially, SD can be used to predict local scale variables based on global scale variables. SD requires a method to accommodate non linear effects and extreme values. Extreme value Theory (EVT) can be used to analyze the extreme value. One of methods to identify the extreme events is peak over threshold that follows Generalized Pareto Distribution (GPD). The vector generalized additive model (VGAM) is an extension of the generalized additive model. It is able to accommodate linear or nonlinear effects by involving more than one additive predictors. The advantage of VGAM is to handle multi response models. The key idea of VGAM are iteratively reweighted least square for maximum likelihood estimation, penalized smoothing, fisher scoring and additive models. This works aims to analyze extreme rainfall data in Indramayu using VGAM. The results show that the VGAM with GPD is able to predict extreme rainfall data accurately. The prediction in February is very close to the actual value at quantile 75.

  15. Present-day genetic structure of Atlantic salmon (Salmo salar) in Icelandic rivers and ice-cap retreat models.

    PubMed

    Olafsson, Kristinn; Pampoulie, Christophe; Hjorleifsdottir, Sigridur; Gudjonsson, Sigurdur; Hreggvidsson, Gudmundur O

    2014-01-01

    Due to an improved understanding of past climatological conditions, it has now become possible to study the potential concordance between former climatological models and present-day genetic structure. Genetic variability was assessed in 26 samples from different rivers of Atlantic salmon in Iceland (total of 2,352 individuals), using 15 microsatellite loci. F-statistics revealed significant differences between the majority of the populations that were sampled. Bayesian cluster analyses using both prior information and no prior information on sampling location revealed the presence of two distinguishable genetic pools - namely, the Northern (Group 1) and Southern (Group 2) regions of Iceland. Furthermore, the random permutation of different allele sizes among allelic states revealed a significant mutational component to the genetic differentiation at four microsatellite loci (SsaD144, Ssa171, SSsp2201 and SsaF3), and supported the proposition of a historical origin behind the observed variation. The estimated time of divergence, using two different ABC methods, suggested that the observed genetic pattern originated from between the Last Glacial Maximum to the Younger Dryas, which serves as additional evidence of the relative immaturity of Icelandic fish populations, on account of the re-colonisation of this young environment following the Last Glacial Maximum. Additional analyses suggested the presence of several genetic entities which were likely to originate from the original groups detected. PMID:24498283

  16. Teaching Human Genetics with Mustard: Rapid Cycling "Brassica rapa" (Fast Plants Type) as a Model for Human Genetics in the Classroom Laboratory

    ERIC Educational Resources Information Center

    Wendell, Douglas L.; Pickard, Dawn

    2007-01-01

    We have developed experiments and materials to model human genetics using rapid cycling "Brassica rapa", also known as Fast Plants. Because of their self-incompatibility for pollination and the genetic diversity within strains, "B. rapa" can serve as a relevant model for human genetics in teaching laboratory experiments. The experiment presented…

  17. GRAVITATIONAL LENS MODELING WITH GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZERS

    SciTech Connect

    Rogers, Adam; Fiege, Jason D.

    2011-02-01

    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 {chi}{sup 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 {chi}{sup 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.

  18. Integrated reservoir characterization: Improvement in heterogeneities stochastic modelling by integration of additional external constraints

    SciTech Connect

    Doligez, B.; Eschard, R.; Geffroy, F.

    1997-08-01

    The classical approach to construct reservoir models is to start with a fine scale geological model which is informed with petrophysical properties. Then scaling-up techniques allow to obtain a reservoir model which is compatible with the fluid flow simulators. Geostatistical modelling techniques are widely used to build the geological models before scaling-up. These methods provide equiprobable images of the area under investigation, which honor the well data, and which variability is the same than the variability computed from the data. At an appraisal phase, when few data are available, or when the wells are insufficient to describe all the heterogeneities and the behavior of the field, additional constraints are needed to obtain a more realistic geological model. For example, seismic data or stratigraphic models can provide average reservoir information with an excellent areal coverage, but with a poor vertical resolution. New advances in modelisation techniques allow now to integrate this type of additional external information in order to constrain the simulations. In particular, 2D or 3D seismic derived information grids, or sand-shale ratios maps coming from stratigraphic models can be used as external drifts to compute the geological image of the reservoir at the fine scale. Examples are presented to illustrate the use of these new tools, their impact on the final reservoir model, and their sensitivity to some key parameters.

  19. Additive genetic variation in resistance traits of an exotic pine species: little evidence for constraints on evolution of resistance against native herbivores

    PubMed Central

    Moreira, X; Zas, R; Sampedro, L

    2013-01-01

    The apparent failure of invasions by alien pines in Europe has been explained by the co-occurrence of native pine congeners supporting herbivores that might easily recognize the new plants as hosts. Previous studies have reported that exotic pines show reduced tolerance and capacity to induce resistance to those native herbivores. We hypothesize that limited genetic variation in resistance to native herbivores and the existence of evolutionary trade-offs between growth and resistance could represent additional potential constraints on the evolution of invasiveness of exotic pines outside their natural range. In this paper, we examined genetic variation for constitutive and induced chemical defences (measured as non-volatile resin in the stem and total phenolics in the needles) and resistance to two major native generalist herbivores of pines in cafeteria bioassays (the phloem-feeder Hylobius abietis and the defoliator Thaumetopoea pityocampa) using half-sib families drawn from a sample of the population of Pinus radiata introduced to Spain in the mid-19th century. We found (i) significant genetic variation, with moderate-to-high narrow-sense heritabilities for both the production of constitutive non-volatile resin and induced total phenolics, and for constitutive resistance against T. pityocampa in bioassays, (ii) no evolutionary trade-offs between plant resistance and growth traits or between the production of different quantitative chemical defences and (iii) a positive genetic correlation between constitutive resistance to the two studied herbivores. Overall, results of our study indicate that the exotic pine P. radiata has limited genetic constraints on the evolution of resistance against herbivores in its introduced range, suggesting that, at least in terms of interactions with these enemies, this pine species has potential to become invasive in the future. PMID:23232833

  20. Smooth-Threshold Multivariate Genetic Prediction with Unbiased Model Selection.

    PubMed

    Ueki, Masao; Tamiya, Gen

    2016-04-01

    We develop a new genetic prediction method, smooth-threshold multivariate genetic prediction, using single nucleotide polymorphisms (SNPs) data in genome-wide association studies (GWASs). Our method consists of two stages. At the first stage, unlike the usual discontinuous SNP screening as used in the gene score method, our method continuously screens SNPs based on the output from standard univariate analysis for marginal association of each SNP. At the second stage, the predictive model is built by a generalized ridge regression simultaneously using the screened SNPs with SNP weight determined by the strength of marginal association. Continuous SNP screening by the smooth thresholding not only makes prediction stable but also leads to a closed form expression of generalized degrees of freedom (GDF). The GDF leads to the Stein's unbiased risk estimation (SURE), which enables data-dependent choice of optimal SNP screening cutoff without using cross-validation. Our method is very rapid because computationally expensive genome-wide scan is required only once in contrast to the penalized regression methods including lasso and elastic net. Simulation studies that mimic real GWAS data with quantitative and binary traits demonstrate that the proposed method outperforms the gene score method and genomic best linear unbiased prediction (GBLUP), and also shows comparable or sometimes improved performance with the lasso and elastic net being known to have good predictive ability but with heavy computational cost. Application to whole-genome sequencing (WGS) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) exhibits that the proposed method shows higher predictive power than the gene score and GBLUP methods.

  1. Toward a genetically-informed model of borderline personality disorder.

    PubMed

    Livesley, John

    2008-02-01

    This article describes a conceptual framework for describing borderline personality disorder (BPD) based on empirical studies of the phenotypic structure and genetic architecture of personality. The proposed phenotype has 2 components: (1) a description of core self and interpersonal pathology-the defining features of personality disorder-as these features are expressed in the disorder; and (2) a set of traits based on the anxious-dependent or emotional dysregulation factor of the four-factor model of PD. Four kinds of traits are described: emotional (anxiousness, emotional reactivity, emotional intensity, and pessimistic-anhedonia), interpersonal (submissiveness, insecure attachment, social apprehensiveness, and need for approval), cognitive (cognitive dysregulation), and self-harm (behaviors and ideas). Formulation of the phenotype was guided by the conceptualization of personality as a system of interrelated sub-systems. The psychopathology associated with BPD involves most components of the system. The trait structure of the disorder is assumed to reflect the genetic architecture of personality and individual traits are assumed to be based on adaptive mechanisms. It is suggested that borderline traits are organized around the trait of anxiousness and that an important feature of BPD is dysregulation of the threat management system leading to pervasive fearfulness and unstable emotions. The interpersonal traits are assumed to be heritable characteristics that evolved to deal with interpersonal threats that arose as a result of social living. The potential for unstable and conflicted interpersonal relationships that is inherent to the disorder is assumed to result from the interplay between the adaptive structure of personality and psychosocial adversity. The etiology of the disorder is discussed in terms of biological and environmental factors associated with each component of the phenotype.

  2. Experimental model and analytic solution for real-time observation of vehicle's additional steer angle

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaolong; Li, Liang; Pan, Deng; Cao, Chengmao; Song, Jian

    2014-03-01

    The current research of real-time observation for vehicle roll steer angle and compliance steer angle(both of them comprehensively referred as the additional steer angle in this paper) mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle's roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ɛ-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system(ESC). The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model's generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal (the magnitude up to 1°), followed by the longitudinal acceleration-deceleration and the road wave amplitude (the magnitude up to 0.3°). Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC. This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.

  3. Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models.

    PubMed

    Baeder, Desiree Y; Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens; Regoes, Roland R

    2016-05-26

    Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials.This article is part of the themed issue 'Evolutionary ecology of arthropod antimicrobial peptides'. PMID:27160596

  4. Molecular genetics and animal models in autistic disorder.

    PubMed

    Andres, Christian

    2002-01-01

    Autistic disorder is a behavioural syndrome beginning before the age of 3 years and lasting over the whole lifetime. It is characterised by impaired communication, impaired social interactions, and repetitive interests and behaviour. The prevalence is about 7/10,000 taking a restrictive definition and more than 1/500 with a broader definition, including all the pervasive developmental disorders. The importance of genetic factors has been highlighted by epidemiological studies showing that autistic disorder is one of the most genetic neuropsychiatric diseases. The relative risk of first relatives is about 100-fold higher than the risk in the normal population and the concordance in monozygotic twin is about 60%. Different strategies have been applied on the track of susceptibility genes. The systematic search of linked loci led to contradictory results, in part due to the heterogeneity of the clinical definitions, to the differences in the DNA markers, and to the different methods of analysis used. An oversimplification of the inferred model is probably also cause of our disappointment. More work is necessary to give a clearer picture. One region emerges more frequently: the long arm of chromosome 7. Several candidate genes have been studied and some gave indications of association: the Reelin gene and the Wnt2 gene. Cytogenetical abnormalities are frequent at 15q11-13, the region of the Angelman and Prader-Willi syndrome. Imprinting plays an important role in this region, no candidate gene has been identified in autism. Biochemical abnormalities have been found in the serotonin system. Association and linkage studies gave no consistent results with some serotonin receptors and in the transporter, although it seems interesting to go further in the biochemical characterisation of the serotonin transporter activity, particularly in platelets, easily accessible. Two monogenic diseases have been associated with autistic disorder: tuberous sclerosis and fragile X. A

  5. Three-dimensional inverse modelling of magnetic anomaly sources based on a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Montesinos, Fuensanta G.; Blanco-Montenegro, Isabel; Arnoso, José

    2016-04-01

    We present a modelling method to estimate the 3-D geometry and location of homogeneously magnetized sources from magnetic anomaly data. As input information, the procedure needs the parameters defining the magnetization vector (intensity, inclination and declination) and the Earth's magnetic field direction. When these two vectors are expected to be different in direction, we propose to estimate the magnetization direction from the magnetic map. Then, using this information, we apply an inversion approach based on a genetic algorithm which finds the geometry of the sources by seeking the optimum solution from an initial population of models in successive iterations through an evolutionary process. The evolution consists of three genetic operators (selection, crossover and mutation), which act on each generation, and a smoothing operator, which looks for the best fit to the observed data and a solution consisting of plausible compact sources. The method allows the use of non-gridded, non-planar and inaccurate anomaly data and non-regular subsurface partitions. In addition, neither constraints for the depth to the top of the sources nor an initial model are necessary, although previous models can be incorporated into the process. We show the results of a test using two complex synthetic anomalies to demonstrate the efficiency of our inversion method. The application to real data is illustrated with aeromagnetic data of the volcanic island of Gran Canaria (Canary Islands).

  6. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling

    PubMed Central

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-01-01

    Summary The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method. PMID:25061254

  7. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

    PubMed

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-04-01

    The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method. PMID:25061254

  8. Midrapidity inclusive densities in high energy pp collisions in additive quark model

    NASA Astrophysics Data System (ADS)

    Shabelski, Yu. M.; Shuvaev, A. G.

    2016-08-01

    High energy (CERN SPS and LHC) inelastic pp (pbar{p}) scattering is treated in the framework of the additive quark model together with Pomeron exchange theory. We extract the midrapidity inclusive density of the charged secondaries produced in a single quark-quark collision and investigate its energy dependence. Predictions for the π p collisions are presented.

  9. Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

    PubMed Central

    Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

    2012-01-01

    Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

  10. A molecular assessment of the genetic model of spathe color inheritance in Anthurium andraeanum (Hort.).

    PubMed

    Gopaulchan, David; Umaharan, Pathmanathan; Lennon, Adrian M

    2014-03-01

    Past genetic studies have shown three independent loci designated O, R and M control spathe color in Anthurium andraeanum (Hort.). To evaluate the genetic model and to understand the control of anthocyanin biosynthesis at the molecular level, the expression of the anthocyanin biosynthetic genes, CHS, F3H, DFR, ANS and F3'H, was examined at the mRNA and protein levels and correlated to anthocyanin content and spathe color in eight genetically characterized anthurium cultivars representing different states of the O, R and M loci. The results showed that the expression of F3H and ANS was co-regulated by a putative transcription factor encoded by the R locus, and the expression of DFR was regulated by a putative transcription factor encoded by the O locus. White cultivars, which were in the homozygous recessive state for either O or R or both, exhibited reduced expression of the anthocyanin biosynthetic genes and hence had negligible levels of anthocyanin. Cultivars that were mm displayed reduced expression of F3'H suggesting that it may either encode a defective form of the F3'H gene or a regulator that controls its expression. Additionally, a correlation between anthocyanin abundance and the expression of F3'H in the red cultivars suggested that F3'H expression may be a key control point in the regulation of anthocyanin biosynthesis in anthurium and hence plays a major role in influencing the shade intensity in red cultivars. These findings provide evidence in support of the genetic model for color inheritance in the spathe. PMID:24363030

  11. Genetically evolved receptor models: a computational approach to construction of receptor models.

    PubMed

    Walters, D E; Hinds, R M

    1994-08-01

    Given the three-dimensional structure of a receptor site, there are several methods available for designing ligands to occupy the site; frequently, the three-dimensional structure of interesting receptors is not known, however. The GERM program uses a genetic algorithm to produce atomic-level models of receptor sites, based on a small set of known structure-activity relationships. The evolved models show a high correlation between calculated intermolecular energies and bioactivities; they also give reasonable predictions of bioactivity for compounds which were not included in model generation. Such models may serve as starting points for computational or human ligand design efforts. PMID:8057298

  12. Genetically evolved receptor models: a computational approach to construction of receptor models.

    PubMed

    Walters, D E; Hinds, R M

    1994-08-01

    Given the three-dimensional structure of a receptor site, there are several methods available for designing ligands to occupy the site; frequently, the three-dimensional structure of interesting receptors is not known, however. The GERM program uses a genetic algorithm to produce atomic-level models of receptor sites, based on a small set of known structure-activity relationships. The evolved models show a high correlation between calculated intermolecular energies and bioactivities; they also give reasonable predictions of bioactivity for compounds which were not included in model generation. Such models may serve as starting points for computational or human ligand design efforts.

  13. Form Follows Function: A Model for Clinical Supervision of Genetic Counseling Students.

    PubMed

    Wherley, Colleen; Veach, Patricia McCarthy; Martyr, Meredith A; LeRoy, Bonnie S

    2015-10-01

    Supervision plays a vital role in genetic counselor training, yet models describing genetic counseling supervision processes and outcomes are lacking. This paper describes a proposed supervision model intended to provide a framework to promote comprehensive and consistent clinical supervision training for genetic counseling students. Based on the principle "form follows function," the model reflects and reinforces McCarthy Veach et al.'s empirically derived model of genetic counseling practice - the "Reciprocal Engagement Model" (REM). The REM consists of mutually interactive educational, relational, and psychosocial components. The Reciprocal Engagement Model of Supervision (REM-S) has similar components and corresponding tenets, goals, and outcomes. The 5 REM-S tenets are: Learning and applying genetic information are key; Relationship is integral to genetic counseling supervision; Student autonomy must be supported; Students are capable; and Student emotions matter. The REM-S outcomes are: Student understands and applies information to independently provide effective services, develop professionally, and engage in self-reflective practice. The 16 REM-S goals are informed by the REM of genetic counseling practice and supported by prior literature. A review of models in medicine and psychology confirms the REM-S contains supervision elements common in healthcare fields, while remaining unique to genetic counseling. The REM-S shows promise for enhancing genetic counselor supervision training and practice and for promoting research on clinical supervision. The REM-S is presented in detail along with specific examples and training and research suggestions.

  14. Are mouse models of human mycobacterial diseases relevant? Genetics says: ‘yes!’

    PubMed Central

    Apt, Alexander S

    2011-01-01

    Relevance and accuracy of experimental mouse models of tuberculosis (TB) are the subject of constant debate. This article briefly reviews genetic aspects of this problem and provides a few examples of mycobacterial diseases with similar or identical genetic control in mice and humans. The two species display more similarities than differences regarding both genetics of susceptibility/severity of mycobacterial diseases and the networks of protective and pathological immune reactions. In the opinion of the author, refined mouse models of mycobacterial diseases are extremely useful for modelling the corresponding human conditions, if genetic diversity is taken into account. PMID:21896006

  15. Modeling Longitudinal Data with Generalized Additive Models: Applications to Single-Case Designs

    ERIC Educational Resources Information Center

    Sullivan, Kristynn J.; Shadish, William R.

    2013-01-01

    Single case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time both in the presence and absence of treatment. For a variety of reasons, interest in the statistical analysis and meta-analysis of these designs has been growing in recent years. This paper proposes modeling SCD data with…

  16. A new explained-variance based genetic risk score for predictive modeling of disease risk.

    PubMed

    Che, Ronglin; Motsinger-Reif, Alison A

    2012-09-25

    The goal of association mapping is to identify genetic variants that predict disease, and as the field of human genetics matures, the number of successful association studies is increasing. Many such studies have shown that for many diseases, risk is explained by a reasonably large number of variants that each explains a very small amount of disease risk. This is prompting the use of genetic risk scores in building predictive models, where information across several variants is combined for predictive modeling. In the current study, we compare the performance of four previously proposed genetic risk score methods and present a new method for constructing genetic risk score that incorporates explained variance information. The methods compared include: a simple count Genetic Risk Score, an odds ratio weighted Genetic Risk Score, a direct logistic regression Genetic Risk Score, a polygenic Genetic Risk Score, and the new explained variance weighted Genetic Risk Score. We compare the methods using a wide range of simulations in two steps, with a range of the number of deleterious single nucleotide polymorphisms (SNPs) explaining disease risk, genetic modes, baseline penetrances, sample sizes, relative risks (RR) and minor allele frequencies (MAF). Several measures of model performance were compared including overall power, C-statistic and Akaike's Information Criterion. Our results show the relative performance of methods differs significantly, with the new explained variance weighted GRS (EV-GRS) generally performing favorably to the other methods.

  17. Formation and reduction of carcinogenic furan in various model systems containing food additives.

    PubMed

    Kim, Jin-Sil; Her, Jae-Young; Lee, Kwang-Geun

    2015-12-15

    The aim of this study was to analyse and reduce furan in various model systems. Furan model systems consisting of monosaccharides (0.5M glucose and ribose), amino acids (0.5M alanine and serine) and/or 1.0M ascorbic acid were heated at 121°C for 25 min. The effects of food additives (each 0.1M) such as metal ions (iron sulphate, magnesium sulphate, zinc sulphate and calcium sulphate), antioxidants (BHT and BHA), and sodium sulphite on the formation of furan were measured. The level of furan formed in the model systems was 6.8-527.3 ng/ml. The level of furan in the model systems of glucose/serine and glucose/alanine increased 7-674% when food additives were added. In contrast, the level of furan decreased by 18-51% in the Maillard reaction model systems that included ribose and alanine/serine with food additives except zinc sulphate.

  18. NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid

    NASA Astrophysics Data System (ADS)

    Thomas, Togis; Gupta, K. K.

    2016-03-01

    Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.

  19. Achieving World-Class Schools: Mastering School Improvement Using a Genetic Model.

    ERIC Educational Resources Information Center

    Kimmelman, Paul L.; Kroeze, David J.

    In providing its program for education reform, this book uses, as an analogy, the genetic model taken from the Human Genome project. In the first part, "Theoretical Underpinnings," the book explains why a genetic model can be used to improve school systems; describes the critical components of a world-class school system; and details the genetic…

  20. Genetic Model Fitting in IQ, Assortative Mating & Components of IQ Variance.

    ERIC Educational Resources Information Center

    Capron, Christiane; Vetta, Adrian R.; Vetta, Atam

    1998-01-01

    The biometrical school of scientists who fit models to IQ data traces their intellectual ancestry to R. Fisher (1918), but their genetic models have no predictive value. Fisher himself was critical of the concept of heritability, because assortative mating, such as for IQ, introduces complexities into the study of a genetic trait. (SLD)

  1. Detecting epistatic genetic variance with a clonally replicated design: models for lowvs high-order nonallelic interaction.

    PubMed

    Wu, R L

    1996-07-01

    A quantitative genetic model, that uses known family structure with clonal replicates to separate genetic variance into its additive, dominance and epistatic components, is available in the current literature. Making use of offspring testing, this model is based on the theory that components of variance from the linear model of an experimental design may be expressed in terms of expected covariances among relatives. However, if interactions between a pair of quantitative trait loci (QTLs) explain a large proportion of the total epistasis, it will seriously overestimate the additive and dominance variances but underestimate the epistatic variance. In the present paper, a new model is developed to manipulate this problem by combining parental and offspring material into the same test. Under the condition described above, the new model can provide an accurate estimate for additive x additive variances. Also, its accuracy in estimating dominance and total epistatic variances is much greater than the accuracy of the previous model. However, if there is obvious evidence showing the major contribution of high-order interactions, especially among ≥ 4QTLs, to the total epistasis, the previous model is more appropriate to partition the genetic variance for a quantitative trait. The re-analysis of an example from a factorial mating design in poplar shows large differences in estimating variance components between the new and previous models when two different assumptions (lowvs high-order epistatic interactions) are used. The new model will be an alternative to estimating the mode of quantitative inheritance for species, especially for longlived, predominantly outcrossing forest trees, that can be clonally replicated.

  2. Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

    PubMed

    Hong, X; Harris, C J

    2000-01-01

    This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

  3. Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.

    PubMed

    He, Liang; Sillanpää, Mikko J; Silventoinen, Karri; Kaprio, Jaakko; Pitkäniemi, Janne

    2016-04-01

    Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene-environment (G×E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametricG×Einteraction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more

  4. Genetic analysis of calving traits by the multi-trait individual animal model.

    PubMed

    Weller, J I; Ezra, E

    2016-01-01

    Five alternative models were applied for analysis of dystocia and stillbirth in first and second parities. Models 1 and 2 were included only to estimate the parameters required for model 4, and models 3 and 5 are included only as comparisons to the model 4 estimates. Variance components were estimated by multi-trait REML, including cows with valid calving records for both parities. For the effects of sire of calf on first and second parities, variance components were estimated including only calvings with the same sire of calf for both parities. All heritabilities for the cow effect were quite low, but higher for dystocia than for stillbirth and higher in first parity. The sire-of-calf heritabilities were higher than the cow effect heritabilities, except for stillbirth in parity 2. Unlike the effect of cow correlations, all sire of calf correlations were >0.6, and the correlations for the same trait in parities 1 and 2 were >0.9. Thus, a multi-trait analysis should yield a significant gain in accuracy with respect to the sire of calf effects for bulls not mated to virgin heifers. A multi-trait individual animal model algorithm was developed for joint analysis of dystocia and stillbirth in first and second parities. Relationships matrices were included both for the effects of cow and sire of calf. In addition, random herd-year-season and fixed sex of calf effects were included in the model. Records were preadjusted for calving month and age. A total of 899,223 Israeli Holstein cows with first calvings since 1985 were included in the complete analysis. Approximate reliabilities were computed for both sire of cow and sire of calf effects. Correlations between these reliabilities and reliabilities obtained by direct inversion of the coefficient matrix for a sire of cow-sire of calf model were all close to 0.99. Phenotypic trends for cows born from 1983 through 2007 were economically unfavorable for dystocia and favorable for stillbirth in both parities. Genetic trends

  5. Genetically engineered mice with an additional class of cone photoreceptors: implications for the evolution of color vision.

    PubMed

    Smallwood, Philip M; Olveczky, Bence P; Williams, Gary L; Jacobs, Gerald H; Reese, Benjamin E; Meister, Markus; Nathans, Jeremy

    2003-09-30

    Among eutherian mammals, only primates possess trichromatic color vision. In Old World primates, trichromacy was made possible by a visual pigment gene duplication. In most New World primates, trichromacy is based on polymorphic variation in a single X-linked gene that produces, by random X inactivation, a patchy mosaic of spectrally distinct cone photoreceptors in heterozygous females. In the present work, we have modeled the latter strategy in a nonprimate by replacing the X-linked mouse green pigment gene with one encoding the human red pigment. In the mouse retina, the human red pigment seems to function normally, and heterozygous female mice express the human red and mouse green pigments at levels that vary between animals. Multielectrode array recordings from heterozygous female retinas reveal significant variation in the chromatic sensitivities of retinal ganglion cells. The data are consistent with a model in which these retinal ganglion cells draw their inputs indiscriminately from a coarse-grained mosaic of red and green cones. These observations support the ideas that (i) chromatic signals could arise from stochastic variation in inputs drawn nonselectively from red and green cones and (ii) tissue mosaicism due to X chromosome inactivation could be one mechanism for driving the evolution of CNS diversity. PMID:14500905

  6. Genetically engineered mice with an additional class of cone photoreceptors: implications for the evolution of color vision.

    PubMed

    Smallwood, Philip M; Olveczky, Bence P; Williams, Gary L; Jacobs, Gerald H; Reese, Benjamin E; Meister, Markus; Nathans, Jeremy

    2003-09-30

    Among eutherian mammals, only primates possess trichromatic color vision. In Old World primates, trichromacy was made possible by a visual pigment gene duplication. In most New World primates, trichromacy is based on polymorphic variation in a single X-linked gene that produces, by random X inactivation, a patchy mosaic of spectrally distinct cone photoreceptors in heterozygous females. In the present work, we have modeled the latter strategy in a nonprimate by replacing the X-linked mouse green pigment gene with one encoding the human red pigment. In the mouse retina, the human red pigment seems to function normally, and heterozygous female mice express the human red and mouse green pigments at levels that vary between animals. Multielectrode array recordings from heterozygous female retinas reveal significant variation in the chromatic sensitivities of retinal ganglion cells. The data are consistent with a model in which these retinal ganglion cells draw their inputs indiscriminately from a coarse-grained mosaic of red and green cones. These observations support the ideas that (i) chromatic signals could arise from stochastic variation in inputs drawn nonselectively from red and green cones and (ii) tissue mosaicism due to X chromosome inactivation could be one mechanism for driving the evolution of CNS diversity.

  7. Rodent models of genetic contributions to motivation to abuse alcohol.

    PubMed

    Crabbe, John C

    2014-01-01

    In summary, there are remarkably few studies focused on the genetic contributions to alcohol's reinforcing values. Almost all such studies examine the two-bottle preference test. Despite the deficiencies I have raised in its interpretation, a rodent genotype's willingness to drink ethanol when water is freely available offers a reasonable aggregate estimate of alcohol's reinforcing value relative to other genotypes (Green and Grahame 2008). As indicated above, however, preference drinking studies will likely never avoid the confounding role of taste preferences and most often yield intake levels not sufficient to yield a pharmacologically significant BAL. Thus, the quest for improved measures of reinforcing value continues. Of the potential motivational factors considered by McClearn in his seminal review in this series, we can safely conclude that rodent alcohol drinking is not primarily directed at obtaining calories. The role of taste (and odor) remains a challenge. McClearn appears to have been correct that especially those genotypes that avoid alcohol are probably doing so based on preingestive sensory cues; however, postingestive consequences are also important. Cunningham's intragastric model shows the role of both preingestional and postingestional modulating factors for the best known examples, the usually nearly absolutely alcohol-avoiding DBA/2J and HAP-2 mice. Much subsequent data reinforce McClearn's earlier conclusion that C57BL/6J mice, at least, do not regulate their intake around a given self-administered dose of alcohol by adjusting their intake. This leaves us with the puzzle of why nearly all genotypes, even those directionally selectively bred for high voluntary intake for many generations, fail to self-administer intoxicating amounts of alcohol. Since McClearn's review, many ingenious assays to index alcohol's motivational effects have been used extensively, and new methods for inducing dependence have supplanted the older ones prevalent in

  8. Genetic variation, climate models and the ecological genetics of Larix occidentalis

    SciTech Connect

    Rehfeldt, G.E.

    1995-12-31

    Provenance tests of 138 populations of Larix occidentalis revealed genetic differentiation for eight variables describing growth, phenology, tolerance to spring frosts, effects of Meria laricis needle cast, and survival. Geographic variables accounted for as much as 34% of the variance among Rocky Mountain populations. Patterns of genetic variation were dominated by the effects of latitude and elevation, with populations from the north and from high elevations having the lowest growth potential, the least tolerance to the needle cast, and the lowest survival. However, the slope of the geographic clines was relatively flat. Populations in the same geographic area, for instance, need to be separated by about 500 m in elevation before genetic differentiation can be expected.

  9. Physiological basis of tolerance to complete submergence in rice involves genetic factors in addition to the SUB1 gene.

    PubMed

    Singh, Sudhanshu; Mackill, David J; Ismail, Abdelbagi M

    2014-01-01

    1 lines. This suggests the possibility of further improvements in submergence tolerance by incorporating additional traits present in FR13A or other similar landraces. PMID:25281725

  10. Use of additive technologies for practical working with complex models for foundry technologies

    NASA Astrophysics Data System (ADS)

    Olkhovik, E.; Butsanets, A. A.; Ageeva, A. A.

    2016-07-01

    The article presents the results of research of additive technology (3D printing) application for developing a geometrically complex model of castings parts. Investment casting is well known and widely used technology for the production of complex parts. The work proposes the use of a 3D printing technology for manufacturing models parts, which are removed by thermal destruction. Traditional methods of equipment production for investment casting involve the use of manual labor which has problems with dimensional accuracy, and CNC technology which is less used. Such scheme is low productive and demands considerable time. We have offered an alternative method which consists in printing the main knots using a 3D printer (PLA and ABS) with a subsequent production of castings models from them. In this article, the main technological methods are considered and their problems are discussed. The dimensional accuracy of models in comparison with investment casting technology is considered as the main aspect.

  11. Generalized Additive Mixed-Models for Pharmacology Using Integrated Discrete Multiple Organ Co-Culture

    PubMed Central

    Ingersoll, Thomas; Cole, Stephanie; Madren-Whalley, Janna; Booker, Lamont; Dorsey, Russell; Li, Albert; Salem, Harry

    2016-01-01

    Integrated Discrete Multiple Organ Co-culture (IDMOC) is emerging as an in-vitro alternative to in-vivo animal models for pharmacology studies. IDMOC allows dose-response relationships to be investigated at the tissue and organoid levels, yet, these relationships often exhibit responses that are far more complex than the binary responses often measured in whole animals. To accommodate departure from binary endpoints, IDMOC requires an expansion of analytic techniques beyond simple linear probit and logistic models familiar in toxicology. IDMOC dose-responses may be measured at continuous scales, exhibit significant non-linearity such as local maxima or minima, and may include non-independent measures. Generalized additive mixed-modeling (GAMM) provides an alternative description of dose-response that relaxes assumptions of independence and linearity. We compared GAMMs to traditional linear models for describing dose-response in IDMOC pharmacology studies. PMID:27110941

  12. Evidence of thermal additivity during short laser pulses in an in vitro retinal model

    NASA Astrophysics Data System (ADS)

    Denton, Michael L.; Tijerina, Amanda J.; Dyer, Phillip N.; Oian, Chad A.; Noojin, Gary D.; Rickman, John M.; Shingledecker, Aurora D.; Clark, Clifton D.; Castellanos, Cherry C.; Thomas, Robert J.; Rockwell, Benjamin A.

    2015-03-01

    Laser damage thresholds were determined for exposure to 2.5-ms 532-nm pulses in an established in vitro retinal model. Single and multiple pulses (10, 100, 1000) were delivered to the cultured cells at three different pulse repetition frequency (PRF) values, and overt damage (membrane breach) was scored 1 hr post laser exposure. Trends in the damage data within and across the PRF range identified significant thermal additivity as PRF was increased, as evidenced by drastically reduced threshold values (< 40% of single-pulse value). Microthermography data that were collected in real time during each exposure also provided evidence of thermal additivity between successive laser pulses. Using thermal profiles simulated at high temporal resolution, damage threshold values were predicted by an in-house computational model. Our simulated ED50 value for a single 2.5-ms pulse was in very good agreement with experimental results, but ED50 predictions for multiple-pulse trains will require more refinement.

  13. Additive influence of genetic predisposition and conventional risk factors in the incidence of coronary heart disease: a population-based study in Greece

    PubMed Central

    Yiannakouris, Nikos; Katsoulis, Michail; Trichopoulou, Antonia; Ordovas, Jose M; Trichopoulos, Dimitrios

    2014-01-01

    Objectives An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-‘environment’ joint actions on CHD for several conventional cardiovascular risk factors (ConvRFs), including smoking, hypertension, type-2 diabetes mellitus (T2DM), body mass index (BMI), physical activity and adherence to the Mediterranean diet. Design A case–control study. Setting The general Greek population of the EPIC study. Participants and outcome measures 477 patients with medically confirmed incident CHD and 1271 controls participated in this study. We estimated the ORs for CHD by dividing participants at higher or lower GRS and, alternatively, at higher or lower ConvRF, and calculated the relative excess risk due to interaction (RERI) as a measure of deviation from additivity. Results The joint presence of higher GRS and higher risk ConvRF was in all instances associated with an increased risk of CHD, compared with the joint presence of lower GRS and lower risk ConvRF. The OR (95% CI) was 1.7 (1.2 to 2.4) for smoking, 2.7 (1.9 to 3.8) for hypertension, 4.1 (2.8 to 6.1) for T2DM, 1.9 (1.4 to 2.5) for lower physical activity, 2.0 (1.3 to 3.2) for high BMI and 1.5 (1.1 to 2.1) for poor adherence to the Mediterranean diet. In all instances, RERI values were fairly small and not statistically significant, suggesting that the GRS and the ConvRFs do not have effects beyond additivity. Conclusions Genetic predisposition to CHD, operationalised through a multilocus GRS, and ConvRFs have essentially additive effects on CHD risk. PMID:24500614

  14. Mouse models as a tool to unravel the genetic basis for human otitis media

    PubMed Central

    Zheng, Qing Yin; Hardisty-Hughes, Rachel; Brown, Steve D.M.

    2010-01-01

    The pathogenesis of otitis media (OM) is multifactorial and includes infection, anatomical factors, immunologic status, genetic predisposition, and environmental factors. OM remains the most common cause of hearing impairment in childhood. Genetic predisposition is increasingly recognized as an important factor. The completion of the mouse genome sequence has offered a powerful basket of tools for investigating gene function and can expect to generate a rich resource of mouse mutants for the elucidation of genetic factors underlying OM. We review the literature and discuss recent progresses in developing mouse models and using mouse models to uncover the genetic basis for human OM. PMID:16917982

  15. Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

    NASA Astrophysics Data System (ADS)

    Samadhi, TMAA; Sumihartati, Atin

    2016-02-01

    The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

  16. A DNA-hairpin model for repeat-addition processivity in telomere synthesis.

    PubMed

    Yang, Wei; Lee, Young-Sam

    2015-11-01

    We propose a DNA-hairpin model for the processivity of telomeric-repeat addition. Concomitantly with template-RNA translocation after each repeat synthesis, the complementary DNA repeat, for example, AGGGTT, loops out in a noncanonical base-paired hairpin, thus freeing the RNA template for the next round of repeat synthesis. The DNA hairpin is temporarily stabilized by telomerase and the incoming dGTP but becomes realigned for processive telomere synthesis.

  17. [The discussion of the infiltrative model of mathematical knowledge to genetics teaching].

    PubMed

    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.

  18. Broad bandwidth or high fidelity? Evidence from the structure of genetic and environmental effects on the facets of the five factor model.

    PubMed

    Briley, Daniel A; Tucker-Drob, Elliot M

    2012-09-01

    The Five Factor Model 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. For three of the Big Five domains, 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. 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.

  19. Rain water transport and storage in a model sandy soil with hydrogel particle additives.

    PubMed

    Wei, Y; Durian, D J

    2014-10-01

    We study rain water infiltration and drainage in a dry model sandy soil with superabsorbent hydrogel particle additives by measuring the mass of retained water for non-ponding rainfall using a self-built 3D laboratory set-up. In the pure model sandy soil, the retained water curve measurements indicate that instead of a stable horizontal wetting front that grows downward uniformly, a narrow fingered flow forms under the top layer of water-saturated soil. This rain water channelization phenomenon not only further reduces the available rain water in the plant root zone, but also affects the efficiency of soil additives, such as superabsorbent hydrogel particles. Our studies show that the shape of the retained water curve for a soil packing with hydrogel particle additives strongly depends on the location and the concentration of the hydrogel particles in the model sandy soil. By carefully choosing the particle size and distribution methods, we may use the swollen hydrogel particles to modify the soil pore structure, to clog or extend the water channels in sandy soils, or to build water reservoirs in the plant root zone.

  20. DNA looping increases the range of bistability in a stochastic model of the lac genetic switch.

    PubMed

    Earnest, Tyler M; Roberts, Elijah; Assaf, Michael; Dahmen, Karin; Luthey-Schulten, Zaida

    2013-04-01

    Conditions and parameters affecting the range of bistability of the lac genetic switch in Escherichia coli are examined for a model which includes DNA looping interactions with the lac repressor and a lactose analogue. This stochastic gene-mRNA-protein model of the lac switch describes DNA looping using a third transcriptional state. We exploit the fast bursting dynamics of mRNA by combining a novel geometric burst extension with the finite state projection method. This limits the number of protein/mRNA states, allowing for an accelerated search of the model's parameter space. We evaluate how the addition of the third state changes the bistability properties of the model and find a critical region of parameter space where the phenotypic switching occurs in a range seen in single molecule fluorescence studies. Stochastic simulations show induction in the looping model is preceded by a rare complete dissociation of the loop followed by an immediate burst of mRNA rather than a slower build up of mRNA as in the two-state model. The overall effect of the looped state is to allow for faster switching times while at the same time further differentiating the uninduced and induced phenotypes. Furthermore, the kinetic parameters are consistent with free energies derived from thermodynamic studies suggesting that this minimal model of DNA looping could have a broader range of application. PMID:23406725

  1. DNA looping increases the range of bistability in a stochastic model of the lac genetic switch

    NASA Astrophysics Data System (ADS)

    Earnest, Tyler M.; Roberts, Elijah; Assaf, Michael; Dahmen, Karin; Luthey-Schulten, Zaida

    2013-04-01

    Conditions and parameters affecting the range of bistability of the lac genetic switch in Escherichia coli are examined for a model which includes DNA looping interactions with the lac repressor and a lactose analogue. This stochastic gene-mRNA-protein model of the lac switch describes DNA looping using a third transcriptional state. We exploit the fast bursting dynamics of mRNA by combining a novel geometric burst extension with the finite state projection method. This limits the number of protein/mRNA states, allowing for an accelerated search of the model's parameter space. We evaluate how the addition of the third state changes the bistability properties of the model and find a critical region of parameter space where the phenotypic switching occurs in a range seen in single molecule fluorescence studies. Stochastic simulations show induction in the looping model is preceded by a rare complete dissociation of the loop followed by an immediate burst of mRNA rather than a slower build up of mRNA as in the two-state model. The overall effect of the looped state is to allow for faster switching times while at the same time further differentiating the uninduced and induced phenotypes. Furthermore, the kinetic parameters are consistent with free energies derived from thermodynamic studies suggesting that this minimal model of DNA looping could have a broader range of application.

  2. Nephron Deficiency and Predisposition to Renal Injury in a Novel One-Kidney Genetic Model.

    PubMed

    Wang, Xuexiang; Johnson, Ashley C; Williams, Jan M; White, Tiffani; Chade, Alejandro R; Zhang, Jie; Liu, Ruisheng; Roman, Richard J; Lee, Jonathan W; Kyle, Patrick B; Solberg-Woods, Leah; Garrett, Michael R

    2015-07-01

    Some studies have reported up to 40% of patients born with a single kidney develop hypertension, proteinuria, and in some cases renal failure. The increased susceptibility to renal injury may be due, in part, to reduced nephron numbers. Notably, children who undergo nephrectomy or adults who serve as kidney donors exhibit little difference in renal function compared with persons who have two kidneys. However, the difference in risk between being born with a single kidney versus being born with two kidneys and then undergoing nephrectomy are unclear. Animal models used previously to investigate this question are not ideal because they require invasive methods to model congenital solitary kidney. In this study, we describe a new genetic animal model, the heterogeneous stock-derived model of unilateral renal agenesis (HSRA) rat, which demonstrates 50%-75% spontaneous incidence of a single kidney. The HSRA model is characterized by reduced nephron number (more than would be expected by loss of one kidney), early kidney/glomerular hypertrophy, and progressive renal injury, which culminates in reduced renal function. Long-term studies of temporal relationships among BP, renal hemodynamics, and renal function demonstrate that spontaneous single-kidney HSRA rats are more likely than uninephrectomized normal littermates to exhibit renal impairment because of the combination of reduced nephron numbers and prolonged exposure to renal compensatory mechanisms (i.e., hyperfiltration). Future studies with this novel animal model may provide additional insight into the genetic contributions to kidney development and agenesis and the factors influencing susceptibility to renal injury in individuals with congenital solitary kidney.

  3. Nephron Deficiency and Predisposition to Renal Injury in a Novel One-Kidney Genetic Model

    PubMed Central

    Wang, Xuexiang; Johnson, Ashley C.; Williams, Jan M.; White, Tiffani; Chade, Alejandro R.; Zhang, Jie; Liu, Ruisheng; Roman, Richard J.; Lee, Jonathan W.; Kyle, Patrick B.; Solberg-Woods, Leah

    2015-01-01

    Some studies have reported up to 40% of patients born with a single kidney develop hypertension, proteinuria, and in some cases renal failure. The increased susceptibility to renal injury may be due, in part, to reduced nephron numbers. Notably, children who undergo nephrectomy or adults who serve as kidney donors exhibit little difference in renal function compared with persons who have two kidneys. However, the difference in risk between being born with a single kidney versus being born with two kidneys and then undergoing nephrectomy are unclear. Animal models used previously to investigate this question are not ideal because they require invasive methods to model congenital solitary kidney. In this study, we describe a new genetic animal model, the heterogeneous stock-derived model of unilateral renal agenesis (HSRA) rat, which demonstrates 50%–75% spontaneous incidence of a single kidney. The HSRA model is characterized by reduced nephron number (more than would be expected by loss of one kidney), early kidney/glomerular hypertrophy, and progressive renal injury, which culminates in reduced renal function. Long-term studies of temporal relationships among BP, renal hemodynamics, and renal function demonstrate that spontaneous single-kidney HSRA rats are more likely than uninephrectomized normal littermates to exhibit renal impairment because of the combination of reduced nephron numbers and prolonged exposure to renal compensatory mechanisms (i.e., hyperfiltration). Future studies with this novel animal model may provide additional insight into the genetic contributions to kidney development and agenesis and the factors influencing susceptibility to renal injury in individuals with congenital solitary kidney. PMID:25349207

  4. Generalized linear and generalized additive models in studies of species distributions: Setting the scene

    USGS Publications Warehouse

    Guisan, A.; Edwards, T.C.; Hastie, T.

    2002-01-01

    An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001. We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling. ?? 2002 Elsevier Science B.V. All rights reserved.

  5. Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

    PubMed Central

    2012-01-01

    Background The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle. Methods Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models. Results and discussion On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence. Conclusions For the evaluation of

  6. Testing the genetic predictions of a biogeographical model in a dominant endemic Eastern Pacific coral (Porites panamensis) using a genetic seascape approach.

    PubMed

    Saavedra-Sotelo, Nancy C; Calderon-Aguilera, Luis E; Reyes-Bonilla, Héctor; Paz-García, David A; López-Pérez, Ramón A; Cupul-Magaña, Amilcar; Cruz-Barraza, José A; Rocha-Olivares, Axayácatl

    2013-10-01

    The coral fauna of the Eastern Tropical Pacific (ETP) is depauperate and peripheral; hence, it has drawn attention to the factors allowing its survival. Here, we use a genetic seascape approach and ecological niche modeling to unravel the environmental factors correlating with the genetic variation of Porites panamensis, a hermatypic coral endemic to the ETP. Specifically, we test if levels of diversity and connectivity are higher among abundant than among depauperate populations, as expected by a geographically relaxed version of the Abundant Center Hypothesis (rel-ACH). Unlike the original ACH, referring to a geographical center of distribution of maximal abundance, the rel-ACH refers only to a center of maximum abundance, irrespective of its geographic position. The patterns of relative abundance of P. panamensis in the Mexican Pacific revealed that northern populations from Baja California represent its center of abundance; and southern depauperate populations along the continental margin are peripheral relative to it. Genetic patterns of diversity and structure of nuclear DNA sequences (ribosomal DNA and a single copy open reading frame) and five alloenzymatic loci partially agreed with rel-ACH predictions. We found higher diversity levels in peninsular populations and significant differentiation between peninsular and continental colonies. In addition, continental populations showed higher levels of differentiation and lower connectivity than peninsular populations in the absence of isolation by distance in each region. Some discrepancies with model expectations may relate to the influence of significant habitat discontinuities in the face of limited dispersal potential. Environmental data analyses and niche modeling allowed us to identify temperature, water clarity, and substrate availability as the main factors correlating with patterns of abundance, genetic diversity, and structure, which may hold the key to the survival of P. panamensis in the face of

  7. Testing the genetic predictions of a biogeographical model in a dominant endemic Eastern Pacific coral (Porites panamensis) using a genetic seascape approach.

    PubMed

    Saavedra-Sotelo, Nancy C; Calderon-Aguilera, Luis E; Reyes-Bonilla, Héctor; Paz-García, David A; López-Pérez, Ramón A; Cupul-Magaña, Amilcar; Cruz-Barraza, José A; Rocha-Olivares, Axayácatl

    2013-10-01

    The coral fauna of the Eastern Tropical Pacific (ETP) is depauperate and peripheral; hence, it has drawn attention to the factors allowing its survival. Here, we use a genetic seascape approach and ecological niche modeling to unravel the environmental factors correlating with the genetic variation of Porites panamensis, a hermatypic coral endemic to the ETP. Specifically, we test if levels of diversity and connectivity are higher among abundant than among depauperate populations, as expected by a geographically relaxed version of the Abundant Center Hypothesis (rel-ACH). Unlike the original ACH, referring to a geographical center of distribution of maximal abundance, the rel-ACH refers only to a center of maximum abundance, irrespective of its geographic position. The patterns of relative abundance of P. panamensis in the Mexican Pacific revealed that northern populations from Baja California represent its center of abundance; and southern depauperate populations along the continental margin are peripheral relative to it. Genetic patterns of diversity and structure of nuclear DNA sequences (ribosomal DNA and a single copy open reading frame) and five alloenzymatic loci partially agreed with rel-ACH predictions. We found higher diversity levels in peninsular populations and significant differentiation between peninsular and continental colonies. In addition, continental populations showed higher levels of differentiation and lower connectivity than peninsular populations in the absence of isolation by distance in each region. Some discrepancies with model expectations may relate to the influence of significant habitat discontinuities in the face of limited dispersal potential. Environmental data analyses and niche modeling allowed us to identify temperature, water clarity, and substrate availability as the main factors correlating with patterns of abundance, genetic diversity, and structure, which may hold the key to the survival of P. panamensis in the face of

  8. Testing the genetic predictions of a biogeographical model in a dominant endemic Eastern Pacific coral (Porites panamensis) using a genetic seascape approach

    PubMed Central

    Saavedra-Sotelo, Nancy C; Calderon-Aguilera, Luis E; Reyes-Bonilla, Héctor; Paz-García, David A; López-Pérez, Ramón A; Cupul-Magaña, Amilcar; Cruz-Barraza, José A; Rocha-Olivares, Axayácatl

    2013-01-01

    The coral fauna of the Eastern Tropical Pacific (ETP) is depauperate and peripheral; hence, it has drawn attention to the factors allowing its survival. Here, we use a genetic seascape approach and ecological niche modeling to unravel the environmental factors correlating with the genetic variation of Porites panamensis, a hermatypic coral endemic to the ETP. Specifically, we test if levels of diversity and connectivity are higher among abundant than among depauperate populations, as expected by a geographically relaxed version of the Abundant Center Hypothesis (rel-ACH). Unlike the original ACH, referring to a geographical center of distribution of maximal abundance, the rel-ACH refers only to a center of maximum abundance, irrespective of its geographic position. The patterns of relative abundance of P. panamensis in the Mexican Pacific revealed that northern populations from Baja California represent its center of abundance; and southern depauperate populations along the continental margin are peripheral relative to it. Genetic patterns of diversity and structure of nuclear DNA sequences (ribosomal DNA and a single copy open reading frame) and five alloenzymatic loci partially agreed with rel-ACH predictions. We found higher diversity levels in peninsular populations and significant differentiation between peninsular and continental colonies. In addition, continental populations showed higher levels of differentiation and lower connectivity than peninsular populations in the absence of isolation by distance in each region. Some discrepancies with model expectations may relate to the influence of significant habitat discontinuities in the face of limited dispersal potential. Environmental data analyses and niche modeling allowed us to identify temperature, water clarity, and substrate availability as the main factors correlating with patterns of abundance, genetic diversity, and structure, which may hold the key to the survival of P. panamensis in the face of

  9. A new genetic fuzzy system approach for parameter estimation of ARIMA model

    NASA Astrophysics Data System (ADS)

    Hassan, Saima; Jaafar, Jafreezal; Belhaouari, Brahim S.; Khosravi, Abbas

    2012-09-01

    The Autoregressive Integrated moving Average model is the most powerful and practical time series model for forecasting. Parameter estimation is the most crucial part in ARIMA modeling. Inaccurate and wrong estimated parameters lead to bias and unacceptable forecasting results. Parameter optimization can be adopted in order to increase the demand forecasting accuracy. A paradigm of the fuzzy system and a genetic algorithm is proposed in this paper as a parameter estimation approach for ARIMA. The new approach will optimize the parameters by tuning the fuzzy membership functions with a genetic algorithm. The proposed Hybrid model of ARIMA and the genetic fuzzy system will yield acceptable forecasting results.

  10. Plasmodium falciparum genetic crosses in a humanized mouse model

    PubMed Central

    Vaughan, Ashley M.; Pinapati, Richard S.; Cheeseman, Ian H.; Camargo, Nelly; Fishbaugher, Matthew; Checkley, Lisa A.; Nair, Shalini; Hutyra, Carolyn A.; Nosten, François H.; Anderson, Timothy J. C.; Ferdig, Michael T.; Kappe, Stefan H. I.

    2015-01-01

    Genetic crosses of phenotypically distinct strains of the human malaria parasite Plasmodium falciparum are a powerful tool for identifying genes controlling drug resistance and other key phenotypes. Previous studies relied on the isolation of recombinant parasites from splenectomized chimpanzees, a research avenue that is no longer available. Here, we demonstrate that human-liver chimeric mice support recovery of recombinant progeny for the identification of genetic determinants of parasite traits and adaptations. PMID:26030447

  11. Resources allocation in healthcare for cancer: a case study using generalised additive mixed models.

    PubMed

    Musio, Monica; Sauleau, Erik A; Augustin, Nicole H

    2012-11-01

    Our aim is to develop a method for helping resources re-allocation in healthcare linked to cancer, in order to replan the allocation of providers. Ageing of the population has a considerable impact on the use of health resources because aged people require more specialised medical care due notably to cancer. We propose a method useful to monitor changes of cancer incidence in space and time taking into account two age categories, according to healthcar general organisation. We use generalised additive mixed models with a Poisson response, according to the methodology presented in Wood, Generalised additive models: an introduction with R. Chapman and Hall/CRC, 2006. Besides one-dimensional smooth functions accounting for non-linear effects of covariates, the space-time interaction can be modelled using scale invariant smoothers. Incidence data collected by a general cancer registry between 1992 and 2007 in a specific area of France is studied. Our best model exhibits a strong increase of the incidence of cancer along time and an obvious spatial pattern for people more than 70 years with a higher incidence in the central band of the region. This is a strong argument for re-allocating resources for old people cancer care in this sub-region. PMID:23242683

  12. Resources allocation in healthcare for cancer: a case study using generalised additive mixed models.

    PubMed

    Musio, Monica; Sauleau, Erik A; Augustin, Nicole H

    2012-11-01

    Our aim is to develop a method for helping resources re-allocation in healthcare linked to cancer, in order to replan the allocation of providers. Ageing of the population has a considerable impact on the use of health resources because aged people require more specialised medical care due notably to cancer. We propose a method useful to monitor changes of cancer incidence in space and time taking into account two age categories, according to healthcar general organisation. We use generalised additive mixed models with a Poisson response, according to the methodology presented in Wood, Generalised additive models: an introduction with R. Chapman and Hall/CRC, 2006. Besides one-dimensional smooth functions accounting for non-linear effects of covariates, the space-time interaction can be modelled using scale invariant smoothers. Incidence data collected by a general cancer registry between 1992 and 2007 in a specific area of France is studied. Our best model exhibits a strong increase of the incidence of cancer along time and an obvious spatial pattern for people more than 70 years with a higher incidence in the central band of the region. This is a strong argument for re-allocating resources for old people cancer care in this sub-region.

  13. Identification of Treatment Targets in a Genetic Mouse Model of Voluntary Methamphetamine Drinking.

    PubMed

    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. PMID:27055611

  14. Genetic basis of hindlimb loss in a naturally occurring vertebrate model

    PubMed Central

    Don, Emily K.; de Jong-Curtain, Tanya A.; Doggett, Karen; Hall, Thomas E.; Heng, Benjamin; Badrock, Andrew P.; Winnick, Claire; Nicholson, Garth A.; Guillemin, Gilles J.; Currie, Peter D.; Hesselson, Daniel; Heath, Joan K.; Cole, Nicholas J.

    2016-01-01

    ABSTRACT Here we genetically characterise pelvic finless, a naturally occurring model of hindlimb loss in zebrafish that lacks pelvic fin structures, which are homologous to tetrapod hindlimbs, but displays no other abnormalities. Using a hybrid positional cloning and next generation sequencing approach, we identified mutations in the nuclear localisation signal (NLS) of T-box transcription factor 4 (Tbx4) that impair nuclear localisation of the protein, resulting in altered gene expression patterns during pelvic fin development and the failure of pelvic fin development. Using a TALEN-induced tbx4 knockout allele we confirm that mutations within the Tbx4 NLS (A78V; G79A) are sufficient to disrupt pelvic fin development. By combining histological, genetic, and cellular approaches we show that the hindlimb initiation gene tbx4 has an evolutionarily conserved, essential role in pelvic fin development. In addition, our novel viable model of hindlimb deficiency is likely to facilitate the elucidation of the detailed molecular mechanisms through which Tbx4 functions during pelvic fin and hindlimb development. PMID:26892237

  15. Dominant, non-MHC genetic control of food allergy in an adjuvant-free mouse model.

    PubMed

    Parvataneni, S; Birmingham, N P; Gonipeta, B; Gangur, V

    2009-10-01

    Food allergy is a potentially fatal immune-mediated disorder with incompletely understood mechanisms. We studied the genetic control of food allergy using major histocompatibility complex-identical mice (H2(s)) and an adjuvant-free method of sensitization. Whereas, transdermal exposure to hazelnut - a model allergenic food, elicited robust IgG1 response in both strains, an IgE response was evident only in A.SW mice. Following oral challenge, only A.SW but not SJL mice exhibited signs of systemic anaphylaxis and hypothermia. In addition, (A.SW x SJL) F1 hybrids exhibited IgE responsiveness, systemic anaphylaxis and hypothermia similar to A.SW, indicating dominant inheritance of these traits. Furthermore, whereas A.SW and F1 mice but not SJL elicited robust interleukin (IL)-4 response, all three strains elicited IL-5 and IL-13 responses by spleen cells. These data demonstrate for the first time, dominant non-MHC genetic control of food allergy and a critical role of IL-4 but not IL-5 or IL-13 in this model. PMID:19624800

  16. Identification of Genetic Loci Involved in Diabetes using a Rat Model of Depression

    PubMed Central

    Woods, Leah C Solberg; Ahmadiyeh, Nasim; Baum, Amber; Shimomura, Kazuhiro; Li, Qian; Steiner, Donald F; Turek, Fred W; Takahashi, Joseph S; Churchill, Gary A; Redei, Eva E

    2009-01-01

    While diabetic patients often present with comorbid depression, the underlying mechanisms linking diabetes and depression are unknown. The Wistar Kyoto (WKY) rat is a well-known animal model of depression and stress hyper-reactivity. In addition, the WKY rat is glucose intolerant and likely harbors diabetes susceptibility alleles. We conducted a quantitative trait loci (QTL) analysis in the segregating F2 population of a WKY × Fischer 344 (F344) inter-cross. We have previously published QTL analyses for depressive behavior and hypothalamic-pituitary-adrenal (HPA) activity in this cross. In the current study, we report results from the QTL analysis for multiple metabolic phenotypes, including fasting glucose, post-restraint stress glucose, post-prandial glucose and insulin, and body weight. We identified multiple QTLs for each trait and many of the QTLs overlap with those previously identified using inbred models of type 2 diabetes (T2D). Significant correlations were found between metabolic traits and HPA axis measures and several metabolic loci overlap with loci previously identified for HPA activity in this F2 intercross, suggesting the genetic mechanisms underlying these traits may be similar. These results indicate that WKY rats harbor diabetes susceptibility alleles and suggest that this strain may be useful for dissecting the underlying genetic mechanisms linking diabetes, HPA activity and depression. PMID:19697080

  17. Analysis of human mini-exome sequencing data from Genetic Analysis Workshop 17 using a Bayesian hierarchical mixture model

    PubMed Central

    2011-01-01

    Next-generation sequencing technologies are rapidly changing the field of genetic epidemiology and enabling exploration of the full allele frequency spectrum underlying complex diseases. Although sequencing technologies have shifted our focus toward rare genetic variants, statistical methods traditionally used in genetic association studies are inadequate for estimating effects of low minor allele frequency variants. Four our study we use the Genetic Analysis Workshop 17 data from 697 unrelated individuals (genotypes for 24,487 autosomal variants from 3,205 genes). We apply a Bayesian hierarchical mixture model to identify genes associated with a simulated binary phenotype using a transformed genotype design matrix weighted by allele frequencies. A Metropolis Hasting algorithm is used to jointly sample each indicator variable and additive genetic effect pair from its conditional posterior distribution, and remaining parameters are sampled by Gibbs sampling. This method identified 58 genes with a posterior probability greater than 0.8 for being associated with the phenotype. One of these 58 genes, PIK3C2B was correctly identified as being associated with affected status based on the simulation process. This project demonstrates the utility of Bayesian hierarchical mixture models using a transformed genotype matrix to detect genes containing rare and common variants associated with a binary phenotype. PMID:22373180

  18. Genetic and genomic analysis of RNases in model cyanobacteria.

    PubMed

    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.

  19. Ballooning dispersal using silk: world fauna, phylogenies, genetics and models.

    PubMed

    Bell, J R; Bohan, D A; Shaw, E M; Weyman, G S

    2005-04-01

    Aerial dispersal using silk ('ballooning') has evolved in spiders (Araneae), spider mites (Acari) and in the larvae of moths (Lepidoptera). Since the 17th century, over 500 observations of ballooning behaviours have been published, yet there is an absence of any evolutionary synthesis of these data. In this paper the literature is reviewed, extensively documenting the known world fauna that balloon and the principal behaviours involved. This knowledge is then incorporated into the current evolutionary phylogenies to examine how ballooning might have arisen. Whilst it is possible that ballooning co-evolved with silk and emerged as early as the Devonian (410-355 mya), it is arguably more likely that ballooning evolved in parallel with deciduous trees, herbaceous annuals and grasses in the Cretaceous (135-65 mya). During this period, temporal (e.g. bud burst, chlorophyll thresholds) and spatial (e.g. herbivory, trampling) heterogeneities in habitat structuring predominated and intensified into the Cenozoic (65 mya to the present). It is hypothesized that from the ancestral launch mechanism known as 'suspended ballooning', widely used by individuals in plant canopies, 'tip-toe' and 'rearing' take-off behaviours were strongly selected for as habitats changed. It is contended that ballooning behaviour in all three orders can be described as a mixed Evolutionary Stable Strategy. This comprises individual bet-hedging due to habitat unpredictability, giving an underlying randomness to individual ballooning, with adjustments to the individual ballooning probability being conferred by more predictable habitat changes or colonization strategies. Finally, current methods used to study ballooning, including modelling and genetic research, are illustrated and an indication of future prospects given.

  20. A generalized additive model for the spatial distribution of snowpack in the Spanish Pyrenees

    NASA Astrophysics Data System (ADS)

    López-Moreno, J. I.; Nogués-Bravo, D.

    2005-10-01

    A generalized additive model (GAM) was used to model the spatial distribution of snow depth in the central Spanish Pyrenees. Statistically significant non-linear relationships were found between distinct location and topographical variables and the average depth of the April snowpack at 76 snow poles from 1985 to 2000. The joint effect of the predictor variables explained more than 73% of the variance of the dependent variable. The performance of the model was assessed by applying a number of quantitative approaches to the residuals from a cross-validation test. The relatively low estimated errors and the possibility of understanding the processes that control snow accumulation, through the response curves of each independent variable, indicate that GAMs may be a useful tool for interpolating local snow depth or other climate parameters.

  1. Parity Symmetry and Parity Breaking in the Quantum Rabi Model with Addition of Ising Interaction

    NASA Astrophysics Data System (ADS)

    Wang, Qiong; He, Zhi; Yao, Chun-Mei

    2015-04-01

    We explore the possibility to generate new parity symmetry in the quantum Rabi model after a bias is introduced. In contrast to a mathematical treatment in a previous publication [J. Phys. A 46 (2013) 265302], we consider a physically realistic method by involving an additional spin into the quantum Rabi model to couple with the original spin by an Ising interaction, and then the parity symmetry is broken as well as the scaling behavior of the ground state by introducing a bias. The rule can be found that the parity symmetry is broken by introducing a bias and then restored by adding new degrees of freedom. Experimental feasibility of realizing the models under discussion is investigated. Supported by the National Natural Science Foundation of China under Grant Nos. 61475045 and 11347142, the Natural Science Foundation of Hunan Province, China under Grant No. 2015JJ3092

  2. Evaporation model for beam based additive manufacturing using free surface lattice Boltzmann methods

    NASA Astrophysics Data System (ADS)

    Klassen, Alexander; Scharowsky, Thorsten; Körner, Carolin

    2014-07-01

    Evaporation plays an important role in many technical applications including beam-based additive manufacturing processes, such as selective electron beam or selective laser melting (SEBM/SLM). In this paper, we describe an evaporation model which we employ within the framework of a two-dimensional free surface lattice Boltzmann method. With this method, we solve the hydrodynamics as well as thermodynamics of the molten material taking into account the mass and energy losses due to evaporation and the recoil pressure acting on the melt pool. Validation of the numerical model is performed by measuring maximum melt depths and evaporative losses in samples of pure titanium and Ti-6Al-4V molten by an electron beam. Finally, the model is applied to create processing maps for an SEBM process. The results predict that the penetration depth of the electron beam, which is a function of the acceleration voltage, has a significant influence on evaporation effects.

  3. New research avenues in toxicology: 7-gas N-Gas Model, toxicant suppressants, and genetic toxicology.

    PubMed

    Levin, B C

    1996-12-31

    Three research areas -- a 7-gas N-Gas Model, toxicant suppressants, and genetic toxicology -- are presented as new research approaches in toxicology. The current 6-gas N-Gas Model predicts the toxic potency of the combustion products of materials based on the toxicological interactions of the fire gases carbon monoxide (CO), carbon dioxide (CO2), low oxygen (O2) concentrations, hydrogen cyanide (HCN), hydrogen chloride, and hydrogen bromide. The present research includes nitrogen dioxide (NO2) in a new 7-gas model which incorporates the synergistic effects of NO2 and CO2, the antagonistic effects of NO2 and HCN, and the additive effects of NO2 with CO and low O2. The area of toxicant suppressants concerns chemicals, which when added to a material, will inhibit or reduce the concentration of a specific toxic gas normally generated during thermal decomposition of that material. The effectiveness of this approach was demonstrated at the US National Institute of Standards and Technology when HCN generation was reduced by 90% and the resultant toxicity of the combustion products was lowered by 50% when a flexible polyurethane (FPU) foam was treated with 0.1% (by weight) cuprous oxide (Cu2O). Although melamine-treated FPU foams are being promoted as more fire safe than standard foams, a melamine-treated foam generated 10 times more HCN than a foam without melamine. The addition of Cu2O to this melamine foam also reduced the HCN generation by 90%. The genetic toxicology research entails the examination of DNA damage that results from the exposure of human cells to various environmental toxicants and gases.

  4. Assessing a landscape barrier using genetic simulation modelling: implications for raccoon rabies management.

    PubMed

    Rees, Erin E; Pond, Bruce A; Cullingham, Catherine I; Tinline, Rowland; Ball, David; Kyle, Christopher J; White, Bradley N

    2008-08-15

    Landscape barriers influence movement patterns of animals, which in turn, affect spatio-temporal spread of infectious wildlife disease. We compare genetic data from computer simulations to those acquired from field samples to measure the effect of a landscape barrier on raccoon (Procyon lotor) movement, enabling risk assessment of raccoon rabies disease spread across the Niagara River from New York State into Ontario, an area currently uninfected by rabies. An individual-based spatially explicit model is used to simulate the expansion of a raccoon population to cross the Niagara River, for different permeabilities of the river to raccoon crossings. Since the model records individual raccoon genetics, the genetic population structure of neutral mitochondrial DNA haplotypes are characterised in the expanding population, every 25 years, using a genetic distance measure, phi ST, Mantel tests and a gene diversity measure. The river barrier effect is assessed by comparing genetic measures computed from model outputs to those calculated from 166 raccoons recently sampled from the same landscape. The "best fit" between modelled scenarios and field data indicate the river prevents 50% of attempts to cross the river. Founder effects dominated the colonizing genetic population structure, and, as the river barrier effect increased, its genetic diversity decreased. Using gene flow to calibrate the effect of the river as a barrier to movement provides an estimate of the effect of a river in reducing the likelihood of cross-river infection. Including individual genetic markers in simulation modelling benefits investigations of disease spread and control.

  5. UV exposure, genetic targets in melanocytic tumors and transgenic mouse models.

    PubMed

    de Gruijl, Frank R; van Kranen, Henk J; van Schanke, Arne

    2005-01-01

    The genetic changes and corruption of kinase activity in melanomas appear to revolve around a central axis: mitogenic signaling along the RAS pathway down to transcription regulation by pRB. Epidemiological studies point to the importance of ultraviolet (UV) radiation in the etiology of melanoma, but where and how UV radiation is targeted to contribute to the oncogenic signaling remains obscure. Animal models of melanoma genesis could serve to clarify this issue, but many of these models are not responsive to UV exposure. Most interesting advances have been made by using transgenic mice that carry genetic defects that are known to be relevant to human melanoma: specifically, dysfunction in the tumor suppressive action of p16INK4a or a receptor tyrosine kinase/RAS pathway, that is constitutively activated in melanocytes. The latter types of mice appear to be most responsive to (neonatal) UV exposure. Whether this is due to a general increase in target cells by melanocytosis and a paucity or complete lack of pigment, or a possible UV-induced response of the promoter-enhancer of the transgene or a genuinely independent and additional genetic alteration caused by UV exposure needs to be established. Importantly, the full effect of UV radiation needs to be ascertained in mice with different pigmentation by varying the wavelengths, UV-B versus UV-A1, and the exposure schedules, i.e. neonatal versus adult and chronic versus intermittent overexposure. Intermittent UV-B overexposure deserves special attention because it most strongly evokes proliferative responses in melanocytes.

  6. Wall-models for large eddy simulation based on a generic additive-filter formulation

    NASA Astrophysics Data System (ADS)

    Sanchez Rocha, Martin

    Based on the philosophy of only resolving the large scales of turbulent motion, Large Eddy Simulation (LES) has demonstrated potential to provide high-fidelity turbulence simulations at low computational cost. However, when the scales that control the turbulence in a particular flow are not large, LES has to increase significantly its computational cost to provide accurate predictions. This is the case in wall-bounded flows, where the grid resolution required by LES to resolve the near-wall structures is close to the requirements to resolve the smallest dissipative scales in turbulence. Therefore, to reduce this demanding requirement, it has been proposed to model the near-wall region with Reynolds-Averaged Navier-Stokes (RANS) models, in what is known as hybrid RANS/LES approach. In this work, the mathematical implications of merging two different turbulence modeling approaches are addressed by deriving the exact hybrid RANS/LES Navier-Stokes equations. These equations are derived by introducing an additive-filter, which linearly combines the RANS and LES operators with a blending function. The equations derived with the additive-filter predict additional hybrid terms, which represent the interactions between RANS and LES formulations. Theoretically, the prediction of the hybrid terms demonstrates that the hybridization of the two approaches cannot be accomplished only by the turbulence model equations, as it is claimed in current hybrid RANS/LES models. The importance of the exact hybrid RANS/LES equations is demonstrated by conducting numerical calculations on a turbulent flat-plate boundary layer. Results indicate that the hybrid terms help to maintain an equilibrated model transition when the hybrid formulation switches from RANS to LES. Results also indicate, that when the hybrid terms are not included, the accuracy of the calculations strongly relies on the blending function implemented in the additive-filter. On the other hand, if the exact equations are

  7. Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction.

    PubMed

    Cardoso, F F; Tempelman, R J

    2012-07-01

    The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of

  8. Reduction of carcinogenic 4(5)-methylimidazole in a caramel model system: influence of food additives.

    PubMed

    Seo, Seulgi; Ka, Mi-Hyun; Lee, Kwang-Geun

    2014-07-01

    The effect of various food additives on the formation of carcinogenic 4(5)-methylimidazole (4-MI) in a caramel model system was investigated. The relationship between the levels of 4-MI and various pyrazines was studied. When glucose and ammonium hydroxide were heated, the amount of 4-MI was 556 ± 1.3 μg/mL, which increased to 583 ± 2.6 μg/mL by the addition of 0.1 M of sodium sulfite. When various food additives, such as 0.1 M of iron sulfate, magnesium sulfate, zinc sulfate, tryptophan, and cysteine were added, the amount of 4-MI was reduced to 110 ± 0.7, 483 ± 2.0, 460 ± 2.0, 409 ± 4.4, and 397 ± 1.7 μg/mL, respectively. The greatest reduction, 80%, occurred with the addition of iron sulfate. Among the 12 pyrazines, 2-ethyl-6-methylpyrazine with 4-MI showed the highest correlation (r = -0.8239).

  9. Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

    PubMed

    Ayres, D R; Pereira, R J; Boligon, A A; Silva, F F; Schenkel, F S; Roso, V M; Albuquerque, L G

    2013-12-01

    Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. PMID:24236604

  10. New Genetics

    MedlinePlus

    ... human genome, behavioral genetics, pharmacogenetics, drug resistance, biofilms, computer modeling. » more Chapter 5: 21st-Century Genetics Covers systems biology, GFP, genetic testing, privacy concerns, DNA forensics, ...

  11. Analysis of Time to Event Outcomes in Randomized Controlled Trials by Generalized Additive Models

    PubMed Central

    Argyropoulos, Christos; Unruh, Mark L.

    2015-01-01

    Background Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure. Despite the widespread adoption of HRs, these provide a limited understanding of the treatment effect and may even provide a biased estimate when the assumption of proportional hazards in the Cox model is not verified by the trial data. Additional treatment effect measures on the survival probability or the time scale may be used to supplement HRs but a framework for the simultaneous generation of these measures is lacking. Methods By splitting follow-up time at the nodes of a Gauss Lobatto numerical quadrature rule, techniques for Poisson Generalized Additive Models (PGAM) can be adopted for flexible hazard modeling. Straightforward simulation post-estimation transforms PGAM estimates for the log hazard into estimates of the survival function. These in turn were used to calculate relative and absolute risks or even differences in restricted mean survival time between treatment arms. We illustrate our approach with extensive simulations and in two trials: IPASS (in which the proportionality of hazards was violated) and HEMO a long duration study conducted under evolving standards of care on a heterogeneous patient population. Findings PGAM can generate estimates of the survival function and the hazard ratio that are essentially identical to those obtained by Kaplan Meier curve analysis and the Cox model. PGAMs can simultaneously provide multiple measures of treatment efficacy after a single data pass. Furthermore, supported unadjusted (overall treatment effect) but also subgroup and adjusted analyses, while incorporating multiple time scales and accounting for non-proportional hazards in survival data. Conclusions By augmenting the HR conventionally reported, PGAMs have the potential to support the inferential goals of multiple stakeholders involved in the evaluation and appraisal of clinical trial

  12. Topsoil organic carbon content of Europe, a new map based on a generalised additive model

    NASA Astrophysics Data System (ADS)

    de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

    2014-05-01

    There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average

  13. Improving the predictive accuracy of hurricane power outage forecasts using generalized additive models.

    PubMed

    Han, Seung-Ryong; Guikema, Seth D; Quiring, Steven M

    2009-10-01

    Electric power is a critical infrastructure service after hurricanes, and rapid restoration of electric power is important in order to minimize losses in the impacted areas. However, rapid restoration of electric power after a hurricane depends on obtaining the necessary resources, primarily repair crews and materials, before the hurricane makes landfall and then appropriately deploying these resources as soon as possible after the hurricane. This, in turn, depends on having sound estimates of both the overall severity of the storm and the relative risk of power outages in different areas. Past studies have developed statistical, regression-based approaches for estimating the number of power outages in advance of an approaching hurricane. However, these approaches have either not been applicable for future events or have had lower predictive accuracy than desired. This article shows that a different type of regression model, a generalized additive model (GAM), can outperform the types of models used previously. This is done by developing and validating a GAM based on power outage data during past hurricanes in the Gulf Coast region and comparing the results from this model to the previously used generalized linear models.

  14. The genetic basis of emotional behavior: has the time come for a Drosophila model?

    PubMed

    Iliadi, Konstantin G

    2009-01-01

    The aim of this review was to summarize the studies potentially relevant to whether Drosophila can be used as a genetically tractable model to study the genetic and molecular basis of emotional behavior. Can these studies contribute to a better understanding of neural substrates of abnormal emotional states and specific neuropsychiatric illnesses, such as depression and anxiety? PMID:19107631

  15. Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data

    PubMed Central

    TAPAK, Leili; MAHJUB, Hossein; SADEGHIFAR, Majid; SAIDIJAM, Massoud; POOROLAJAL, Jalal

    2016-01-01

    Background: One substantial part of microarray studies is to predict patients’ survival based on their gene expression profile. Variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. However, these techniques have not been investigated in competing risks setting. This study aimed to investigate the performance of four sparse variable selection methods in estimating the survival time. Methods: The data included 1381 gene expression measurements and clinical information from 301 patients with bladder cancer operated in the years 1987 to 2000 in hospitals in Denmark, Sweden, Spain, France, and England. Four methods of the least absolute shrinkage and selection operator, smoothly clipped absolute deviation, the smooth integration of counting and absolute deviation and elastic net were utilized for simultaneous variable selection and estimation under an additive hazards model. The criteria of area under ROC curve, Brier score and c-index were used to compare the methods. Results: The median follow-up time for all patients was 47 months. The elastic net approach was indicated to outperform other methods. The elastic net had the lowest integrated Brier score (0.137±0.07) and the greatest median of the over-time AUC and C-index (0.803±0.06 and 0.779±0.13, respectively). Five out of 19 selected genes by the elastic net were significant (P<0.05) under an additive hazards model. It was indicated that the expression of RTN4, SON, IGF1R and CDC20 decrease the survival time, while the expression of SMARCAD1 increase it. Conclusion: The elastic net had higher capability than the other methods for the prediction of survival time in patients with bladder cancer in the presence of competing risks base on additive hazards model. PMID:27114989

  16. Comparison of prosthetic models produced by traditional and additive manufacturing methods

    PubMed Central

    Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong

    2015-01-01

    PURPOSE The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). MATERIALS AND METHODS Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). RESULTS The mean marginal gaps and internal gaps showed significant differences according to tooth type (P<.001 and P<.001, respectively) and manufacturing method (P<.037 and P<.001, respectively). Micro-SLA did not show any significant difference from CLWT regarding mean marginal gap compared to the WBM and MJM methods. CONCLUSION The mean values of gaps resulting from the four different manufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing. PMID:26330976

  17. Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

    PubMed

    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.

  18. Modelling and genetic algorithm based optimisation of inverse supply chain

    NASA Astrophysics Data System (ADS)

    Bányai, T.

    2009-04-01

    (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a

  19. Thermodynamic network model for predicting effects of substrate addition and other perturbations on subsurface microbial communities

    SciTech Connect

    Jack Istok; Melora Park; James McKinley; Chongxuan Liu; Lee Krumholz; Anne Spain; Aaron Peacock; Brett Baldwin

    2007-04-19

    The overall goal of this project is to develop and test a thermodynamic network model for predicting the effects of substrate additions and environmental perturbations on microbial growth, community composition and system geochemistry. The hypothesis is that a thermodynamic analysis of the energy-yielding growth reactions performed by defined groups of microorganisms can be used to make quantitative and testable predictions of the change in microbial community composition that will occur when a substrate is added to the subsurface or when environmental conditions change.

  20. An implementation of continuous genetic algorithm in parameter estimation of predator-prey model

    NASA Astrophysics Data System (ADS)

    Windarto

    2016-03-01

    Genetic algorithm is an optimization method based on the principles of genetics and natural selection in life organisms. The main components of this algorithm are chromosomes population (individuals population), parent selection, crossover to produce new offspring, and random mutation. In this paper, continuous genetic algorithm was implemented to estimate parameters in a predator-prey model of Lotka-Volterra type. For simplicity, all genetic algorithm parameters (selection rate and mutation rate) are set to be constant along implementation of the algorithm. It was found that by selecting suitable mutation rate, the algorithms can estimate these parameters well.

  1. A genetic developmental model of iron deficiency: biological aspects.

    PubMed

    Morse, A C; Beard, J L; Jones, B C

    1999-03-01

    Numerous studies have demonstrated the negative impact of iron deficiency on growth and development. The present study expands on the published literature by exploring the role of genetics and developmental timing on the impact of iron deficiency on development in two strains of mice. Growth rates, organ weights, and hematological responses to an iron-deficient diet differed by strain and sex. The results from this study provided novel insight into iron metabolism and the impact of iron deficiency in C57 and DBA strains of mice. Future studies should continue to examine the contributions of both genetics and sex to the development of iron deficiency.

  2. Efficacy of targeted AKT inhibition in genetically engineered mouse models of PTEN-deficient prostate cancer.

    PubMed

    De Velasco, Marco A; Kura, Yurie; Yoshikawa, Kazuhiro; Nishio, Kazuto; Davies, Barry R; Uemura, Hirotsugu

    2016-03-29

    The PI3K/AKT pathway is frequently altered in advanced human prostate cancer mainly through the loss of functional PTEN, and presents as potential target for personalized therapy. Our aim was to determine the therapeutic potential of the pan-AKT inhibitor, AZD5363, in PTEN-deficient prostate cancer. Here we used a genetically engineered mouse (GEM) model of PTEN-deficient prostate cancer to evaluate the in vivo pharmacodynamic and antitumor activity of AZD5363 in castration-naïve and castration-resistant prostate cancer. An additional GEM model, based on the concomitant inactivation of PTEN and Trp53 (P53), was established as an aggressive model of advanced prostate cancer and was used to further evaluate clinically relevant endpoints after treatment with AZD5363. In vivo pharmacodynamic studies demonstrated that AZD5363 effectively inhibited downstream targets of AKT. AZD5363 monotherapy significantly reduced growth of tumors in castration-naïve and castration-resistant models of PTEN-deficient prostate cancer. More importantly, AZD5363 significantly delayed tumor growth and improved overall survival and progression-free survival in PTEN/P53 double knockout mice. Our findings demonstrate that AZD5363 is effective against GEM models of PTEN-deficient prostate cancer and provide lines of evidence to support further investigation into the development of treatment strategies targeting AKT for the treatment of PTEN-deficient prostate cancer.

  3. A genetic mouse model for progressive ablation and regeneration of insulin producing beta-cells

    PubMed Central

    Shamsi, Farnaz; Parlato, Rosanna; Collombat, Patrick; Mansouri, Ahmed

    2014-01-01

    The putative induction of adult β-cell regeneration represents a promising approach for the treatment of type 1 diabetes. Toward this ultimate goal, it is essential to develop an inducible model mimicking the long-lasting disease progression. In the current study, we have established a novel β-cell ablation mouse model, in which the β-cell mass progressively declines, as seen in type 1 diabetes. The model is based on the β-cell specific genetic ablation of the transcription initiation factor 1A, TIF-IA, essential for RNA Polymerase I activity (TIF-IAΔ/Δ). Using this approach, we induced a slow apoptotic response that eventually leads to a protracted β-cell death. In this model, we observed β-cell regeneration that resulted in a complete recovery of the β-cell mass and normoglycemia. In addition, we showed that adaptive proliferation of remaining β-cells is the prominent mechanism acting to compensate for the massive β-cell loss in young but also aged mice. Interestingly, at any age, we also detected β-like cells expressing the glucagon hormone, suggesting a transition between α- and β-cell identities or vice versa. Taken together, the TIF-IAΔ/Δ mouse model can be used to investigate the potential therapeutic approaches for type 1 diabetes targeting β-cell regeneration. PMID:25558832

  4. Genome editing revolutionize the creation of genetically modified pigs for modeling human diseases.

    PubMed

    Yao, Jing; Huang, Jiaojiao; Zhao, Jianguo

    2016-09-01

    Pigs have anatomical, physiological and genomic characteristics that make them highly suitable for modeling human diseases. Genetically modified (GM) pig models of human diseases are critical for studying pathogenesis, treatment, and prevention. The emergence of nuclease-mediated genome editing technology has been successfully employed for engineering of the pig genome, which has revolutionize the creation of GM pig models with highly complex pathophysiologies and comorbidities. In this review, we summarize the progress of recently developed genome editing technologies, including zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9), which enable highly efficient and precise introduction of genome modifications into pigs, and tailored disease models that have been generated in various disciplines via genome editing technology. We also summarize the GM pig models that have been generated by conventional transgenic strategies. Additionally, perspectives regarding the application of GM pigs in biomedical research are discussed.

  5. Efficacy of targeted AKT inhibition in genetically engineered mouse models of PTEN-deficient prostate cancer

    PubMed Central

    De Velasco, Marco A.; Kura, Yurie; Yoshikawa, Kazuhiro; Nishio, Kazuto; Davies, Barry R.; Uemura, Hirotsugu

    2016-01-01

    The PI3K/AKT pathway is frequently altered in advanced human prostate cancer mainly through the loss of functional PTEN, and presents as potential target for personalized therapy. Our aim was to determine the therapeutic potential of the pan-AKT inhibitor, AZD5363, in PTEN-deficient prostate cancer. Here we used a genetically engineered mouse (GEM) model of PTEN-deficient prostate cancer to evaluate the in vivo pharmacodynamic and antitumor activity of AZD5363 in castration-naïve and castration-resistant prostate cancer. An additional GEM model, based on the concomitant inactivation of PTEN and Trp53 (P53), was established as an aggressive model of advanced prostate cancer and was used to further evaluate clinically relevant endpoints after treatment with AZD5363. In vivo pharmacodynamic studies demonstrated that AZD5363 effectively inhibited downstream targets of AKT. AZD5363 monotherapy significantly reduced growth of tumors in castration-naïve and castration-resistant models of PTEN-deficient prostate cancer. More importantly, AZD5363 significantly delayed tumor growth and improved overall survival and progression-free survival in PTEN/P53 double knockout mice. Our findings demonstrate that AZD5363 is effective against GEM models of PTEN-deficient prostate cancer and provide lines of evidence to support further investigation into the development of treatment strategies targeting AKT for the treatment of PTEN-deficient prostate cancer. PMID:26910118

  6. Generalized additive models and Lucilia sericata growth: assessing confidence intervals and error rates in forensic entomology.

    PubMed

    Tarone, Aaron M; Foran, David R

    2008-07-01

    Forensic entomologists use blow fly development to estimate a postmortem interval. Although accurate, fly age estimates can be imprecise for older developmental stages and no standard means of assigning confidence intervals exists. Presented here is a method for modeling growth of the forensically important blow fly Lucilia sericata, using generalized additive models (GAMs). Eighteen GAMs were created to predict the extent of juvenile fly development, encompassing developmental stage, length, weight, strain, and temperature data, collected from 2559 individuals. All measures were informative, explaining up to 92.6% of the deviance in the data, though strain and temperature exerted negligible influences. Predictions made with an independent data set allowed for a subsequent examination of error. Estimates using length and developmental stage were within 5% of true development percent during the feeding portion of the larval life cycle, while predictions for postfeeding third instars were less precise, but within expected error.

  7. A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

    PubMed Central

    Anacleto, Osvaldo; Garcia-Cortés, Luis Alberto; Lipschutz-Powell, Debby; Woolliams, John A.; Doeschl-Wilson, Andrea B.

    2015-01-01

    There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations. PMID:26405030

  8. Using genetic mouse models to gain insight into glaucoma: Past results and future possibilities.

    PubMed

    Fernandes, Kimberly A; Harder, Jeffrey M; Williams, Pete A; Rausch, Rebecca L; Kiernan, Amy E; Nair, K Saidas; Anderson, Michael G; John, Simon W M; Howell, Gareth R; Libby, Richard T

    2015-12-01

    While all forms of glaucoma are characterized by a specific pattern of retinal ganglion cell death, they are clinically divided into several distinct subclasses, including normal tension glaucoma, primary open angle glaucoma, congenital glaucoma, and secondary glaucoma. For each type of glaucoma there are likely numerous molecular pathways that control susceptibility to the disease. Given this complexity, a single animal model will never precisely model all aspects of all the different types of human glaucoma. Therefore, multiple animal models have been utilized to study glaucoma but more are needed. Because of the powerful genetic tools available to use in the laboratory mouse, it has proven to be a highly useful mammalian system for studying the pathophysiology of human disease. The similarity between human and mouse eyes coupled with the ability to use a combination of advanced cell biological and genetic tools in mice have led to a large increase in the number of studies using mice to model specific glaucoma phenotypes. Over the last decade, numerous new mouse models and genetic tools have emerged, providing important insight into the cell biology and genetics of glaucoma. In this review, we describe available mouse genetic models that can be used to study glaucoma-relevant disease/pathobiology. Furthermore, we discuss how these models have been used to gain insights into ocular hypertension (a major risk factor for glaucoma) and glaucomatous retinal ganglion cell death. Finally, the potential for developing new mouse models and using advanced genetic tools and resources for studying glaucoma are discussed.

  9. Definition of Historical Models of Gene Function and Their Relation to Students' Understanding of Genetics

    ERIC Educational Resources Information Center

    Gericke, Niklas Markus; Hagberg, Mariana

    2007-01-01

    Models are often used when teaching science. In this paper historical models and students' ideas about genetics are compared. The historical development of the scientific idea of the gene and its function is described and categorized into five historical models of gene function. Differences and similarities between these historical models are made…

  10. Guarana provides additional stimulation over caffeine alone in the planarian model.

    PubMed

    Moustakas, Dimitrios; Mezzio, Michael; Rodriguez, Branden R; Constable, Mic Andre; Mulligan, Margaret E; Voura, Evelyn B

    2015-01-01

    The stimulant effect of energy drinks is primarily attributed to the caffeine they contain. Many energy drinks also contain other ingredients that might enhance the tonic effects of these caffeinated beverages. One of these additives is guarana. Guarana is a climbing plant native to the Amazon whose seeds contain approximately four times the amount of caffeine found in coffee beans. The mix of other natural chemicals contained in guarana seeds is thought to heighten the stimulant effects of guarana over caffeine alone. Yet, despite the growing use of guarana as an additive in energy drinks, and a burgeoning market for it as a nutritional supplement, the science examining guarana and how it affects other dietary ingredients is lacking. To appreciate the stimulant effects of guarana and other natural products, a straightforward model to investigate their physiological properties is needed. The planarian provides such a system. The locomotor activity and convulsive response of planarians with substance exposure has been shown to provide an excellent system to measure the effects of drug stimulation, addiction and withdrawal. To gauge the stimulant effects of guarana we studied how it altered the locomotor activity of the planarian species Dugesia tigrina. We report evidence that guarana seeds provide additional stimulation over caffeine alone, and document the changes to this stimulation in the context of both caffeine and glucose. PMID:25880065

  11. Analysis and Modeling of soil hydrology under different soil additives in artificial runoff plots

    NASA Astrophysics Data System (ADS)

    Ruidisch, M.; Arnhold, S.; Kettering, J.; Huwe, B.; Kuzyakov, Y.; Ok, Y.; Tenhunen, J. D.

    2009-12-01

    The impact of monsoon events during June and July in the Korean project region Haean Basin, which is located in the northeastern part of South Korea plays a key role for erosion, leaching and groundwater pollution risk by agrochemicals. Therefore, the project investigates the main hydrological processes in agricultural soils under field and laboratory conditions on different scales (plot, hillslope and catchment). Soil hydrological parameters were analysed depending on different soil additives, which are known for prevention of soil erosion and nutrient loss as well as increasing of water infiltration, aggregate stability and soil fertility. Hence, synthetic water-soluble Polyacrylamides (PAM), Biochar (Black Carbon mixed with organic fertilizer), both PAM and Biochar were applied in runoff plots at three agricultural field sites. Additionally, as control a subplot was set up without any additives. The field sites were selected in areas with similar hillslope gradients and with emphasis on the dominant land management form of dryland farming in Haean, which is characterised by row planting and row covering by foil. Hydrological parameters like satured water conductivity, matrix potential and water content were analysed by infiltration experiments, continuous tensiometer measurements, time domain reflectometry as well as pressure plates to indentify characteristic water retention curves of each horizon. Weather data were observed by three weather stations next to the runoff plots. Measured data also provide the input data for modeling water transport in the unsatured zone in runoff plots with HYDRUS 1D/2D/3D and SWAT (Soil & Water Assessment Tool).

  12. Guarana provides additional stimulation over caffeine alone in the planarian model.

    PubMed

    Moustakas, Dimitrios; Mezzio, Michael; Rodriguez, Branden R; Constable, Mic Andre; Mulligan, Margaret E; Voura, Evelyn B

    2015-01-01

    The stimulant effect of energy drinks is primarily attributed to the caffeine they contain. Many energy drinks also contain other ingredients that might enhance the tonic effects of these caffeinated beverages. One of these additives is guarana. Guarana is a climbing plant native to the Amazon whose seeds contain approximately four times the amount of caffeine found in coffee beans. The mix of other natural chemicals contained in guarana seeds is thought to heighten the stimulant effects of guarana over caffeine alone. Yet, despite the growing use of guarana as an additive in energy drinks, and a burgeoning market for it as a nutritional supplement, the science examining guarana and how it affects other dietary ingredients is lacking. To appreciate the stimulant effects of guarana and other natural products, a straightforward model to investigate their physiological properties is needed. The planarian provides such a system. The locomotor activity and convulsive response of planarians with substance exposure has been shown to provide an excellent system to measure the effects of drug stimulation, addiction and withdrawal. To gauge the stimulant effects of guarana we studied how it altered the locomotor activity of the planarian species Dugesia tigrina. We report evidence that guarana seeds provide additional stimulation over caffeine alone, and document the changes to this stimulation in the context of both caffeine and glucose.

  13. Guarana Provides Additional Stimulation over Caffeine Alone in the Planarian Model

    PubMed Central

    Moustakas, Dimitrios; Mezzio, Michael; Rodriguez, Branden R.; Constable, Mic Andre; Mulligan, Margaret E.; Voura, Evelyn B.

    2015-01-01

    The stimulant effect of energy drinks is primarily attributed to the caffeine they contain. Many energy drinks also contain other ingredients that might enhance the tonic effects of these caffeinated beverages. One of these additives is guarana. Guarana is a climbing plant native to the Amazon whose seeds contain approximately four times the amount of caffeine found in coffee beans. The mix of other natural chemicals contained in guarana seeds is thought to heighten the stimulant effects of guarana over caffeine alone. Yet, despite the growing use of guarana as an additive in energy drinks, and a burgeoning market for it as a nutritional supplement, the science examining guarana and how it affects other dietary ingredients is lacking. To appreciate the stimulant effects of guarana and other natural products, a straightforward model to investigate their physiological properties is needed. The planarian provides such a system. The locomotor activity and convulsive response of planarians with substance exposure has been shown to provide an excellent system to measure the effects of drug stimulation, addiction and withdrawal. To gauge the stimulant effects of guarana we studied how it altered the locomotor activity of the planarian species Dugesia tigrina. We report evidence that guarana seeds provide additional stimulation over caffeine alone, and document the changes to this stimulation in the context of both caffeine and glucose. PMID:25880065

  14. Genetic versus phenotypic models of selection: can genetics be neglected in a long-term perspective?

    PubMed

    Weissing, F J

    1996-01-01

    Game theoretical concepts in evolutionary biology have been criticized by populations geneticists, because they neglect such crucial aspects as the mating system or the mode of inheritance. In fact, the dynamics of natural selection does not necessarily lead to a fitness maximum or an ESS if genetic constraints are taken into account. Yet, it may be premature to conclude that game theoretical concepts do not have a dynamical justification. The new paradigm of long-term evolution postulates that genetic constraints, which may be dominant in a short-term perspective, will in the long run disappear in the face of the ongoing influx of mutations. Two basic results (see Hammerstein; this issue) seem to reconcile the dynamical approach of long-term population genetics with the static approach of evolutionary game theory: (1) only populations at local fitness optima (Nash strategies) can be long-term stable; and (2) in monomorphic populations, evolutionary stability is necessary and sufficient to ensure long-term dynamic stability. The present paper has a double purpose. On the one hand, it is demonstrated by fairly general arguments that the scope of the results mentioned above extends to non-linear frequency dependent selection, to multiple loci, and to quite general mating systems. On the other hand, some limitations of the theory of long-term evolution will also be stressed: (1) there is little hope for a game theoretical characterization of stability in polymorphic populations; (2) many interesting systems do not admit long-term stable equilibria; and (3) even if a long-term stable equilibrium exists, it is not at all clear whether and how it is attainable by a series of gene substitution events.

  15. Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models.

    PubMed

    Fan, Jianqing; Feng, Yang; Song, Rui

    2011-06-01

    A variable screening procedure via correlation learning was proposed in Fan and Lv (2008) to reduce dimensionality in sparse ultra-high dimensional models. Even when the true model is linear, the marginal regression can be highly nonlinear. To address this issue, we further extend the correlation learning to marginal nonparametric learning. Our nonparametric independence screening is called NIS, a specific member of the sure independence screening. Several closely related variable screening procedures are proposed. Under general nonparametric models, it is shown that under some mild technical conditions, the proposed independence screening methods enjoy a sure screening property. The extent to which the dimensionality can be reduced by independence screening is also explicitly quantified. As a methodological extension, a data-driven thresholding and an iterative nonparametric independence screening (INIS) are also proposed to enhance the finite sample performance for fitting sparse additive models. The simulation results and a real data analysis demonstrate that the proposed procedure works well with moderate sample size and large dimension and performs better than competing methods.

  16. Model Scramjet Inlet Unstart Induced by Mass Addition and Heat Release

    NASA Astrophysics Data System (ADS)

    Im, Seong-Kyun; Baccarella, Damiano; McGann, Brendan; Liu, Qili; Wermer, Lydiy; Do, Hyungrok

    2015-11-01

    The inlet unstart phenomena in a model scramjet are investigated at an arc-heated hypersonic wind tunnel. The unstart induced by nitrogen or ethylene jets at low or high enthalpy Mach 4.5 freestream flow conditions are compared. The jet injection pressurizes the downstream flow by mass addition and flow blockage. In case of the ethylene jet injection, heat release from combustion increases the backpressure further. Time-resolved schlieren imaging is performed at the jet and the lip of the model inlet to visualize the flow features during unstart. High frequency pressure measurements are used to provide information on pressure fluctuation at the scramjet wall. In both of the mass and heat release driven unstart cases, it is observed that there are similar flow transient and quasi-steady behaviors of unstart shockwave system during the unstart processes. Combustion driven unstart induces severe oscillatory flow motions of the jet and the unstart shock at the lip of the scramjet inlet after the completion of the unstart process, while the unstarted flow induced by solely mass addition remains relatively steady. The discrepancies between the processes of mass and heat release driven unstart are explained by flow choking mechanism.

  17. Exact solutions for models of evolving networks with addition and deletion of nodes.

    PubMed

    Moore, Cristopher; Ghoshal, Gourab; Newman, M E J

    2006-09-01

    There has been considerable recent interest in the properties of networks, such as citation networks and the worldwide web, that grow by the addition of vertices, and a number of simple solvable models of network growth have been studied. In the real world, however, many networks, including the web, not only add vertices but also lose them. Here we formulate models of the time evolution of such networks and give exact solutions for a number of cases of particular interest. For the case of net growth and so-called preferential attachment--in which newly appearing vertices attach to previously existing ones in proportion to vertex degree--we show that the resulting networks have power-law degree distributions, but with an exponent that diverges as the growth rate vanishes. We conjecture that the low exponent values observed in real-world networks are thus the result of vigorous growth in which the rate of addition of vertices far exceeds the rate of removal. Were growth to slow in the future--for instance, in a more mature future version of the web--we would expect to see exponents increase, potentially without bound.

  18. Linguini Models of Molecular Genetic Mapping and Fingerprinting.

    ERIC Educational Resources Information Center

    Thompson, James N., Jr.; Gray, Stanton B.; Hellack, Jenna J.

    1997-01-01

    Presents an exercise using linguini noodles to demonstrate an aspect of DNA fingerprinting. DNA maps that show genetic differences can be produced by digesting a certain piece of DNA with two or more restriction enzymes both individually and in combination. By rearranging and matching linguini fragments, students can recreate the original pattern…

  19. A realistic model under which the genetic code is optimal.

    PubMed

    Buhrman, Harry; van der Gulik, Peter T S; Klau, Gunnar W; Schaffner, Christian; Speijer, Dave; Stougie, Leen

    2013-10-01

    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 comparing this value with a distribution of values belonging to codes generated by random permutations of amino acid assignments, the level of error robustness of a genetic code can be quantified. We present a calculation in which the standard genetic code is shown to be optimal. We obtain this result by (1) using recently updated values of polar requirement as input; (2) fixing seven assignments (Ile, Trp, His, Phe, Tyr, Arg, and Leu) based on aptamer considerations; and (3) using known biosynthetic relations of the 20 amino acids. This last point is reflected in an approach of subdivision (restricting the random reallocation of assignments to amino acid subgroups, the set of 20 being divided in four such subgroups). The three approaches to explain robustness of the code (specific selection for robustness, amino acid-RNA interactions leading to assignments, or a slow growth process of assignment patterns) are reexamined in light of our findings. We offer a comprehensive hypothesis, stressing the importance of biosynthetic relations, with the code evolving from an early stage with just glycine and alanine, via intermediate stages, towards 64 codons carrying todays meaning.

  20. The case for developing a lacewing genetic model organism

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lacewings (Chrysopidae: Neuroptera) are a family of insect predators, also called aphidlions because of their voracious feeding on aphids. While lacewings have been popular with growers, gardeners, and biological control scientists, they have had little visibility in the world of genetics. Generalis...

  1. Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

    PubMed

    Ngwira, Alfred; Stanley, Christopher C

    2015-01-01

    Studies on factors of low birth weight in Malawi have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study aimed at investigating risk factors of low birth weight in Malawi by assuming a flexible approach for continuous covariates and geographical random effect. A Bayesian geo-additive model for birth weight in kilograms and size of the child at birth (less than average or average and higher) with district as a spatial effect using the 2010 Malawi demographic and health survey data was adopted. A Gaussian model for birth weight in kilograms and a binary logistic model for the binary outcome (size of child at birth) were fitted. Continuous covariates were modelled by the penalized (p) splines and spatial effects were smoothed by the two dimensional p-spline. The study found that child birth order, mother weight and height are significant predictors of birth weight. Secondary education for mother, birth order categories 2-3 and 4-5, wealth index of richer family and mother height were significant predictors of child size at birth. The area associated with low birth weight was Chitipa and areas with increased risk to less than average size at birth were Chitipa and Mchinji. The study found support for the flexible modelling of some covariates that clearly have nonlinear influences. Nevertheless there is no strong support for inclusion of geographical spatial analysis. The spatial patterns though point to the influence of omitted variables with some spatial structure or possibly epidemiological processes that account for this spatial structure and the maps generated could be used for targeting development efforts at a glance.

  2. Modeling protein density of states: additive hydrophobic effects are insufficient for calorimetric two-state cooperativity.

    PubMed

    Chan, H S

    2000-09-01

    A well-established experimental criterion for two-state thermodynamic cooperativity in protein folding is that the van't Hoff enthalpy DeltaH(vH) around the transition midpoint is equal, or very nearly so, to the calorimetric enthalpy DeltaH(cal) of the entire transition. This condition is satisfied by many small proteins. We use simple lattice models to provide a statistical mechanical framework to elucidate how this calorimetric two-state picture may be reconciled with the hierarchical multistate scenario emerging from recent hydrogen exchange experiments. We investigate the feasibility of using inverse Laplace transforms to recover the underlying density of states (i.e., enthalpy distribution) from calorimetric data. We find that the constraint imposed by DeltaH(vH)/DeltaH(cal) approximately 1 on densities of states of proteins is often more stringent than other "two-state" criteria proposed in recent theoretical studies. In conjunction with reasonable assumptions, the calorimetric two-state condition implies a narrow distribution of denatured-state enthalpies relative to the overall enthalpy difference between the native and the denatured conformations. This requirement does not always correlate with simple definitions of "sharpness" of a transition and has important ramifications for theoretical modeling. We find that protein models that assume capillarity cooperativity can exhibit overall calorimetric two-state-like behaviors. However, common heteropolymer models based on additive hydrophobic-like interactions, including highly specific two-dimensional Gō models, fail to produce proteinlike DeltaH(vH)/DeltaH(cal) approximately 1. A simple model is constructed to illustrate a proposed scenario in which physically plausible local and nonlocal cooperative terms, which mimic helical cooperativity and environment-dependent hydrogen bonding strength, can lead to thermodynamic behaviors closer to experiment. Our results suggest that proteinlike thermodynamic

  3. Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling

    PubMed Central

    Ngwira, Alfred; Stanley, Christopher C.

    2015-01-01

    Studies on factors of low birth weight in Malawi have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study aimed at investigating risk factors of low birth weight in Malawi by assuming a flexible approach for continuous covariates and geographical random effect. A Bayesian geo-additive model for birth weight in kilograms and size of the child at birth (less than average or average and higher) with district as a spatial effect using the 2010 Malawi demographic and health survey data was adopted. A Gaussian model for birth weight in kilograms and a binary logistic model for the binary outcome (size of child at birth) were fitted. Continuous covariates were modelled by the penalized (p) splines and spatial effects were smoothed by the two dimensional p-spline. The study found that child birth order, mother weight and height are significant predictors of birth weight. Secondary education for mother, birth order categories 2-3 and 4-5, wealth index of richer family and mother height were significant predictors of child size at birth. The area associated with low birth weight was Chitipa and areas with increased risk to less than average size at birth were Chitipa and Mchinji. The study found support for the flexible modelling of some covariates that clearly have nonlinear influences. Nevertheless there is no strong support for inclusion of geographical spatial analysis. The spatial patterns though point to the influence of omitted variables with some spatial structure or possibly epidemiological processes that account for this spatial structure and the maps generated could be used for targeting development efforts at a glance. PMID:26114866

  4. A Tailored Approach to Family-Centered Genetic Counseling for Cystic Fibrosis Newborn Screening: The Wisconsin Model

    PubMed Central

    Tluczek, Audrey; Zaleski, Christina; Stachiw-Hietpas, Dania; Modaff, Peggy; Adamski, Craig R.; Nelson, Megan R.; Reiser, Catherine A.; Ghate, Sumedha; Josephson, Kevin D.

    2010-01-01

    Objective Develop a tailored family-centered approach to genetic counseling following abnormal newborn screening (NBS) for cystic fibrosis (CF). Method A genetic counseling consortium reviewed research literature, selected theoretical frameworks, and incorporated counseling psychology micro skills. Results This innovative intervention integrated theories and empirically validated techniques. Pilot testing and parent feedback confirmed satisfaction with and feasibility of the approach designed to (a) minimize parents’ distress, (b) facilitate parents’ understanding, (c) increase parents’ capacities to use genetic information, and (d) enhance parents’ experiences with genetic counseling. Counselors engage in a highly interactive process of evaluating parents’ needs and tailoring assessments and interventions that include a therapeutic environment, the family’s emotional needs, parents’ informational needs, and a follow-up plan. Conclusion This promising new model is the first to establish a theory-driven, evidence-based standard for genetic counseling in the context of NBS for CF. Additional research will evaluate the model’s efficacy in clinical practice. PMID:20936425

  5. Genetics and the evolution of primate enamel thickness: a baboon model.

    PubMed

    Hlusko, Leslea J; Suwa, Gen; Kono, Reiko T; Mahaney, Michael C

    2004-07-01

    The thickness of mammalian tooth enamel plays a prominent role in paleontology because it correlates with diet, and thicker enamel protects against tooth breakage and wear. Hominid evolutionary studies have stressed the importance of this character for over 30 years, from the identification of "Ramapithecus" as an early Miocene hominid, to the recent discovery that the earliest hominids display molar enamel intermediate in thickness between extant chimpanzees and Australopithecus. Enamel thickness remains largely unexplored for nonhominoid primate fossils, though there is significant variation across modern species. Despite the importance of enamel thickness variation to primate evolution, the mechanisms underlying variation in this trait have not yet been elucidated. We report here on the first quantitative genetic analysis of primate enamel thickness, an analysis based on 506 pedigreed baboons from a captive breeding colony. Computed tomography analysis of 44 Papio mandibular molars shows a zone of sufficiently uniform enamel thickness on the lateral surface of the protoconid. With this knowledge, we developed a caliper metric measurement protocol for use on baboon molars worn to within this zone, enabling the collection of a data set large enough for genetic analyses. Quantitative genetic analyses show that a significant portion of the phenotypic variance in enamel thickness is due to the additive effects of genes and is independent of sex and tooth size. Our models predict that enamel thickness could rapidly track dietary adaptive shifts through geological time, thus increasing the potential for homoplasy in this character. These results have implications for analyses of hominoid enamel thickness variation, and provide a foundation from which to explore the evolution of this phenotype in the papionin fossil record.

  6. A genetic rat model of cholinergic hypersensitivity: implications for chemical intolerance, chronic fatigue, and asthma.

    PubMed

    Overstreet, D H; Djuric, V

    2001-03-01

    The fact that only some individuals exposed to environmental chemicals develop chemical intolerance raises the possibility that genetic factors could be contributing factors. The present communication summarizes evidence from a genetic animal model of cholinergic supersensitivity that suggests that an abnormal cholinergic system could be one predisposing genetic factor. The Flinders Sensitive Line (FSL) rats were established by selective breeding for increased responses to an organophosphate. It was subsequently found that these FSL rats were also more sensitive to direct-acting muscarinic agonists and had elevated muscarinic receptors compared to the selectively bred parallel group, the Flinders Resistant Line (FRL) rats, or randomly bred control rats. Increased sensitivity to cholinergic agents has also been observed in several human populations, including individuals suffering from chemical intolerance. Indeed, the FSL rats exhibit certain behavioral characteristics such as abnormal sleep, activity, and appetite that are similar to those reported in these human populations. In addition, the FSL rats have been reported to exhibit increased sensitivity to a variety of other chemical agents. Peripheral tissues, such as intestinal and airway smooth muscle, appear to be more sensitive to both cholinergic agonists and an antigen, ovalbumin. Hypothermia, a centrally mediated response, is more pronounced in the FSL rats after nicotine and alcohol, as well as agents that are selective for the dopaminergic and serotonergic systems. In some cases, the increased sensitivity has been detected in the absence of any changes in the receptors with which the drugs interact (dopamine receptors), while receptor changes have been seen in other cases (nicotine receptors). Therefore, there may be multiple mechanisms underlying the multiple chemical sensitivity-chemical intolerance of the FSL rats. An elucidation of these mechanisms may provide useful clues to those involved in

  7. USE OF MODELING APPROACHES TO UNDERSTAND POTENTIAL IMPACTS OF GENETICALLY MODIFIED PLANTS ON PLANT COMMUNITIES

    EPA Science Inventory

    Model development is of interest to ecologists, regulators and developers, since it may assist theoretical understanding, decision making in experimental design, product development and risk assessment. In order to predict the potential impacts of genetically modified (GM) plants...

  8. Generalized Additive Models Used to Predict Species Abundance in the Gulf of Mexico: An Ecosystem Modeling Tool

    PubMed Central

    Drexler, Michael; Ainsworth, Cameron H.

    2013-01-01

    Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum) and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist. PMID:23691223

  9. The biobehavioral family model: testing social support as an additional exogenous variable.

    PubMed

    Woods, Sarah B; Priest, Jacob B; Roush, Tara

    2014-12-01

    This study tests the inclusion of social support as a distinct exogenous variable in the Biobehavioral Family Model (BBFM). The BBFM is a biopsychosocial approach to health that proposes that biobehavioral reactivity (anxiety and depression) mediates the relationship between family emotional climate and disease activity. Data for this study included married, English-speaking adult participants (n = 1,321; 55% female; M age = 45.2 years) from the National Comorbidity Survey Replication, a nationally representative epidemiological study of the frequency of mental disorders in the United States. Participants reported their demographics, marital functioning, social support from friends and relatives, anxiety and depression (biobehavioral reactivity), number of chronic health conditions, and number of prescription medications. Confirmatory factor analyses supported the items used in the measures of negative marital interactions, social support, and biobehavioral reactivity, as well as the use of negative marital interactions, friends' social support, and relatives' social support as distinct factors in the model. Structural equation modeling indicated a good fit of the data to the hypothesized model (χ(2)  = 846.04, p = .000, SRMR = .039, CFI = .924, TLI = .914, RMSEA = .043). Negative marital interactions predicted biobehavioral reactivity (β = .38, p < .001), as did relatives' social support, inversely (β = -.16, p < .001). Biobehavioral reactivity predicted disease activity (β = .40, p < .001) and was demonstrated to be a significant mediator through tests of indirect effects. Findings are consistent with previous tests of the BBFM with adult samples, and suggest the important addition of family social support as a predicting factor in the model. PMID:24981970

  10. Modeling particulate matter concentrations measured through mobile monitoring in a deletion/substitution/addition approach

    NASA Astrophysics Data System (ADS)

    Su, Jason G.; Hopke, Philip K.; Tian, Yilin; Baldwin, Nichole; Thurston, Sally W.; Evans, Kristin; Rich, David Q.

    2015-12-01

    Land use regression modeling (LUR) through local scale circular modeling domains has been used to predict traffic-related air pollution such as nitrogen oxides (NOX). LUR modeling for fine particulate matters (PM), which generally have smaller spatial gradients than NOX, has been typically applied for studies involving multiple study regions. To increase the spatial coverage for fine PM and key constituent concentrations, we designed a mobile monitoring network in Monroe County, New York to measure pollutant concentrations of black carbon (BC, wavelength at 880 nm), ultraviolet black carbon (UVBC, wavelength at 3700 nm) and Delta-C (the difference between the UVBC and BC concentrations) using the Clarkson University Mobile Air Pollution Monitoring Laboratory (MAPL). A Deletion/Substitution/Addition (D/S/A) algorithm was conducted, which used circular buffers as a basis for statistics. The algorithm maximizes the prediction accuracy for locations without measurements using the V-fold cross-validation technique, and it reduces overfitting compared to other approaches. We found that the D/S/A LUR modeling approach could achieve good results, with prediction powers of 60%, 63%, and 61%, respectively, for BC, UVBC, and Delta-C. The advantage of mobile monitoring is that it can monitor pollutant concentrations at hundreds of spatial points in a region, rather than the typical less than 100 points from a fixed site saturation monitoring network. This research indicates that a mobile saturation sampling network, when combined with proper modeling techniques, can uncover small area variations (e.g., 10 m) in particulate matter concentrations.

  11. A habitat suitability model for Chinese sturgeon determined using the generalized additive method

    NASA Astrophysics Data System (ADS)

    Yi, Yujun; Sun, Jie; Zhang, Shanghong

    2016-03-01

    The Chinese sturgeon is a type of large anadromous fish that migrates between the ocean and rivers. Because of the construction of dams, this sturgeon's migration path has been cut off, and this species currently is on the verge of extinction. Simulating suitable environmental conditions for spawning followed by repairing or rebuilding its spawning grounds are effective ways to protect this species. Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat. In this study, a two-dimensional hydraulic simulation is used to inform a habitat suitability model based on the generalized additive method (GAM). The GAM is based on real data. The values of water depth and velocity are calculated first via the hydrodynamic model and later applied in the GAM. The final habitat suitability model is validated using the catch per unit effort (CPUEd) data of 1999 and 2003. The model results show that a velocity of 1.06-1.56 m/s and a depth of 13.33-20.33 m are highly suitable ranges for the Chinese sturgeon to spawn. The hydraulic habitat suitability indexes (HHSI) for seven discharges (4000; 9000; 12,000; 16,000; 20,000; 30,000; and 40,000 m3/s) are calculated to evaluate integrated habitat suitability. The results show that the integrated habitat suitability reaches its highest value at a discharge of 16,000 m3/s. This study is the first to apply a GAM to evaluate the suitability of spawning grounds for the Chinese sturgeon. The study provides a reference for the identification of potential spawning grounds in the entire basin.

  12. The biobehavioral family model: testing social support as an additional exogenous variable.

    PubMed

    Woods, Sarah B; Priest, Jacob B; Roush, Tara

    2014-12-01

    This study tests the inclusion of social support as a distinct exogenous variable in the Biobehavioral Family Model (BBFM). The BBFM is a biopsychosocial approach to health that proposes that biobehavioral reactivity (anxiety and depression) mediates the relationship between family emotional climate and disease activity. Data for this study included married, English-speaking adult participants (n = 1,321; 55% female; M age = 45.2 years) from the National Comorbidity Survey Replication, a nationally representative epidemiological study of the frequency of mental disorders in the United States. Participants reported their demographics, marital functioning, social support from friends and relatives, anxiety and depression (biobehavioral reactivity), number of chronic health conditions, and number of prescription medications. Confirmatory factor analyses supported the items used in the measures of negative marital interactions, social support, and biobehavioral reactivity, as well as the use of negative marital interactions, friends' social support, and relatives' social support as distinct factors in the model. Structural equation modeling indicated a good fit of the data to the hypothesized model (χ(2)  = 846.04, p = .000, SRMR = .039, CFI = .924, TLI = .914, RMSEA = .043). Negative marital interactions predicted biobehavioral reactivity (β = .38, p < .001), as did relatives' social support, inversely (β = -.16, p < .001). Biobehavioral reactivity predicted disease activity (β = .40, p < .001) and was demonstrated to be a significant mediator through tests of indirect effects. Findings are consistent with previous tests of the BBFM with adult samples, and suggest the important addition of family social support as a predicting factor in the model.

  13. Drosophila melanogaster as a genetic model system to study neurotransmitter transporters

    PubMed Central

    Martin, Ciara A.; Krantz, David E.

    2014-01-01

    The model genetic organism Drosophila melanogaster, commonly known as the fruit fly, uses many of the same neurotransmitters as mammals and very similar mechanisms of neurotransmitter storage, release and recycling. This system offers a variety of powerful molecular-genetic methods for the study of transporters, many of which would be difficult in mammalian models. We review here progress made using Drosophila to understand the function and regulation of neurotransmitter transporters and discuss future directions for its use. PMID:24704795

  14. Drosophila melanogaster as a genetic model system to study neurotransmitter transporters.

    PubMed

    Martin, Ciara A; Krantz, David E

    2014-07-01

    The model genetic organism Drosophila melanogaster, commonly known as the fruit fly, uses many of the same neurotransmitters as mammals and very similar mechanisms of neurotransmitter storage, release and recycling. This system offers a variety of powerful molecular-genetic methods for the study of transporters, many of which would be difficult in mammalian models. We review here progress made using Drosophila to understand the function and regulation of neurotransmitter transporters and discuss future directions for its use.

  15. Studying genetic regulatory networks at the molecular level: delayed reaction stochastic models.

    PubMed

    Zhu, Rui; Ribeiro, Andre S; Salahub, Dennis; Kauffman, Stuart A

    2007-06-21

    Current advances in molecular biology enable us to access the rapidly increasing body of genetic information. It is still challenging to model gene systems at the molecular level. Here, we propose two types of reaction kinetic models for constructing genetic networks. Time delays involved in transcription and translation are explicitly considered to explore the effects of delays, which may be significant in genetic networks featured with feedback loops. One type of model is based on delayed effective reactions, each reaction modeling a biochemical process like transcription without involving intermediate reactions. The other is based on delayed virtual reactions, each reaction being converted from a mathematical function to model a biochemical function like gene inhibition. The latter stochastic models are derived from the corresponding mean-field models. The former ones are composed of single gene expression modules. We thus design a model of gene expression. This model is verified by our simulations using a delayed stochastic simulation algorithm, which accurately reproduces the stochastic kinetics in a recent experimental study. Various simplified versions of the model are given and evaluated. We then use the two methods to study the genetic toggle switch and the repressilator. We define the "on" and "off" states of genes and extract a binary code from the stochastic time series. The binary code can be described by the corresponding Boolean network models in certain conditions. We discuss these conditions, suggesting a method to connect Boolean models, mean-field models, and stochastic chemical models. PMID:17350653

  16. Impact of an additional chronic BDNF reduction on learning performance in an Alzheimer mouse model.

    PubMed

    Psotta, Laura; Rockahr, Carolin; Gruss, Michael; Kirches, Elmar; Braun, Katharina; Lessmann, Volkmar; Bock, Jörg; Endres, Thomas

    2015-01-01

    There is increasing evidence that brain-derived neurotrophic factor (BDNF) plays a crucial role in Alzheimer's disease (AD) pathology. A number of studies demonstrated that AD patients exhibit reduced BDNF levels in the brain and the blood serum, and in addition, several animal-based studies indicated a potential protective effect of BDNF against Aβ-induced neurotoxicity. In order to further investigate the role of BDNF in the etiology of AD, we created a novel mouse model by crossing a well-established AD mouse model (APP/PS1) with a mouse exhibiting a chronic BDNF deficiency (BDNF(+/-)). This new triple transgenic mouse model enabled us to further analyze the role of BDNF in AD in vivo. We reasoned that in case BDNF has a protective effect against AD pathology, an AD-like phenotype in our new mouse model should occur earlier and/or in more severity than in the APP/PS1-mice. Indeed, the behavioral analysis revealed that the APP/PS1-BDNF(+/-)-mice show an earlier onset of learning impairments in a two-way active avoidance task in comparison to APP/PS1- and BDNF(+/-)-mice. However in the Morris water maze (MWM) test, we could not observe an overall aggrevated impairment in spatial learning and also short-term memory in an object recognition task remained intact in all tested mouse lines. In addition to the behavioral experiments, we analyzed the amyloid plaque pathology in the APP/PS1 and APP/PS1-BDNF(+/-)-mice and observed a comparable plaque density in the two genotypes. Moreover, our results revealed a higher plaque density in prefrontal cortical compared to hippocampal brain regions. Our data reveal that higher cognitive tasks requiring the recruitment of cortical networks appear to be more severely affected in our new mouse model than learning tasks requiring mainly sub-cortical networks. Furthermore, our observations of an accelerated impairment in active avoidance learning in APP/PS1-BDNF(+/-)-mice further supports the hypothesis that BDNF deficiency

  17. Nonlinear feedback in a six-dimensional Lorenz model: impact of an additional heating term

    NASA Astrophysics Data System (ADS)

    Shen, B.-W.

    2015-12-01

    In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the streamfunction is referred to as a secondary streamfunction mode, while the two additional modes, which appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): "If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

  18. Nonlinear feedback in a six-dimensional Lorenz Model: impact of an additional heating term

    NASA Astrophysics Data System (ADS)

    Shen, B.-W.

    2015-03-01

    In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the steamfunction is referred to as a secondary streamfunction mode, while the two additional modes, that appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

  19. Genetic mouse models to study blood–brain barrier development and function

    PubMed Central

    2013-01-01

    The blood–brain barrier (BBB) is a complex physiological structure formed by the blood vessels of the central nervous system (CNS) that tightly regulates the movement of substances between the blood and the neural tissue. Recently, the generation and analysis of different genetic mouse models has allowed for greater understanding of BBB development, how the barrier is regulated during health, and its response to disease. Here we discuss: 1) Genetic mouse models that have been used to study the BBB, 2) Available mouse genetic tools that can aid in the study of the BBB, and 3) Potential tools that if generated could greatly aid in our understanding of the BBB. PMID:23305182

  20. Estimation and Inference in Generalized Additive Coefficient Models for Nonlinear Interactions with High-Dimensional Covariates

    PubMed Central

    Shujie, MA; Carroll, Raymond J.; Liang, Hua; Xu, Shizhong

    2015-01-01

    In the low-dimensional case, the generalized additive coefficient model (GACM) proposed by Xue and Yang [Statist. Sinica 16 (2006) 1423–1446] has been demonstrated to be a powerful tool for studying nonlinear interaction effects of variables. In this paper, we propose estimation and inference procedures for the GACM when the dimension of the variables is high. Specifically, we propose a groupwise penalization based procedure to distinguish significant covariates for the “large p small n” setting. The procedure is shown to be consistent for model structure identification. Further, we construct simultaneous confidence bands for the coefficient functions in the selected model based on a refined two-step spline estimator. We also discuss how to choose the tuning parameters. To estimate the standard deviation of the functional estimator, we adopt the smoothed bootstrap method. We conduct simulation experiments to evaluate the numerical performance of the proposed methods and analyze an obesity data set from a genome-wide association study as an illustration. PMID:26412908

  1. Spectral models of additive and modulation noise in speech and phonatory excitation signals

    NASA Astrophysics Data System (ADS)

    Schoentgen, Jean

    2003-01-01

    The article presents spectral models of additive and modulation noise in speech. The purpose is to learn about the causes of noise in the spectra of normal and disordered voices and to gauge whether the spectral properties of the perturbations of the phonatory excitation signal can be inferred from the spectral properties of the speech signal. The approach to modeling consists of deducing the Fourier series of the perturbed speech, assuming that the Fourier series of the noise and of the clean monocycle-periodic excitation are known. The models explain published data, take into account the effects of supraglottal tremor, demonstrate the modulation distortion owing to vocal tract filtering, establish conditions under which noise cues of different speech signals may be compared, and predict the impossibility of inferring the spectral properties of the frequency modulating noise from the spectral properties of the frequency modulation noise (e.g., phonatory jitter and frequency tremor). The general conclusion is that only phonatory frequency modulation noise is spectrally relevant. Other types of noise in speech are either epiphenomenal, or their spectral effects are masked by the spectral effects of frequency modulation noise.

  2. Modelling and genetic algorithm based optimisation of inverse supply chain

    NASA Astrophysics Data System (ADS)

    Bányai, T.

    2009-04-01

    (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a

  3. Genetics of phototaxis in a model eukaryote, Dictyostelium discoideum.

    PubMed

    Fisher, P R

    1997-05-01

    The life cycle of Dictyostelium discoideum offers a unique opportunity to study signal transduction in eukaryotic cells at both the unicellular and multicellular levels of organization. Adding to the already extensive knowledge of the unicellular stages, classical and molecular genetics have begun to unravel transduction of signals controlling morphogenesis and behaviour (phototaxis and thermotaxis) in the multicellular 'slug' stage of the life cycle. Distributed over all seven genetic linkage groups are probably about 20, but possibly as many as 55, genes of importance for slug behaviour. The encoded proteins appear from pharmacological studies and mutant phenotypes to govern transduction pathways involving the intracellular second messengers cyclic AMP, cyclic GMP, IP3 and Ca2+. Pathways from the photo- and thermoreceptors converge first with each other and thence, at the level of the second messengers, with those from extracellular tip activation (cyclic AMP) and inhibition (Slug Turning Factor and/or ammonia and/or adenosine) signals that control slug movement and morphogenesis.

  4. Analysis of Advantages, Limitations, and Barriers of Genetic Counseling Service Delivery Models.

    PubMed

    Cohen, Stephanie A; Huziak, Rachelle C; Gustafson, Shanna; Grubs, Robin E

    2016-10-01

    Previous studies on genetic counseling service delivery models (SDMs) have shown that genetic counselors (GCs) are incorporating alternate models to address growing service demand and improve access to genetic services. This study sought to identify barriers, limitations and advantages to previously identified genetic counseling SDMs. A qualitative research design was employed, in which 20 practicing GCs who utilize a variety of SDMs were interviewed using an email interview format. Interview transcripts were analyzed using a thematic analysis to identify themes related to implementation and utilization of SDMs. Factors that led GCs to implement SDMs other than in-person genetic counseling included: 1) travel distance, 2) wait time and 3) convenience. Logistical issues such as billing and reimbursement, equipment set up, making arrangements for genetic testing and the inability to see the patient are major limitations to alternative genetic counseling SDMs in clinical practice. However, GCs interviewed stated that the convenience to the patient and genetic counselor of alternative SDMs outweighed these limitations. More research is needed to assess the outcomes of SDMs in practice to demonstrate an impact on the identified barriers of travel distance, wait time and convenience.

  5. Additive Factors Do Not Imply Discrete Processing Stages: A Worked Example Using Models of the Stroop Task

    PubMed Central

    Stafford, Tom; Gurney, Kevin N.

    2011-01-01

    Previously, it has been shown experimentally that the psychophysical law known as Piéron’s Law holds for color intensity and that the size of the effect is additive with that of Stroop condition (Stafford et al., 2011). According to the additive factors method (Donders, 1868–1869/1969; Sternberg, 1998), additivity is assumed to indicate independent and discrete processing stages. We present computational modeling work, using an existing Parallel Distributed Processing model of the Stroop task (Cohen et al., 1990) and a standard model of decision making (Ratcliff, 1978). This demonstrates that additive factors can be successfully accounted for by existing single stage models of the Stroop effect. Consequently, it is not valid to infer either discrete stages or separate loci of effects from additive factors. Further, our modeling work suggests that information binding may be a more important architectural property for producing additive factors than discrete stages. PMID:22102842

  6. Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation

    PubMed Central

    Soomro, Shafiullah; Kim, Jeong Heon; Soomro, Toufique Ahmed

    2016-01-01

    This paper introduces an improved region based active contour method with a level set formulation. The proposed energy functional integrates both local and global intensity fitting terms in an additive formulation. Local intensity fitting term influences local force to pull the contour and confine it to object boundaries. In turn, the global intensity fitting term drives the movement of contour at a distance from the object boundaries. The global intensity term is based on the global division algorithm, which can better capture intensity information of an image than Chan-Vese (CV) model. Both local and global terms are mutually assimilated to construct an energy function based on a level set formulation to segment images with intensity inhomogeneity. Experimental results show that the proposed method performs better both qualitatively and quantitatively compared to other state-of-the-art-methods. PMID:27800011

  7. Use of generalised additive models to categorise continuous variables in clinical prediction

    PubMed Central

    2013-01-01

    Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically

  8. Generalized Concentration Addition Modeling Predicts Mixture Effects of Environmental PPARγ Agonists.

    PubMed

    Watt, James; Webster, Thomas F; Schlezinger, Jennifer J

    2016-09-01

    The vast array of potential environmental toxicant combinations necessitates the development of efficient strategies for predicting toxic effects of mixtures. Current practices emphasize the use of concentration addition to predict joint effects of endocrine disrupting chemicals in coexposures. Generalized concentration addition (GCA) is one such method for predicting joint effects of coexposures to chemicals and has the advantage of allowing for mixture components to have differences in efficacy (ie, dose-response curve maxima). Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that plays a central role in regulating lipid homeostasis, insulin sensitivity, and bone quality and is the target of an increasing number of environmental toxicants. Here, we tested the applicability of GCA in predicting mixture effects of therapeutic (rosiglitazone and nonthiazolidinedione partial agonist) and environmental PPARγ ligands (phthalate compounds identified using EPA's ToxCast database). Transcriptional activation of human PPARγ1 by individual compounds and mixtures was assessed using a peroxisome proliferator response element-driven luciferase reporter. Using individual dose-response parameters and GCA, we generated predictions of PPARγ activation by the mixtures, and we compared these predictions with the empirical data. At high concentrations, GCA provided a better estimation of the experimental response compared with 3 alternative models: toxic equivalency factor, effect summation and independent action. These alternatives provided reasonable fits to the data at low concentrations in this system. These experiments support the implementation of GCA in mixtures analysis with endocrine disrupting compounds and establish PPARγ as an important target for further studies of chemical mixtures.

  9. Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation

    PubMed Central

    Porto, Arthur; Sebastião, Harley; Pavan, Silvia Eliza; VandeBerg, John L.; Marroig, Gabriel; Cheverud, James M.

    2015-01-01

    We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyze the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation. PMID:25818173

  10. Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation.

    PubMed

    Porto, A; Sebastião, H; Pavan, S E; VandeBerg, J L; Marroig, G; Cheverud, J M

    2015-04-01

    We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyse the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation.

  11. Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

    USGS Publications Warehouse

    Louis, S.J.; Raines, G.L.

    2003-01-01

    We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

  12. A generalization of substitution evolution models of nucleotides to genetic motifs.

    PubMed

    Benard, Emmanuel; Michel, Christian J

    2011-11-01

    We generalize here the classical stochastic substitution models of nucleotides to genetic motifs of any size. This generalized model gives the analytical occurrence probabilities of genetic motifs as a function of a substitution matrix containing up to three formal parameters (substitution rates) per motif site and of an initial occurrence probability vector of genetic motifs. The evolution direction can be direct (past-present) or inverse (present-past). This extension has been made due to the identification of a Kronecker relation between the nucleotide substitution matrices and the motif substitution matrices. The evolution models for motifs of size 4 (tetranucleotides) and 5 (pentanucleotides) are now included in the SEGM (Stochastic Evolution of Genetic Motifs) web server.

  13. Modeling external carbon addition in biological nutrient removal processes with an extension of the international water association activated sludge model.

    PubMed

    Swinarski, M; Makinia, J; Stensel, H D; Czerwionka, K; Drewnowski, J

    2012-08-01

    The aim of this study was to expand the International Water Association Activated Sludge Model No. 2d (ASM2d) to account for a newly defined readily biodegradable substrate that can be consumed by polyphosphate-accumulating organisms (PAOs) under anoxic and aerobic conditions, but not under anaerobic conditions. The model change was to add a new substrate component and process terms for its use by PAOs and other heterotrophic bacteria under anoxic and aerobic conditions. The Gdansk (Poland) wastewater treatment plant (WWTP), which has a modified University of Cape Town (MUCT) process for nutrient removal, provided field data and mixed liquor for batch tests for model evaluation. The original ASM2d was first calibrated under dynamic conditions with the results of batch tests with settled wastewater and mixed liquor, in which nitrate-uptake rates, phosphorus-release rates, and anoxic phosphorus uptake rates were followed. Model validation was conducted with data from a 96-hour measurement campaign in the full-scale WWTP. The results of similar batch tests with ethanol and fusel oil as the external carbon sources were used to adjust kinetic and stoichiometric coefficients in the expanded ASM2d. Both models were compared based on their predictions of the effect of adding supplemental carbon to the anoxic zone of an MUCT process. In comparison with the ASM2d, the new model better predicted the anoxic behaviors of carbonaceous oxygen demand, nitrate-nitrogen (NO3-N), and phosphorous (PO4-P) in batch experiments with ethanol and fusel oil. However, when simulating ethanol addition to the anoxic zone of a full-scale biological nutrient removal facility, both models predicted similar effluent NO3-N concentrations (6.6 to 6.9 g N/m3). For the particular application, effective enhanced biological phosphorus removal was predicted by both models with external carbon addition but, for the new model, the effluent PO4-P concentration was approximately one-half of that found from

  14. Cycles of Exploration, Reflection, and Consolidation in Model-Based Learning of Genetics

    ERIC Educational Resources Information Center

    Kim, Beaumie; Pathak, Suneeta A.; Jacobson, Michael J.; Zhang, Baohui; Gobert, Janice D.

    2015-01-01

    Model-based reasoning has been introduced as an authentic way of learning science, and many researchers have developed technological tools for learning with models. This paper describes how a model-based tool, "BioLogica"™, was used to facilitate genetics learning in secondary 3-level biology in Singapore. The research team co-designed…

  15. Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

    NASA Astrophysics Data System (ADS)

    Ushijima, Timothy T.; Yeh, William W.-G.

    2013-10-01

    An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

  16. Ocean circulation model predicts high genetic structure observed in a long-lived pelagic developer.

    PubMed

    Sunday, J M; Popovic, I; Palen, W J; Foreman, M G G; Hart, M W

    2014-10-01

    Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes and may not capture present-day connectivity between populations. Here, we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns, which tend to retain passive larvae within 20-50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks.

  17. Ocean circulation model predicts high genetic structure observed in a long-lived pelagic developer.

    PubMed

    Sunday, J M; Popovic, I; Palen, W J; Foreman, M G G; Hart, M W

    2014-10-01

    Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes and may not capture present-day connectivity between populations. Here, we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns, which tend to retain passive larvae within 20-50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks. PMID:25231198

  18. Adaptive fixation in two-locus models of stabilizing selection and genetic drift.

    PubMed

    Wollstein, Andreas; Stephan, Wolfgang

    2014-10-01

    The relationship between quantitative genetics and population genetics has been studied for nearly a century, almost since the existence of these two disciplines. Here we ask to what extent quantitative genetic models in which selection is assumed to operate on a polygenic trait predict adaptive fixations that may lead to footprints in the genome (selective sweeps). We study two-locus models of stabilizing selection (with and without genetic drift) by simulations and analytically. For symmetric viability selection we find that ∼16% of the trajectories may lead to fixation if the initial allele frequencies are sampled from the neutral site-frequency spectrum and the effect sizes are uniformly distributed. However, if the population is preadapted when it undergoes an environmental change (i.e., sits in one of the equilibria of the model), the fixation probability decreases dramatically. In other two-locus models with general viabilities or an optimum shift, the proportion of adaptive fixations may increase to >24%. Similarly, genetic drift leads to a higher probability of fixation. The predictions of alternative quantitative genetics models, initial conditions, and effect-size distributions are also discussed.

  19. Transposon mouse models to elucidate the genetic mechanisms of hepatitis B viral induced hepatocellular carcinoma

    PubMed Central

    Chiu, Amy P; Tschida, Barbara R; Lo, Lilian H; Moriarity, Branden S; Rowlands, Dewi K; Largaespada, David A; Keng, Vincent W

    2015-01-01

    The major type of human liver cancer is hepatocellular carcinoma (HCC), and there are currently many risk factors that contribute to this deadly disease. The majority of HCC occurrences are associated with chronic hepatitis viral infection, and hepatitis B viral (HBV) infection is currently a major health problem in Eastern Asia. Elucidating the genetic mechanisms associated with HBV-induced HCC has been difficult due to the heterogeneity and genetic complexity associated with this disease. A repertoire of animal models has been broadly used to study the pathophysiology and to develop potential treatment regimens for HBV-associated HCC. The use of these animal models has provided valuable genetic information and has been an important contributor to uncovering the factors involved in liver malignant transformation, invasion and metastasis. Recently, transposon-based mouse models are becoming more widely used in liver cancer research to interrogate the genome by forward genetics and also used to validate genes rapidly in a reverse genetic manner. Importantly, these transposon-based rapid reverse genetic mouse models could become crucial in testing potential therapeutic agents before proceeding to clinical trials in human. Therefore, this review will cover the use of transposon-based mouse models to address the problems of liver cancer, especially HBV-associated HCC occurrences in Asia. PMID:26576100

  20. Evaluation of the Performance of Smoothing Functions in Generalized Additive Models for Spatial Variation in Disease

    PubMed Central

    Siangphoe, Umaporn; Wheeler, David C.

    2015-01-01

    Generalized additive models (GAMs) with bivariate smoothing functions have been applied to estimate spatial variation in risk for many types of cancers. Only a handful of studies have evaluated the performance of smoothing functions applied in GAMs with regard to different geographical areas of elevated risk and different risk levels. This study evaluates the ability of different smoothing functions to detect overall spatial variation of risk and elevated risk in diverse geographical areas at various risk levels using a simulation study. We created five scenarios with different true risk area sh