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Sample records for patterns predicts genetic

  1. Genetic prediction of male pattern baldness.

    Directory of Open Access Journals (Sweden)

    Saskia P Hagenaars

    2017-02-01

    Full Text Available Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8. By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82% those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

  2. Genetic prediction of male pattern baldness.

    Science.gov (United States)

    Hagenaars, Saskia P; Hill, W David; Harris, Sarah E; Ritchie, Stuart J; Davies, Gail; Liewald, David C; Gale, Catharine R; Porteous, David J; Deary, Ian J; Marioni, Riccardo E

    2017-02-01

    Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8). By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

  3. Genetic fuzzy system predicting contractile reactivity patterns of small arteries

    DEFF Research Database (Denmark)

    Tang, J; Sheykhzade, Majid; Clausen, B F

    2014-01-01

    strategies. Results show that optimized fuzzy systems (OFSs) predict contractile reactivity of arteries accurately. In addition, OFSs identified significant differences that were undetectable using conventional analysis in the responses of arteries between groups. We concluded that OFSs may be used...

  4. Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

    Science.gov (United States)

    Kashid, Satishkumar S.; Maity, Rajib

    2012-08-01

    SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

  5. Further improvement of genetic and cytogenetic test pattern with increased relevance predicting carcinogenic and pharmacological effects

    Energy Technology Data Exchange (ETDEWEB)

    Siebert, D.

    1982-08-01

    Testing of chemicals for their genetic activity by applying only one method has the disadvantage, that the results are of limited value. However, a combination of several test systems in such a manner that the apparent difference between the results allows additional conclusions about the pharmacokinetic properties of the substances tested, the correlation between molecular mutations and cytogenetic effects and the possible carcinogenic activity. Three nitrofuran derivatives (nitrofurantoin, carofur and FANFT) tested in six different in vitro and in vivo mutagenicity tests partly showed strong genetic activity without metabolic activation and weak cytogenetic effects. However, polycyclic hydrocarbons needed mammalian metabolism to display their mutagenicity: Dimethylbenzoanthracene and benzo(a)pyrene could be activated by liver microsomes and showed also cytogenetic effects, but phenanthrene was only active in the SCE-test. Out of nine heavy metal salts potassium chromate, potassium dichromate, calcium chromate and cis-dichloro diammine-Pt(II) were effective in at least one genetic and one cytogenetic test. The correlation between mutagenic and the known carcinogenic activity of all test substances was good in the case of the hydrocarbons and the nitrofuran derivatives; the heavy metal salts, however, are of low relevance for the carcinogenicity of the metals itself.

  6. Comparative evaluation of genetic toxicity patterns of carcinogens and noncarcinogens: strategies for predictive use of short-term assays

    International Nuclear Information System (INIS)

    Tennant, R.W.; Spalding, J.W.; Stasiewicz, S.; Caspary, W.D.; Mason, J.M.; Resnick, M.A.

    1987-01-01

    The results of a recent comprehensive evaluation of the relationship between four measures of in vitro genetic toxicity and the capacity of the chemicals to induce neoplasia in rodents carry some important implications. The results showed that while the Salmonella mutagenesis assay detected only about half of the carcinogenes as mutagens, the other three in vitro assays (mutagenesis in MOLY cells or induction of aberrations or SCEs in CHO cells) did not complement Salmonella since they failed to effectively discriminate between the carcinogens and noncarcinogens found negative in the Salmonella assay. The specificity of the Salmonella assay for this group of 73 chemicals was relatively high (only 4 of 29 noncarcinogens were positive). Therefore, the authors have begun to evaluate in vivo genetic toxicity assays for their ability to complement Salmonella in the identification of carcinogens

  7. Solution Patterns Predicting Pythagorean Triples

    Science.gov (United States)

    Ezenweani, Ugwunna Louis

    2013-01-01

    Pythagoras Theorem is an old mathematical treatise that has traversed the school curricula from secondary to tertiary levels. The patterns it produced are quite interesting that many researchers have tried to generate a kind of predictive approach to identifying triples. Two attempts, namely Diophantine equation and Brahmagupta trapezium presented…

  8. Genet-specific spawning patterns in Acropora palmata

    Science.gov (United States)

    Miller, M. W.; Williams, D. E.; Fisch, J.

    2016-12-01

    The broadcast spawning elkhorn coral, Acropora palmata, requires outcrossing among different genets for effective fertilization. Hence, a low density of genets in parts of its range emphasizes the need for precise synchrony among neighboring genets as sperm concentration dilutes rapidly in open-ocean conditions. We documented the genet-specific nightly occurrence of spawning of A. palmata over 8 yr in a depauperate population in the Florida Keys to better understand this potential reproductive hurdle. The observed population failed to spawn within the predicted monthly window (nights 2-6 after the full moon in August) in three of the 8 yr of observation; negligible spawning was observed in a fourth year. Moreover, genet-specific patterns are evident in that (1) certain genets have significantly greater odds of spawning overall and (2) certain genets predictably spawn on the earlier and others on the later lunar nights within the predicted window. Given the already low genet density in this population, this pattern implies a substantial degree of wasted reproductive effort and supports the hypothesis that depensatory factors are impairing recovery in this species.

  9. Genetic algorithms in loading pattern optimization

    International Nuclear Information System (INIS)

    Yilmazbayhan, A.; Tombakoglu, M.; Bekar, K. B.; Erdemli, A. Oe

    2001-01-01

    Genetic Algorithm (GA) based systems are used for the loading pattern optimization. The use of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection of initial population size for PWRs are discussed. Antithetic variates are used to generate the initial population. The performance of GA with antithetic variates is compared to traditional GA. The results of multi-cycle optimization are discussed for objective function taking into account cycle burn-up and discharge burn-up

  10. Prediction of male-pattern baldness from genotypes

    NARCIS (Netherlands)

    F. Liu (Fan); M.A. Hamer (Merel); S. Heilmann (S.); C. Herold (Christine); S. Moebus (Susanne); A. Hofman (Albert); A.G. Uitterlinden (André); M.M. Nöthen (Markus); C.M. van Duijn (Cornelia); T.E.C. Nijsten (Tamar); M.H. Kayser (Manfred)

    2016-01-01

    textabstractThe global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide

  11. Assessment of the genetic diversity and pattern of relationship of ...

    African Journals Online (AJOL)

    An understanding of the extent, distribution and patterns of genetic variation is useful for estimation of any possible loss of genetic diversity and assessment of genetic variability and its potential use in breeding programs, including establishment of heterotic groups. This study assessed patterns of genetic diversity and ...

  12. Highlighting nonlinear patterns in population genetics datasets

    KAUST Repository

    Alanis Lobato, Gregorio; Cannistraci, Carlo Vittorio; Eriksson, Anders; Manica, Andrea; Ravasi, Timothy

    2015-01-01

    Detecting structure in population genetics and case-control studies is important, as it exposes phenomena such as ecoclines, admixture and stratification. Principal Component Analysis (PCA) is a linear dimension-reduction technique commonly used for this purpose, but it struggles to reveal complex, nonlinear data patterns. In this paper we introduce non-centred Minimum Curvilinear Embedding (ncMCE), a nonlinear method to overcome this problem. Our analyses show that ncMCE can separate individuals into ethnic groups in cases in which PCA fails to reveal any clear structure. This increased discrimination power arises from ncMCE's ability to better capture the phylogenetic signal in the samples, whereas PCA better reflects their geographic relation. We also demonstrate how ncMCE can discover interesting patterns, even when the data has been poorly pre-processed. The juxtaposition of PCA and ncMCE visualisations provides a new standard of analysis with utility for discovering and validating significant linear/nonlinear complementary patterns in genetic data.

  13. Highlighting nonlinear patterns in population genetics datasets

    KAUST Repository

    Alanis Lobato, Gregorio

    2015-01-30

    Detecting structure in population genetics and case-control studies is important, as it exposes phenomena such as ecoclines, admixture and stratification. Principal Component Analysis (PCA) is a linear dimension-reduction technique commonly used for this purpose, but it struggles to reveal complex, nonlinear data patterns. In this paper we introduce non-centred Minimum Curvilinear Embedding (ncMCE), a nonlinear method to overcome this problem. Our analyses show that ncMCE can separate individuals into ethnic groups in cases in which PCA fails to reveal any clear structure. This increased discrimination power arises from ncMCE\\'s ability to better capture the phylogenetic signal in the samples, whereas PCA better reflects their geographic relation. We also demonstrate how ncMCE can discover interesting patterns, even when the data has been poorly pre-processed. The juxtaposition of PCA and ncMCE visualisations provides a new standard of analysis with utility for discovering and validating significant linear/nonlinear complementary patterns in genetic data.

  14. Using excitation patterns to predict auditory masking

    NARCIS (Netherlands)

    Heijden, van der M.L.; Kohlrausch, A.G.

    1992-01-01

    We investigated how well auditory masking can be predicted from excitation patterns. For this purpose, a quantitative model proposed by Moore and Glasberg (1987) and Glasberg and Moore (1990) was used to calculate excitation patterns evoked by stationary sounds. We performed simulations of a number

  15. The genetic architecture of UV floral patterning in sunflower.

    Science.gov (United States)

    Moyers, Brook T; Owens, Gregory L; Baute, Gregory J; Rieseberg, Loren H

    2017-07-01

    The patterning of floral ultraviolet (UV) pigmentation varies both intra- and interspecifically in sunflowers and many other plant species, impacts pollinator attraction, and can be critical to reproductive success and crop yields. However, the genetic basis for variation in UV patterning is largely unknown. This study examines the genetic architecture for proportional and absolute size of the UV bullseye in Helianthus argophyllus , a close relative of the domesticated sunflower. A camera modified to capture UV light (320-380 nm) was used to phenotype floral UV patterning in an F 2 mapping population, then quantitative trait loci (QTL) were identified using genotyping-by-sequencing and linkage mapping. The ability of these QTL to predict the UV patterning of natural population individuals was also assessed. Proportional UV pigmentation is additively controlled by six moderate effect QTL that are predictive of this phenotype in natural populations. In contrast, UV bullseye size is controlled by a single large effect QTL that also controls flowerhead size and co-localizes with a major flowering time QTL in Helianthus . The co-localization of the UV bullseye size QTL, flowerhead size QTL and a previously known flowering time QTL may indicate a single highly pleiotropic locus or several closely linked loci, which could inhibit UV bullseye size from responding to selection without change in correlated characters. The genetic architecture of proportional UV pigmentation is relatively simple and different from that of UV bullseye size, and so should be able to respond to natural or artificial selection independently. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  16. A method for predicting monthly rainfall patterns

    International Nuclear Information System (INIS)

    Njau, E.C.

    1987-11-01

    A brief survey is made of previous methods that have been used to predict rainfall trends or drought spells in different parts of the earth. The basic methodologies or theoretical strategies used in these methods are compared with contents of a recent theory of Sun-Weather/Climate links (Njau, 1985a; 1985b; 1986; 1987a; 1987b; 1987c) which point towards the possibility of practical climatic predictions. It is shown that not only is the theoretical basis of each of these methodologies or strategies fully incorporated into the above-named theory, but also this theory may be used to develop a technique by which future monthly rainfall patterns can be predicted in further and finer details. We describe the latter technique and then illustrate its workability by means of predictions made on monthly rainfall patterns in some East African meteorological stations. (author). 43 refs, 11 figs, 2 tabs

  17. Spatiotemporal patterns and predictability of cyberattacks.

    Directory of Open Access Journals (Sweden)

    Yu-Zhong Chen

    Full Text Available A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

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

    Science.gov (United States)

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

    2012-01-01

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

  19. Does genetic diversity predict health in humans?

    Directory of Open Access Journals (Sweden)

    Hanne C Lie

    2009-07-01

    Full Text Available Genetic diversity, especially at genes important for immune functioning within the Major Histocompatibility Complex (MHC, has been associated with fitness-related traits, including disease resistance, in many species. Recently, genetic diversity has been associated with mate preferences in humans. Here we asked whether these preferences are adaptive in terms of obtaining healthier mates. We investigated whether genetic diversity (heterozygosity and standardized mean d(2 at MHC and nonMHC microsatellite loci, predicted health in 153 individuals. Individuals with greater allelic diversity (d(2 at nonMHC loci and at one MHC locus, linked to HLA-DRB1, reported fewer symptoms over a four-month period than individuals with lower d(2. In contrast, there were no associations between MHC or nonMHC heterozygosity and health. NonMHC-d(2 has previously been found to predict male preferences for female faces. Thus, the current findings suggest that nonMHC diversity may play a role in both natural and sexual selection acting on human populations.

  20. Predicting mining activity with parallel genetic algorithms

    Science.gov (United States)

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  1. Application of a genetic algorithm to core reload pattern optimization

    International Nuclear Information System (INIS)

    Tanker, E.; Tanker, A.Z.

    1994-01-01

    A genetic algorithm is applied to reload pattern optimization of a PWR core. Evaluating all different distributions of a given batch load separately is found slow and ineffective. Allowing patterns from different distributions to combine reproduce, an optimized pattern better than that obtained from from linear programming is found, albeit in a longer time. (authors). 5 refs., 2 tabs

  2. Energy prediction using spatiotemporal pattern networks

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

    2017-11-01

    This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

  3. A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

    Science.gov (United States)

    Yang, Zheng Rong; Lertmemongkolchai, Ganjana; Tan, Gladys; Felgner, Philip L.; Titball, Richard

    2009-01-01

    Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated. Second, a properly selected function of the antigens as the diagnostic pattern which is commonly unknown is a key to the diagnostic accuracy and the diagnostic effectiveness in clinical use. Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimizing the diagnostic patterns in terms of their accuracy and effectiveness. During optimization, it is aimed to maximize the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final coverage in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack–knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis. Contact: z.r.yang@ex.ac.uk PMID:19561021

  4. AC-600 reactor reloading pattern optimization by using genetic algorithms

    International Nuclear Information System (INIS)

    Wu Hongchun; Xie Zhongsheng; Yao Dong; Li Dongsheng; Zhang Zongyao

    2000-01-01

    The use of genetic algorithms to optimize reloading pattern of the nuclear power plant reactor is proposed. And a new encoding and translating method is given. Optimization results of minimizing core power peak and maximizing cycle length for both low-leakage and out-in loading pattern of AC-600 reactor are obtained

  5. Predictability of Genetic Interactions from Functional Gene Modules

    Directory of Open Access Journals (Sweden)

    Jonathan H. Young

    2017-02-01

    Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

  6. Prediction of male-pattern baldness from genotypes.

    Science.gov (United States)

    Liu, Fan; Hamer, Merel A; Heilmann, Stefanie; Herold, Christine; Moebus, Susanne; Hofman, Albert; Uitterlinden, André G; Nöthen, Markus M; van Duijn, Cornelia M; Nijsten, Tamar Ec; Kayser, Manfred

    2016-06-01

    The global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide polymorphisms (SNPs) identified from previous GWASs of MPB in a total of 2725 German and Dutch males. A logistic regression model considering the genotypes of 25 SNPs from 12 genomic loci demonstrates that early-onset MPB risk is predictable at an accuracy level of 0.74 when 14 SNPs were included in the model, and measured using the area under the receiver-operating characteristic curves (AUC). Considering age as an additional predictor, the model can predict normal MPB status in middle-aged and elderly individuals at a slightly lower accuracy (AUC 0.69-0.71) when 6-11 SNPs were used. A variance partitioning analysis suggests that 55.8% of early-onset MPB genetic liability can be explained by common autosomal SNPs and 23.3% by X-chromosome SNPs. For normal MPB status in elderly individuals, the proportion of explainable variance is lower (42.4% for autosomal and 9.8% for X-chromosome SNPs). The gap between GWAS findings and the variance partitioning results could be explained by a large body of common DNA variants with small effects that will likely be identified in GWAS of increased sample sizes. Although the accuracy obtained here has not reached a clinically desired level, our model was highly informative for up to 19% of Europeans, thus may assist decision making on early MPB intervention actions and in forensic investigations.

  7. Predictive genetic tests: problems and pitfalls.

    Science.gov (United States)

    Davis, J G

    1997-12-29

    The role that genetic factors play in medicine has expanded, owing to such recent advances as those made by the Human Genome Project and the work that has spun off from it. The project is focusing particularly on localization and characterization of recognized human genetic disorders, which in turn increases awareness of the potential for improved treatment of these disorders. Technical advances in genetic testing in the absence of effective treatment has presented the health profession with major ethical challenges. The example of the identification of the BRCA1 and BRCA2 genes in families at high risk for breast and ovarian cancer is presented to illustrate the issues of the sensitivity of the method, the degree of susceptibility a positive result implies, the need for and availability of counseling and patient education, and confidentiality of the test results. A compelling need exists for adequate education about medical genetics to raise the "literacy" rate among health professionals.

  8. Potential genetic polymorphisms predicting polycystic ovary syndrome

    Directory of Open Access Journals (Sweden)

    Yao Chen

    2018-05-01

    Full Text Available Polycystic ovary syndrome (PCOS is a heterogenous endocrine disorder with typical symptoms of oligomenorrhoea, hyperandrogenism, hirsutism, obesity, insulin resistance and increased risk of type 2 diabetes mellitus. Extensive evidence indicates that PCOS is a genetic disease and numerous biochemical pathways have been linked with its pathogenesis. A number of genes from these pathways have been investigated, which include those involved with steroid hormone biosynthesis and metabolism, action of gonadotropin and gonadal hormones, folliculogenesis, obesity and energy regulation, insulin secretion and action and many others. In this review, we summarize the historical and recent findings in genetic polymorphisms of PCOS from the relevant publications and outline some genetic polymorphisms that are potentially associated with the risk of PCOS. This information could uncover candidate genes associating with PCOS, which will be valuable for the development of novel diagnostic and treatment platforms for PCOS patients.

  9. Patterns of regional cerebellar atrophy in genetic frontotemporal dementia

    Directory of Open Access Journals (Sweden)

    Martina Bocchetta

    2016-01-01

    Conclusion: There appears to be a differential pattern of cerebellar atrophy in the major genetic forms of FTD, being relatively spared in GRN, localized to the lobule VIIa-Crus I in the superior-posterior region of the cerebellum in C9orf72, the area connected via the thalamus to the prefrontal cortex and involved in cognitive function, and localized to the vermis in MAPT, the ‘limbic cerebellum’ involved in emotional processing.

  10. Wetlands explain most in the genetic divergence pattern of Oncomelania hupensis.

    Science.gov (United States)

    Liang, Lu; Liu, Yang; Liao, Jishan; Gong, Peng

    2014-10-01

    Understanding the divergence patterns of hosts could shed lights on the prediction of their parasite transmission. No effort has been devoted to understand the drivers of genetic divergence pattern of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum. Based on a compilation of two O. hupensis gene datasets covering a wide geographic range in China and an array of geographical distance and environmental dissimilarity metrics built from earth observation data and ecological niche modeling, we conducted causal modeling analysis via simple, partial Mantel test and local polynomial fitting to understand the interactions among isolation-by-distance, isolation-by-environment, and genetic divergence. We found that geography contributes more to genetic divergence than environmental isolation, and among all variables involved, wetland showed the strongest correlation with the genetic pairwise distances. These results suggested that in China, O. hupensis dispersal is strongly linked to the distribution of wetlands, and the current divergence pattern of both O. hupensis and schistosomiasis might be altered due to the changed wetland pattern with the accomplishment of the Three Gorges Dam and the South-to-North water transfer project. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Conservation genetics and geographic patterns of genetic variation of the vulnerable officinal herb Fritillaria walujewii (Liliaceae)

    Science.gov (United States)

    Zhihao Su; Borong Pan; Stewart C. Sanderson; Xiaojun Shi; Xiaolong Jiang

    2015-01-01

    The Chinese herb Fritillaria walujewii Regel is an important officinal species that is vulnerable because of over-harvesting. Here, we examined the geographic pattern of genetic variation across the species entire range, to study its evolution process and give implication needed for the conservation. Nine haplotypes were detected on the basis of three chloroplast...

  12. Endogenous network states predict gain or loss of functions for genetic mutations in hepatocellular carcinoma.

    Science.gov (United States)

    Wang, Gaowei; Su, Hang; Yu, Helin; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

    2016-02-01

    Cancers have been typically characterized by genetic mutations. Patterns of such mutations have traditionally been analysed by posteriori statistical association approaches. One may ponder the possibility of a priori determination of any mutation regularity. Here by exploring biological processes implied in a mechanistic theory recently developed (the endogenous molecular-cellular network theory), we found that the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. With hepatocellular carcinoma (HCC) as an example, we found that the normal hepatocyte and cancerous hepatocyte can be represented by robust stable states of one single endogenous network. These stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable predictions on accumulated and preferred mutation spectra in normal tissue. The validation of predicted cancer state mutation patterns demonstrates the usefulness and potential of a causal dynamical framework to understand and predict genetic mutations in cancer. © 2016 The Author(s).

  13. Prediction of quantitative phenotypes based on genetic networks: a case study in yeast sporulation

    Directory of Open Access Journals (Sweden)

    Shen Li

    2010-09-01

    Full Text Available Abstract Background An exciting application of genetic network is to predict phenotypic consequences for environmental cues or genetic perturbations. However, de novo prediction for quantitative phenotypes based on network topology is always a challenging task. Results Using yeast sporulation as a model system, we have assembled a genetic network from literature and exploited Boolean network to predict sporulation efficiency change upon deleting individual genes. We observe that predictions based on the curated network correlate well with the experimentally measured values. In addition, computational analysis reveals the robustness and hysteresis of the yeast sporulation network and uncovers several patterns of sporulation efficiency change caused by double gene deletion. These discoveries may guide future investigation of underlying mechanisms. We have also shown that a hybridized genetic network reconstructed from both temporal microarray data and literature is able to achieve a satisfactory prediction accuracy of the same quantitative phenotypes. Conclusions This case study illustrates the value of predicting quantitative phenotypes based on genetic network and provides a generic approach.

  14. Inferring ancient Agave cultivation practices from contemporary genetic patterns.

    Science.gov (United States)

    Parker, Kathleen C; Trapnell, Dorset W; Hamrick, J L; Hodgson, Wendy C; Parker, Albert J

    2010-04-01

    Several Agave species have played an important ethnobotanical role since prehistory in Mesoamerica and semiarid areas to the north, including central Arizona. We examined genetic variation in relict Agave parryi populations northeast of the Mogollon Rim in Arizona, remnants from anthropogenic manipulation over 600 years ago. We used both allozymes and microsatellites to compare genetic variability and structure in anthropogenically manipulated populations with putative wild populations, to assess whether they were actively cultivated or the result of inadvertent manipulation, and to determine probable source locations for anthropogenic populations. Wild populations were more genetically diverse than anthropogenic populations, with greater expected heterozygosity, polymorphic loci, effective number of alleles and allelic richness. Anthropogenic populations exhibited many traits indicative of past active cultivation: fixed heterozygosity for several loci in all populations (nonexistent in wild populations); fewer multilocus genotypes, which differed by fewer alleles; and greater differentiation among populations than was characteristic of wild populations. Furthermore, manipulated populations date from a period when changes in the cultural context may have favoured active cultivation near dwellings. Patterns of genetic similarity among populations suggest a complex anthropogenic history. Anthropogenic populations were not simply derived from the closest wild A. parryi stock; instead they evidently came from more distant, often more diverse, wild populations, perhaps obtained through trade networks in existence at the time of cultivation.

  15. Use of a twin dataset to identify AMD-related visual patterns controlled by genetic factors

    Science.gov (United States)

    Quellec, Gwénolé; Abràmoff, Michael D.; Russell, Stephen R.

    2010-03-01

    The mapping of genotype to the phenotype of age-related macular degeneration (AMD) is expected to improve the diagnosis and treatment of the disease in a near future. In this study, we focused on the first step to discover this mapping: we identified visual patterns related to AMD which seem to be controlled by genetic factors, without explicitly relating them to the genes. For this purpose, we used a dataset of eye fundus photographs from 74 twin pairs, either monozygotic twins, who have the same genotype, or dizygotic twins, whose genes responsible for AMD are less likely to be identical. If we are able to differentiate monozygotic twins from dizygotic twins, based on a given visual pattern, then this pattern is likely to be controlled by genetic factors. The main visible consequence of AMD is the apparition of drusen between the retinal pigment epithelium and Bruch's membrane. We developed two automated drusen detectors based on the wavelet transform: a shape-based detector for hard drusen, and a texture- and color- based detector for soft drusen. Forty visual features were evaluated at the location of the automatically detected drusen. These features characterize the texture, the shape, the color, the spatial distribution, or the amount of drusen. A distance measure between twin pairs was defined for each visual feature; a smaller distance should be measured between monozygotic twins for visual features controlled by genetic factors. The predictions of several visual features (75.7% accuracy) are comparable or better than the predictions of human experts.

  16. The pattern of cognitive symptoms predicts time to dementia onset.

    NARCIS (Netherlands)

    Sacuiu, S.; Gustafson, D.; Johansson, B.; Thorvaldsson, V.; Berg, S.; Sjogren, J.M.C.; Guo, X.; Ostling, S.; Skoog, I.

    2009-01-01

    BACKGROUND: Few studies have examined whether cognitive symptom patterns differ by age and length of time before dementia onset. Our objective was to investigate whether different patterns of cognitive symptoms at ages 70, 75, and 79 years predict short-term (< or =5 years) and long-term (>5 years)

  17. Predicting fragmentation sizing profiles for different blasting patterns

    International Nuclear Information System (INIS)

    Sheikh, A.M.; Chung, S.H.

    1987-01-01

    This paper evaluates the efficiency of blasting in a large scale underground heap leaching operation. The prediction model is based on the dynamic tensile breaking strength of rock formation, the detonation characteristics of the explosives and the drill hole pattern. The modelling includes crack pattern development and fragmentation computation fitted by the Rosin-Rammler distribution equation

  18. Dispersal similarly shapes both population genetics and community patterns in the marine realm

    KAUST Repository

    Chust, Guillem

    2016-06-27

    Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

  19. Dispersal similarly shapes both population genetics and community patterns in the marine realm

    Science.gov (United States)

    Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Fernández de Puelles, María L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Veríssimo, Helena; Zervoudaki, Soultana; Borja, Angel

    2016-06-01

    Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

  20. Dispersal similarly shapes both population genetics and community patterns in the marine realm

    KAUST Repository

    Chust, Guillem; Villarino, Ernesto; Chenuil, Anne; Irigoien, Xabier; Bizsel, Nihayet; Bode, Antonio; Broms, Cecilie; Claus, Simon; Ferná ndez de Puelles, Marí a L.; Fonda-Umani, Serena; Hoarau, Galice; Mazzocchi, Maria G.; Mozetič, Patricija; Vandepitte, Leen; Verí ssimo, Helena; Zervoudaki, Soultana; Borja, Angel

    2016-01-01

    Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.

  1. Real coded genetic algorithm for fuzzy time series prediction

    Science.gov (United States)

    Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.

    2017-10-01

    Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.

  2. Using Genetic Distance to Infer the Accuracy of Genomic Prediction.

    Directory of Open Access Journals (Sweden)

    Marco Scutari

    2016-09-01

    Full Text Available The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics.

  3. Multifactor dimensionality reduction analysis identifies specific nucleotide patterns promoting genetic polymorphisms

    Directory of Open Access Journals (Sweden)

    Arehart Eric

    2009-03-01

    Full Text Available Abstract Background The fidelity of DNA replication serves as the nidus for both genetic evolution and genomic instability fostering disease. Single nucleotide polymorphisms (SNPs constitute greater than 80% of the genetic variation between individuals. A new theory regarding DNA replication fidelity has emerged in which selectivity is governed by base-pair geometry through interactions between the selected nucleotide, the complementary strand, and the polymerase active site. We hypothesize that specific nucleotide combinations in the flanking regions of SNP fragments are associated with mutation. Results We modeled the relationship between DNA sequence and observed polymorphisms using the novel multifactor dimensionality reduction (MDR approach. MDR was originally developed to detect synergistic interactions between multiple SNPs that are predictive of disease susceptibility. We initially assembled data from the Broad Institute as a pilot test for the hypothesis that flanking region patterns associate with mutagenesis (n = 2194. We then confirmed and expanded our inquiry with human SNPs within coding regions and their flanking sequences collected from the National Center for Biotechnology Information (NCBI database (n = 29967 and a control set of sequences (coding region not associated with SNP sites randomly selected from the NCBI database (n = 29967. We discovered seven flanking region pattern associations in the Broad dataset which reached a minimum significance level of p ≤ 0.05. Significant models (p Conclusion The present study represents the first use of this computational methodology for modeling nonlinear patterns in molecular genetics. MDR was able to identify distinct nucleotide patterning around sites of mutations dependent upon the observed nucleotide change. We discovered one flanking region set that included five nucleotides clustered around a specific type of SNP site. Based on the strongly associated patterns identified in

  4. Geometric Semantic Genetic Programming Algorithm and Slump Prediction

    OpenAIRE

    Xu, Juncai; Shen, Zhenzhong; Ren, Qingwen; Xie, Xin; Yang, Zhengyu

    2017-01-01

    Research on the performance of recycled concrete as building material in the current world is an important subject. Given the complex composition of recycled concrete, conventional methods for forecasting slump scarcely obtain satisfactory results. Based on theory of nonlinear prediction method, we propose a recycled concrete slump prediction model based on geometric semantic genetic programming (GSGP) and combined it with recycled concrete features. Tests show that the model can accurately p...

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

    NARCIS (Netherlands)

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

    1994-01-01

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

  6. Genetic selection for coping style predicts stressor susceptibility

    NARCIS (Netherlands)

    Veenema, AH; Meijer, OC; de Kloet, ER; Koolhaas, JM

    Genetically selected aggressive (SAL) and nonaggressive (LAL) male wild house-mice which show distinctly different coping styles, also display a differential regulation of the hypothalamic-pituitary-adrenal axis after exposure to an acute stressor. To test the hypothesis that coping style predicts

  7. Ethical issues in predictive genetic testing: a public health perspective

    Science.gov (United States)

    Fulda, K G; Lykens, K

    2006-01-01

    As a result of the increase in genetic testing and the fear of discrimination by insurance companies, employers, and society as a result of genetic testing, the disciplines of ethics, public health, and genetics have converged. Whether relatives of someone with a positive predictive genetic test should be notified of the results and risks is a matter urgently in need of debate. Such a debate must encompass the moral and ethical obligations of the diagnosing physician and the patient. The decision to inform or not will vary depending on what moral theory is used. Utilising the utilitarian and libertarian theories produces different outcomes. The principles of justice and non‐maleficence will also play an important role in the decision. PMID:16507657

  8. Ethical issues in predictive genetic testing: a public health perspective.

    Science.gov (United States)

    Fulda, K G; Lykens, K

    2006-03-01

    As a result of the increase in genetic testing and the fear of discrimination by insurance companies, employers, and society as a result of genetic testing, the disciplines of ethics, public health, and genetics have converged. Whether relatives of someone with a positive predictive genetic test should be notified of the results and risks is a matter urgently in need of debate. Such a debate must encompass the moral and ethical obligations of the diagnosing physician and the patient. The decision to inform or not will vary depending on what moral theory is used. Utilising the utilitarian and libertarian theories produces different outcomes. The principles of justice and non-maleficence will also play an important role in the decision.

  9. Prediction of Human Activity by Discovering Temporal Sequence Patterns.

    Science.gov (United States)

    Li, Kang; Fu, Yun

    2014-08-01

    Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

  10. Predicting patterns of glioma recurrence using diffusion tensor imaging

    International Nuclear Information System (INIS)

    Price, Stephen J.; Pickard, John D.; Jena, Rajesh; Burnet, Neil G.; Carpenter, T.A.; Gillard, Jonathan H.

    2007-01-01

    Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T 2 -weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials. (orig.)

  11. Predicting patterns of glioma recurrence using diffusion tensor imaging

    Energy Technology Data Exchange (ETDEWEB)

    Price, Stephen J.; Pickard, John D. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Academic Neurosurgery Unit (United Kingdom); University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences (United Kingdom); Jena, Rajesh; Burnet, Neil G. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, University Department of Oncology (United Kingdom); Carpenter, T.A. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences (United Kingdom); Gillard, Jonathan H. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, University Department of Radiology (United Kingdom)

    2007-07-15

    Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T{sub 2}-weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials. (orig.)

  12. Genetic population structure accounts for contemporary ecogeographic patterns in tropic and subtropic-dwelling humans.

    Science.gov (United States)

    Hruschka, Daniel J; Hadley, Craig; Brewis, Alexandra A; Stojanowski, Christopher M

    2015-01-01

    Contemporary human populations conform to ecogeographic predictions that animals will become more compact in cooler climates and less compact in warmer ones. However, it remains unclear to what extent this pattern reflects plastic responses to current environments or genetic differences among populations. Analyzing anthropometric surveys of 232,684 children and adults from across 80 ethnolinguistic groups in sub-Saharan Africa, Asia and the Americas, we confirm that body surface-to-volume correlates with contemporary temperature at magnitudes found in more latitudinally diverse samples (Adj. R2 = 0.14-0.28). However, far more variation in body surface-to-volume is attributable to genetic population structure (Adj. R2 = 0.50-0.74). Moreover, genetic population structure accounts for nearly all of the observed relationship between contemporary temperature and body surface-to-volume among children and adults. Indeed, after controlling for population structure, contemporary temperature accounts for no more than 4% of the variance in body form in these groups. This effect of genetic affinity on body form is also independent of other ecological variables, such as dominant mode of subsistence and household wealth per capita. These findings suggest that the observed fit of human body surface-to-volume with current climate in this sample reflects relatively large effects of existing genetic population structure of contemporary humans compared to plastic response to current environments.

  13. Genetic population structure accounts for contemporary ecogeographic patterns in tropic and subtropic-dwelling humans.

    Directory of Open Access Journals (Sweden)

    Daniel J Hruschka

    Full Text Available Contemporary human populations conform to ecogeographic predictions that animals will become more compact in cooler climates and less compact in warmer ones. However, it remains unclear to what extent this pattern reflects plastic responses to current environments or genetic differences among populations. Analyzing anthropometric surveys of 232,684 children and adults from across 80 ethnolinguistic groups in sub-Saharan Africa, Asia and the Americas, we confirm that body surface-to-volume correlates with contemporary temperature at magnitudes found in more latitudinally diverse samples (Adj. R2 = 0.14-0.28. However, far more variation in body surface-to-volume is attributable to genetic population structure (Adj. R2 = 0.50-0.74. Moreover, genetic population structure accounts for nearly all of the observed relationship between contemporary temperature and body surface-to-volume among children and adults. Indeed, after controlling for population structure, contemporary temperature accounts for no more than 4% of the variance in body form in these groups. This effect of genetic affinity on body form is also independent of other ecological variables, such as dominant mode of subsistence and household wealth per capita. These findings suggest that the observed fit of human body surface-to-volume with current climate in this sample reflects relatively large effects of existing genetic population structure of contemporary humans compared to plastic response to current environments.

  14. Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms

    Science.gov (United States)

    Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.

    2017-12-01

    Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  15. Acute ischaemic stroke prediction from physiological time series patterns

    Directory of Open Access Journals (Sweden)

    Qing Zhang,

    2013-05-01

    Full Text Available BackgroundStroke is one of the major diseases with human mortality. Recent clinical research has indicated that early changes in common physiological variables represent a potential therapeutic target, thus the manipulation of these variables may eventually yield an effective way to optimise stroke recovery.AimsWe examined correlations between physiological parameters of patients during the first 48 hours after a stroke, and their stroke outcomes after 3 months. We wanted to discover physiological determinants that could be used to improve health outcomes by supporting the medical decisions that need to be made early on a patient’s stroke experience.Method We applied regression-based machine learning techniques to build a prediction algorithm that can forecast 3-month outcomes from initial physiological time series data during the first 48 hours after stroke. In our method, not only did we use statistical characteristics as traditional prediction features, but also we adopted trend patterns of time series data as new key features.ResultsWe tested our prediction method on a real physiological data set of stroke patients. The experiment results revealed an average high precision rate: 90%. We also tested prediction methods only considering statistical characteristics of physiological data, and concluded an average precision rate: 71%.ConclusionWe demonstrated that using trend pattern features in prediction methods improved the accuracy of stroke outcome prediction. Therefore, trend patterns of physiological time series data have an important role in the early treatment of patients with acute ischaemic stroke.

  16. Merlin : microsimulation system for predicting leisure activity-travel patterns

    NARCIS (Netherlands)

    Middelkoop, van M.; Borgers, A.W.J.; Timmermans, H.J.P.

    2004-01-01

    Development of a model of annual activity-travel patterns of leisure and vacation travel is reported. The simulation system, called Merlin, is a hybrid model system consisting of discrete choice models and rule-based models. It predicts the annual number of day trips and vacations, and the profile

  17. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  18. Genetic Programming for Sea Level Predictions in an Island Environment

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2010-03-01

    Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

  19. Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

    Directory of Open Access Journals (Sweden)

    MORARIU, N.

    2007-04-01

    Full Text Available The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.

  20. Size-based predictions of food web patterns

    DEFF Research Database (Denmark)

    Zhang, Lai; Hartvig, Martin; Knudsen, Kim

    2014-01-01

    We employ size-based theoretical arguments to derive simple analytic predictions of ecological patterns and properties of natural communities: size-spectrum exponent, maximum trophic level, and susceptibility to invasive species. The predictions are brought about by assuming that an infinite number...... of species are continuously distributed on a size-trait axis. It is, however, an open question whether such predictions are valid for a food web with a finite number of species embedded in a network structure. We address this question by comparing the size-based predictions to results from dynamic food web...... simulations with varying species richness. To this end, we develop a new size- and trait-based food web model that can be simplified into an analytically solvable size-based model. We confirm existing solutions for the size distribution and derive novel predictions for maximum trophic level and invasion...

  1. Imbalanced target prediction with pattern discovery on clinical data repositories.

    Science.gov (United States)

    Chan, Tak-Ming; Li, Yuxi; Chiau, Choo-Chiap; Zhu, Jane; Jiang, Jie; Huo, Yong

    2017-04-20

    Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice. We propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed. We compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values repositories with imbalance and noise. The prediction results and interpretable patterns can provide insights in an agile and inexpensive way for the potential formal studies.

  2. Genetics and evolution of colour patterns in reptiles.

    Science.gov (United States)

    Olsson, Mats; Stuart-Fox, Devi; Ballen, Cissy

    2013-01-01

    The study of coloration in the polyphyletic reptilians has flourished in the last two decades, in particular with respect to the underlying genetics of colour traits, the function of colours in social interactions, and ongoing selection on these traits in the wild. The taxonomic bias, however, is profound: at this level of resolution almost all available information is for diurnal lizards. Therefore, we focus on case studies, for which there are as complete causal sequences of colour evolution as possible, from phenotypic expression of variation in colour, to ongoing selection in the wild. For work prior to 1992 and for a broader coverage of reptilian coloration we refer the readers to Cooper and Greenburg's (Biology of the Reptilia, 1992) review. There are seven major conclusions we would like to emphasise: (a) visual systems in diurnal lizards are broadly conserved but among the wider range of reptiles in general, there is functionally important variation in the number and type of photoreceptors, spectral tuning of photopigments and optical properties of the eye; (b) coloration in reptiles is a function of complex interactions between structural and pigmentary components, with implications for both proximate control and condition dependence of colour expression; (c) studies of colour-variable species have enabled estimates of heritability of colour and colour patterns, which often show a simple Mendelian pattern of inheritance; (d) colour-polymorphic lizard species sometimes, but not always, show striking differences in genetically encoded reproductive tactics and provide useful models for studying the evolution and maintenance of polymorphism; (e) both male and female colours are sometimes, but not always, a significant component of socio-sexual signalling, often based on multiple traits; (f) evidence for effects of hormones and condition on colour expression, and trade-offs with immunocompetence and parasite load, is variable; (g) lizards show fading of colours

  3. Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

    Directory of Open Access Journals (Sweden)

    Rosen Jimmy

    2009-09-01

    Full Text Available Abstract Background Detailed experimental three dimensional structures of carbohydrates are often difficult to acquire. Molecular modelling and computational conformation prediction are therefore commonly used tools for three dimensional structure studies. Modelling procedures generally require significant training and computing resources, which is often impractical for most experimental chemists and biologists. Shape has been developed to improve the availability of modelling in this field. Results The Shape software package has been developed for simplicity of use and conformation prediction performance. A trivial user interface coupled to an efficient genetic algorithm conformation search makes it a powerful tool for automated modelling. Carbohydrates up to a few hundred atoms in size can be investigated on common computer hardware. It has been shown to perform well for the prediction of over four hundred bioactive oligosaccharides, as well as compare favourably with previously published studies on carbohydrate conformation prediction. Conclusion The Shape fully automated conformation prediction can be used by scientists who lack significant modelling training, and performs well on computing hardware such as laptops and desktops. It can also be deployed on computer clusters for increased capacity. The prediction accuracy under the default settings is good, as it agrees well with experimental data and previously published conformation prediction studies. This software is available both as open source and under commercial licenses.

  4. Genetic prediction of type 2 diabetes using deep neural network.

    Science.gov (United States)

    Kim, J; Kim, J; Kwak, M J; Bajaj, M

    2018-04-01

    Type 2 diabetes (T2DM) has strong heritability but genetic models to explain heritability have been challenging. We tested deep neural network (DNN) to predict T2DM using the nested case-control study of Nurses' Health Study (3326 females, 45.6% T2DM) and Health Professionals Follow-up Study (2502 males, 46.5% T2DM). We selected 96, 214, 399, and 678 single-nucleotide polymorphism (SNPs) through Fisher's exact test and L1-penalized logistic regression. We split each dataset randomly in 4:1 to train prediction models and test their performance. DNN and logistic regressions showed better area under the curve (AUC) of ROC curves than the clinical model when 399 or more SNPs included. DNN was superior than logistic regressions in AUC with 399 or more SNPs in male and 678 SNPs in female. Addition of clinical factors consistently increased AUC of DNN but failed to improve logistic regressions with 214 or more SNPs. In conclusion, we show that DNN can be a versatile tool to predict T2DM incorporating large numbers of SNPs and clinical information. Limitations include a relatively small number of the subjects mostly of European ethnicity. Further studies are warranted to confirm and improve performance of genetic prediction models using DNN in different ethnic groups. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Towards a predictive theory for genetic regulatory networks

    Science.gov (United States)

    Tkacik, Gasper

    When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

  6. Patterns, Entropy, and Predictability of Human Mobility and Life

    Science.gov (United States)

    Qin, Shao-Meng; Verkasalo, Hannu; Mohtaschemi, Mikael; Hartonen, Tuomo; Alava, Mikko

    2012-01-01

    Cellular phones are now offering an ubiquitous means for scientists to observe life: how people act, move and respond to external influences. They can be utilized as measurement devices of individual persons and for groups of people of the social context and the related interactions. The picture of human life that emerges shows complexity, which is manifested in such data in properties of the spatiotemporal tracks of individuals. We extract from smartphone-based data for a set of persons important locations such as “home”, “work” and so forth over fixed length time-slots covering the days in the data-set (see also [1], [2]). This set of typical places is heavy-tailed, a power-law distribution with an exponent close to −1.7. To analyze the regularities and stochastic features present, the days are classified for each person into regular, personal patterns. To this are superimposed fluctuations for each day. This randomness is measured by “life” entropy, computed both before and after finding the clustering so as to subtract the contribution of a number of patterns. The main issue that we then address is how predictable individuals are in their mobility. The patterns and entropy are reflected in the predictability of the mobility of the life both individually and on average. We explore the simple approaches to guess the location from the typical behavior, and of exploiting the transition probabilities with time from location or activity A to B. The patterns allow an enhanced predictability, at least up to a few hours into the future from the current location. Such fixed habits are most clearly visible in the working-day length. PMID:23300542

  7. Genetic Networks and Anticipation of Gene Expression Patterns

    Science.gov (United States)

    Gebert, J.; Lätsch, M.; Pickl, S. W.; Radde, N.; Weber, G.-W.; Wünschiers, R.

    2004-08-01

    An interesting problem for computational biology is the analysis of time-series expression data. Here, the application of modern methods from dynamical systems, optimization theory, numerical algorithms and the utilization of implicit discrete information lead to a deeper understanding. In [1], we suggested to represent the behavior of time-series gene expression patterns by a system of ordinary differential equations, which we analytically and algorithmically investigated under the parametrical aspect of stability or instability. Our algorithm strongly exploited combinatorial information. In this paper, we deepen, extend and exemplify this study from the viewpoint of underlying mathematical modelling. This modelling consists in evaluating DNA-microarray measurements as the basis of anticipatory prediction, in the choice of a smooth model given by differential equations, in an approach of the right-hand side with parametric matrices, and in a discrete approximation which is a least squares optimization problem. We give a mathematical and biological discussion, and pay attention to the special case of a linear system, where the matrices do not depend on the state of expressions. Here, we present first numerical examples.

  8. Consumer preferences for the predictive genetic test for Alzheimer disease.

    Science.gov (United States)

    Huang, Ming-Yi; Huston, Sally A; Perri, Matthew

    2014-04-01

    The purpose of this study was to assess consumer preferences for predictive genetic testing for Alzheimer disease in the United States. A rating conjoint analysis was conducted using an anonymous online survey distributed by Qualtrics to a general population panel in April 2011 in the United States. The study design included three attributes: Accuracy (40%, 80%, and 100%), Treatment Availability (Cure is available/Drug for symptom relief but no cure), and Anonymity (Anonymous/Not anonymous). A total of 12 scenarios were used to elicit people's preference, assessed by an 11-point scale. The respondents also indicated their highest willingness-to-pay (WTP) for each scenario through open-ended questions. A total of 295 responses were collected over 4 days. The most important attribute for the aggregate model was Accuracy, contributing 64.73% to the preference rating. Treatment Availability and Anonymity contributed 20.72% and 14.59%, respectively, to the preference rating. The median WTP for the highest-rating scenario (Accuracy 100%, a cure is available, test result is anonymous) was $100 (mean = $276). The median WTP for the lowest-rating scenario (40% accuracy, no cure but drugs for symptom relief, not anonymous) was zero (mean = $34). The results of this study highlight attributes people find important when making the hypothetical decision to obtain an AD genetic test. These results should be of interests to policy makers, genetic test developers and health care providers.

  9. Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

    Science.gov (United States)

    Marcińska, Magdalena; Pośpiech, Ewelina; Abidi, Sarah; Andersen, Jeppe Dyrberg; van den Berge, Margreet; Carracedo, Ángel; Eduardoff, Mayra; Marczakiewicz-Lustig, Anna; Morling, Niels; Sijen, Titia; Skowron, Małgorzata; Söchtig, Jens; Syndercombe-Court, Denise; Weiler, Natalie; Schneider, Peter M; Ballard, David; Børsting, Claus; Parson, Walther; Phillips, Chris; Branicki, Wojciech

    2015-01-01

    Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

  10. Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

    Directory of Open Access Journals (Sweden)

    Magdalena Marcińska

    Full Text Available Androgenetic alopecia, known in men as male pattern baldness (MPB, is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC. Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

  11. Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

    Science.gov (United States)

    Tolo, Isaiah; Thomas, Jonathan C.; Fischer, Rebecca S. B.; Brown, Eric L.; Gray, Barry M.

    2016-01-01

    Staphylococcus epidermidis is a ubiquitous colonizer of human skin and a common cause of medical device-associated infections. The extent to which the population genetic structure of S. epidermidis distinguishes commensal from pathogenic isolates is unclear. Previously, Bayesian clustering of 437 multilocus sequence types (STs) in the international database revealed a population structure of six genetic clusters (GCs) that may reflect the species' ecology. Here, we first verified the presence of six GCs, including two (GC3 and GC5) with significant admixture, in an updated database of 578 STs. Next, a single nucleotide polymorphism (SNP) assay was developed that accurately assigned 545 (94%) of 578 STs to GCs. Finally, the hypothesis that GCs could distinguish isolation sources was tested by SNP typing and GC assignment of 154 isolates from hospital patients with bacteremia and those with blood culture contaminants and from nonhospital carriage. GC5 was isolated almost exclusively from hospital sources. GC1 and GC6 were isolated from all sources but were overrepresented in isolates from nonhospital and infection sources, respectively. GC2, GC3, and GC4 were relatively rare in this collection. No association was detected between fdh-positive isolates (GC2 and GC4) and nonhospital sources. Using a machine learning algorithm, GCs predicted hospital and nonhospital sources with 80% accuracy and predicted infection and contaminant sources with 45% accuracy, which was comparable to the results seen with a combination of five genetic markers (icaA, IS256, sesD [bhp], mecA, and arginine catabolic mobile element [ACME]). Thus, analysis of population structure with subgenomic data shows the distinction of hospital and nonhospital sources and the near-inseparability of sources within a hospital. PMID:27076664

  12. Predicting vehicle fuel consumption patterns using floating vehicle data.

    Science.gov (United States)

    Du, Yiman; Wu, Jianping; Yang, Senyan; Zhou, Liutong

    2017-09-01

    The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers' information and vehicles' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model. Copyright © 2017. Published by Elsevier B.V.

  13. Genetic risk prediction and neurobiological understanding of alcoholism.

    Science.gov (United States)

    Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefer, F; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B

    2014-05-20

    We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress

  14. Assessment of the genetic diversity and pattern of relationship of ...

    African Journals Online (AJOL)

    SAM

    2014-04-02

    Apr 2, 2014 ... Cluster and principal coordinate analysis of the 30 ... The FST value (0.63) indicated a very high genetic differentiation as expected for ..... diversity) using Markov chain method showed that the ..... WL, Lee M, Porter K (2000).

  15. High Interannual Variability in Connectivity and Genetic Pool of a Temperate Clingfish Matches Oceanographic Transport Predictions

    Science.gov (United States)

    Teixeira, Sara; Assis, Jorge; Serrão, Ester A.; Gonçalves, Emanuel J.; Borges, Rita

    2016-01-01

    Adults of most marine benthic and demersal fish are site-attached, with the dispersal of their larval stages ensuring connectivity among populations. In this study we aimed to infer spatial and temporal variation in population connectivity and dispersal of a marine fish species, using genetic tools and comparing these with oceanographic transport. We focused on an intertidal rocky reef fish species, the shore clingfish Lepadogaster lepadogaster, along the southwest Iberian Peninsula, in 2011 and 2012. We predicted high levels of self-recruitment and distinct populations, due to short pelagic larval duration and because all its developmental stages have previously been found near adult habitats. Genetic analyses based on microsatellites countered our prediction and a biophysical dispersal model showed that oceanographic transport was a good explanation for the patterns observed. Adult sub-populations separated by up to 300 km of coastline displayed no genetic differentiation, revealing a single connected population with larvae potentially dispersing long distances over hundreds of km. Despite this, parentage analysis performed on recruits from one focal site within the Marine Park of Arrábida (Portugal), revealed self-recruitment levels of 2.5% and 7.7% in 2011 and 2012, respectively, suggesting that both long- and short-distance dispersal play an important role in the replenishment of these populations. Population differentiation and patterns of dispersal, which were highly variable between years, could be linked to the variability inherent in local oceanographic processes. Overall, our measures of connectivity based on genetic and oceanographic data highlight the relevance of long-distance dispersal in determining the degree of connectivity, even in species with short pelagic larval durations. PMID:27911952

  16. Phylogeographic Patterns in Africa and High Resolution Delineation of Genetic Clades in the Lion (Panthera leo)

    Science.gov (United States)

    Bertola, L. D.; Jongbloed, H.; van der Gaag, K. J.; de Knijff, P.; Yamaguchi, N.; Hooghiemstra, H.; Bauer, H.; Henschel, P.; White, P. A.; Driscoll, C. A.; Tende, T.; Ottosson, U.; Saidu, Y.; Vrieling, K.; de Iongh, H. H.

    2016-08-01

    Comparative phylogeography of African savannah mammals shows a congruent pattern in which populations in West/Central Africa are distinct from populations in East/Southern Africa. However, for the lion, all African populations are currently classified as a single subspecies (Panthera leo leo), while the only remaining population in Asia is considered to be distinct (Panthera leo persica). This distinction is disputed both by morphological and genetic data. In this study we introduce the lion as a model for African phylogeography. Analyses of mtDNA sequences reveal six supported clades and a strongly supported ancestral dichotomy with northern populations (West Africa, Central Africa, North Africa/Asia) on one branch, and southern populations (North East Africa, East/Southern Africa and South West Africa) on the other. We review taxonomies and phylogenies of other large savannah mammals, illustrating that similar clades are found in other species. The described phylogeographic pattern is considered in relation to large scale environmental changes in Africa over the past 300,000 years, attributable to climate. Refugial areas, predicted by climate envelope models, further confirm the observed pattern. We support the revision of current lion taxonomy, as recognition of a northern and a southern subspecies is more parsimonious with the evolutionary history of the lion.

  17. Phylogeographic Patterns in Africa and High Resolution Delineation of Genetic Clades in the Lion (Panthera leo).

    Science.gov (United States)

    Bertola, L D; Jongbloed, H; van der Gaag, K J; de Knijff, P; Yamaguchi, N; Hooghiemstra, H; Bauer, H; Henschel, P; White, P A; Driscoll, C A; Tende, T; Ottosson, U; Saidu, Y; Vrieling, K; de Iongh, H H

    2016-08-04

    Comparative phylogeography of African savannah mammals shows a congruent pattern in which populations in West/Central Africa are distinct from populations in East/Southern Africa. However, for the lion, all African populations are currently classified as a single subspecies (Panthera leo leo), while the only remaining population in Asia is considered to be distinct (Panthera leo persica). This distinction is disputed both by morphological and genetic data. In this study we introduce the lion as a model for African phylogeography. Analyses of mtDNA sequences reveal six supported clades and a strongly supported ancestral dichotomy with northern populations (West Africa, Central Africa, North Africa/Asia) on one branch, and southern populations (North East Africa, East/Southern Africa and South West Africa) on the other. We review taxonomies and phylogenies of other large savannah mammals, illustrating that similar clades are found in other species. The described phylogeographic pattern is considered in relation to large scale environmental changes in Africa over the past 300,000 years, attributable to climate. Refugial areas, predicted by climate envelope models, further confirm the observed pattern. We support the revision of current lion taxonomy, as recognition of a northern and a southern subspecies is more parsimonious with the evolutionary history of the lion.

  18. Genomic Features That Predict Allelic Imbalance in Humans Suggest Patterns of Constraint on Gene Expression Variation

    Science.gov (United States)

    Fédrigo, Olivier; Haygood, Ralph; Mukherjee, Sayan; Wray, Gregory A.

    2009-01-01

    Variation in gene expression is an important contributor to phenotypic diversity within and between species. Although this variation often has a genetic component, identification of the genetic variants driving this relationship remains challenging. In particular, measurements of gene expression usually do not reveal whether the genetic basis for any observed variation lies in cis or in trans to the gene, a distinction that has direct relevance to the physical location of the underlying genetic variant, and which may also impact its evolutionary trajectory. Allelic imbalance measurements identify cis-acting genetic effects by assaying the relative contribution of the two alleles of a cis-regulatory region to gene expression within individuals. Identification of patterns that predict commonly imbalanced genes could therefore serve as a useful tool and also shed light on the evolution of cis-regulatory variation itself. Here, we show that sequence motifs, polymorphism levels, and divergence levels around a gene can be used to predict commonly imbalanced genes in a human data set. Reduction of this feature set to four factors revealed that only one factor significantly differentiated between commonly imbalanced and nonimbalanced genes. We demonstrate that these results are consistent between the original data set and a second published data set in humans obtained using different technical and statistical methods. Finally, we show that variation in the single allelic imbalance-associated factor is partially explained by the density of genes in the region of a target gene (allelic imbalance is less probable for genes in gene-dense regions), and, to a lesser extent, the evenness of expression of the gene across tissues and the magnitude of negative selection on putative regulatory regions of the gene. These results suggest that the genomic distribution of functional cis-regulatory variants in the human genome is nonrandom, perhaps due to local differences in evolutionary

  19. Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

    Science.gov (United States)

    Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

    2018-06-01

    Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

    Energy Technology Data Exchange (ETDEWEB)

    Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)

    1993-07-01

    A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

  1. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

    International Nuclear Information System (INIS)

    Bornholdt, S.

    1993-07-01

    A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback

  2. Neural networks for predicting breeding values and genetic gains

    Directory of Open Access Journals (Sweden)

    Gabi Nunes Silva

    2014-12-01

    Full Text Available Analysis using Artificial Neural Networks has been described as an approach in the decision-making process that, although incipient, has been reported as presenting high potential for use in animal and plant breeding. In this study, we introduce the procedure of using the expanded data set for training the network. Wealso proposed using statistical parameters to estimate the breeding value of genotypes in simulated scenarios, in addition to the mean phenotypic value in a feed-forward back propagation multilayer perceptron network. After evaluating artificial neural network configurations, our results showed its superiority to estimates based on linear models, as well as its applicability in the genetic value prediction process. The results further indicated the good generalization performance of the neural network model in several additional validation experiments.

  3. Reliable prediction of adsorption isotherms via genetic algorithm molecular simulation.

    Science.gov (United States)

    LoftiKatooli, L; Shahsavand, A

    2017-01-01

    Conventional molecular simulation techniques such as grand canonical Monte Carlo (GCMC) strictly rely on purely random search inside the simulation box for predicting the adsorption isotherms. This blind search is usually extremely time demanding for providing a faithful approximation of the real isotherm and in some cases may lead to non-optimal solutions. A novel approach is presented in this article which does not use any of the classical steps of the standard GCMC method, such as displacement, insertation, and removal. The new approach is based on the well-known genetic algorithm to find the optimal configuration for adsorption of any adsorbate on a structured adsorbent under prevailing pressure and temperature. The proposed approach considers the molecular simulation problem as a global optimization challenge. A detailed flow chart of our so-called genetic algorithm molecular simulation (GAMS) method is presented, which is entirely different from traditions molecular simulation approaches. Three real case studies (for adsorption of CO 2 and H 2 over various zeolites) are borrowed from literature to clearly illustrate the superior performances of the proposed method over the standard GCMC technique. For the present method, the average absolute values of percentage errors are around 11% (RHO-H 2 ), 5% (CHA-CO 2 ), and 16% (BEA-CO 2 ), while they were about 70%, 15%, and 40% for the standard GCMC technique, respectively.

  4. Ternary alloy material prediction using genetic algorithm and cluster expansion

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Chong [Iowa State Univ., Ames, IA (United States)

    2015-12-01

    This thesis summarizes our study on the crystal structures prediction of Fe-V-Si system using genetic algorithm and cluster expansion. Our goal is to explore and look for new stable compounds. We started from the current ten known experimental phases, and calculated formation energies of those compounds using density functional theory (DFT) package, namely, VASP. The convex hull was generated based on the DFT calculations of the experimental known phases. Then we did random search on some metal rich (Fe and V) compositions and found that the lowest energy structures were body centered cube (bcc) underlying lattice, under which we did our computational systematic searches using genetic algorithm and cluster expansion. Among hundreds of the searched compositions, thirteen were selected and DFT formation energies were obtained by VASP. The stability checking of those thirteen compounds was done in reference to the experimental convex hull. We found that the composition, 24-8-16, i.e., Fe3VSi2 is a new stable phase and it can be very inspiring to the future experiments.

  5. Characterizing dispersal patterns in a threatened seabird with limited genetic structure

    NARCIS (Netherlands)

    Hall, Laurie A.; Palsboll, Per J.; Beissinger, Steven R.; Harvey, James T.; Berube, Martine; Raphael, Martin G.; Nelson, S. Kim; Golightly, Richard T.; Mcfarlane-Tranquilla, Laura; Newman, Scott H.; Peery, M. Zachariah

    2009-01-01

    Genetic assignment methods provide an appealing approach for characterizing dispersal patterns on ecological time scales, but require sufficient genetic differentiation to accurately identify migrants and a large enough sample size of migrants to, for example, compare dispersal between sexes or age

  6. Global patterns and predictions of seafloor biomass using random forests.

    Directory of Open Access Journals (Sweden)

    Chih-Lin Wei

    Full Text Available A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM, seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes. Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

  7. Disappearing scales in carps: re-visiting Kirpichnikov's model on the genetics of scale pattern formation.

    Directory of Open Access Journals (Sweden)

    Laura Casas

    Full Text Available The body of most fishes is fully covered by scales that typically form tight, partially overlapping rows. While some of the genes controlling the formation and growth of fish scales have been studied, very little is known about the genetic mechanisms regulating scale pattern formation. Although the existence of two genes with two pairs of alleles (S&s and N&n regulating scale coverage in cyprinids has been predicted by Kirpichnikov and colleagues nearly eighty years ago, their identity was unknown until recently. In 2009, the 'S' gene was found to be a paralog of fibroblast growth factor receptor 1, fgfr1a1, while the second gene called 'N' has not yet been identified. We re-visited the original model of Kirpichnikov that proposed four major scale pattern types and observed a high degree of variation within the so-called scattered phenotype due to which this group was divided into two sub-types: classical mirror and irregular. We also analyzed the survival rates of offspring groups and found a distinct difference between Asian and European crosses. Whereas nude × nude crosses involving at least one parent of Asian origin or hybrid with Asian parent(s showed the 25% early lethality predicted by Kirpichnikov (due to the lethality of the NN genotype, those with two Hungarian nude parents did not. We further extended Kirpichnikov's work by correlating changes in phenotype (scale-pattern to the deformations of fins and losses of pharyngeal teeth. We observed phenotypic changes which were not restricted to nudes, as described by Kirpichnikov, but were also present in mirrors (and presumably in linears as well; not analyzed in detail here. We propose that the gradation of phenotypes observed within the scattered group is caused by a gradually decreasing level of signaling (a dose-dependent effect probably due to a concerted action of multiple pathways involved in scale formation.

  8. Disappearing scales in carps: Re-visiting Kirpichnikov's model on the genetics of scale pattern formation

    KAUST Repository

    Casas, Laura; Szűcs, Ré ka; Vij, Shubha; Goh, Chin Heng; Kathiresan, Purushothaman; Né meth, Sá ndor; Jeney, Zsigmond; Bercsé nyi, Mikló s; Orbá n, Lá szló

    2013-01-01

    The body of most fishes is fully covered by scales that typically form tight, partially overlapping rows. While some of the genes controlling the formation and growth of fish scales have been studied, very little is known about the genetic mechanisms regulating scale pattern formation. Although the existence of two genes with two pairs of alleles (S&s and N&n) regulating scale coverage in cyprinids has been predicted by Kirpichnikov and colleagues nearly eighty years ago, their identity was unknown until recently. In 2009, the 'S' gene was found to be a paralog of fibroblast growth factor receptor 1, fgfr1a1, while the second gene called 'N' has not yet been identified. We re-visited the original model of Kirpichnikov that proposed four major scale pattern types and observed a high degree of variation within the so-called scattered phenotype due to which this group was divided into two sub-types: classical mirror and irregular. We also analyzed the survival rates of offspring groups and found a distinct difference between Asian and European crosses. Whereas nude x nude crosses involving at least one parent of Asian origin or hybrid with Asian parent(s) showed the 25% early lethality predicted by Kirpichnikov (due to the lethality of the NN genotype), those with two Hungarian nude parents did not. We further extended Kirpichnikov's work by correlating changes in phenotype (scale-pattern) to the deformations of fins and losses of pharyngeal teeth. We observed phenotypic changes which were not restricted to nudes, as described by Kirpichnikov, but were also present in mirrors (and presumably in linears as well; not analyzed in detail here). We propose that the gradation of phenotypes observed within the scattered group is caused by a gradually decreasing level of signaling (a dosedependent effect) probably due to a concerted action of multiple pathways involved in scale formation. 2013 Casas et al.

  9. Disappearing scales in carps: Re-visiting Kirpichnikov's model on the genetics of scale pattern formation

    KAUST Repository

    Casas, Laura

    2013-12-30

    The body of most fishes is fully covered by scales that typically form tight, partially overlapping rows. While some of the genes controlling the formation and growth of fish scales have been studied, very little is known about the genetic mechanisms regulating scale pattern formation. Although the existence of two genes with two pairs of alleles (S&s and N&n) regulating scale coverage in cyprinids has been predicted by Kirpichnikov and colleagues nearly eighty years ago, their identity was unknown until recently. In 2009, the \\'S\\' gene was found to be a paralog of fibroblast growth factor receptor 1, fgfr1a1, while the second gene called \\'N\\' has not yet been identified. We re-visited the original model of Kirpichnikov that proposed four major scale pattern types and observed a high degree of variation within the so-called scattered phenotype due to which this group was divided into two sub-types: classical mirror and irregular. We also analyzed the survival rates of offspring groups and found a distinct difference between Asian and European crosses. Whereas nude x nude crosses involving at least one parent of Asian origin or hybrid with Asian parent(s) showed the 25% early lethality predicted by Kirpichnikov (due to the lethality of the NN genotype), those with two Hungarian nude parents did not. We further extended Kirpichnikov\\'s work by correlating changes in phenotype (scale-pattern) to the deformations of fins and losses of pharyngeal teeth. We observed phenotypic changes which were not restricted to nudes, as described by Kirpichnikov, but were also present in mirrors (and presumably in linears as well; not analyzed in detail here). We propose that the gradation of phenotypes observed within the scattered group is caused by a gradually decreasing level of signaling (a dosedependent effect) probably due to a concerted action of multiple pathways involved in scale formation. 2013 Casas et al.

  10. Genetic risk prediction and neurobiological understanding of alcoholism

    Science.gov (United States)

    Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B

    2014-01-01

    We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse

  11. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

    DEFF Research Database (Denmark)

    Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S

    2018-01-01

    Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns...... the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes...... in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely...

  12. Regional genetic diversity patterns in Antarctic hairgrass (Deschampsia antartica Desv.)

    NARCIS (Netherlands)

    van de Wouw, M.J.; Van Dijk, P.J.; Huiskes, A.H.L.

    2008-01-01

    Aim To determine patterns in diversity of a major Antarctic plant species, including relationships of Antarctic populations with those outside the Antarctic zone. Location Antarctic Peninsula, Maritime Antarctica, sub-Antarctic islands, Falkland Islands and South America. Methods Amplified fragment

  13. Modelling and predicting biogeographical patterns in river networks

    Directory of Open Access Journals (Sweden)

    Sabela Lois

    2016-04-01

    Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

  14. Scientific reporting is suboptimal for aspects that characterize genetic risk prediction studies: a review of published articles based on the Genetic RIsk Prediction Studies statement.

    Science.gov (United States)

    Iglesias, Adriana I; Mihaescu, Raluca; Ioannidis, John P A; Khoury, Muin J; Little, Julian; van Duijn, Cornelia M; Janssens, A Cecile J W

    2014-05-01

    Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement. We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted. Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model. Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Cortical activity patterns predict robust speech discrimination ability in noise

    Science.gov (United States)

    Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

    2012-01-01

    The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

  16. Elevational patterns of genetic variation in the cosmopolitan moss Bryum argenteum (Bryaceae).

    Science.gov (United States)

    Pisa, Sergio; Werner, Olaf; Vanderpoorten, Alain; Magdy, Mahmoud; Ros, Rosa M

    2013-10-01

    The Baas Becking tenet posits that 'everything is everywhere, but the environment selects' to explain cosmopolitan distributions in highly vagile taxa. Bryophyte species show wider distributions than vascular plants and include examples of truly cosmopolitan ranges, which have been interpreted as a result of high dispersal capacities and ecological plasticity. In the current study, we documented patterns of genetic structure and diversity in the cosmopolitan moss Bryum argenteum along an elevational gradient to determine if genetic diversity and structure is homogenized by intense migrations in the lack of ecological differentiation. • 60 specimens were collected in the Sierra Nevada Mountains (Spain) between 100 and 2870 m and sequenced for ITS and rps4. Comparative analyses, genetic diversity estimators, and Mantel's tests were employed to determine the relationship between genetic variation, elevation, and geographic distance and to look for signs of demographic shifts. • Genetic diversity peaked above 1900 m and no signs of demographic shifts were detected at any elevation. There was a strong phylogenetic component in elevational variation. Genetic variation was significantly correlated with elevation, but not with geographic distance. • The results point to the long-term persistence of Bryum argenteum in a range that was glaciated during the Late Pleistocene. Evidence for an environmentally driven pattern of genetic differentiation suggests adaptive divergence. This supports the Baas Becking tenet and indicates that ecological specialization might play a key role in explaining patterns of genetic structure in cosmopolitan mosses.

  17. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

    Directory of Open Access Journals (Sweden)

    Chu Annie TW

    2010-06-01

    Full Text Available Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Results - Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 ± 9.2 years from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%, recovery (0% and 4.3%, delayed dysfunction (13% and 15.9% and resilience (76.8% and 66.7%. Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant

  18. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study.

    Science.gov (United States)

    Ho, Samuel M Y; Ho, Judy W C; Bonanno, George A; Chu, Annie T W; Chan, Emily M S

    2010-06-11

    Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline) and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 +/- 9.2 years) from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%), recovery (0% and 4.3%), delayed dysfunction (13% and 15.9%) and resilience (76.8% and 66.7%). Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression) were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant predictor of a resilience outcome trajectory for depression

  19. Genetic patterns of Streptococcus uberis isolated from bovine mastitis

    Directory of Open Access Journals (Sweden)

    Elina B Reinoso

    2015-06-01

    Full Text Available The aim of this study was to evaluate the genotypic relationships among 40 Streptococcus uberis isolated from bovine mastitis by using pulsed-field gel electrophoresis (PFGE. Additionally, the association between PFGE patterns and virulence profiles was investigated. The isolates exhibited 17 PFGE patterns. Different strains were found within and among herds; however, a low number of isolates within the same herd shared an identical PFGE type. No association between PFGE patterns and virulence profiles was found. However, the detection of specific strains in some herds could indicate that some strains are more virulent than others. Further research needs to be undertaken to elucidate new virulence-associated genes that might contribute to the capability of these strains to produce infection.

  20. Genetic patterns of Streptococcus uberis isolated from bovine mastitis.

    Science.gov (United States)

    Reinoso, Elina B; Lasagno, Mirta C; Odierno, Liliana M

    2015-01-01

    The aim of this study was to evaluate the genotypic relationships among 40 Streptococcus uberis isolated from bovine mastitis by using pulsed-field gel electrophoresis (PFGE). Additionally, the association between PFGE patterns and virulence profiles was investigated. The isolates exhibited 17 PFGE patterns. Different strains were found within and among herds; however, a low number of isolates within the same herd shared an identical PFGE type. No association between PFGE patterns and virulence profiles was found. However, the detection of specific strains in some herds could indicate that some strains are more virulent than others. Further research needs to be undertaken to elucidate new virulence-associated genes that might contribute to the capability of these strains to produce infection. Copyright © 2014 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

  1. Anthropogenic fragmentation may not alter pre-existing patterns of genetic diversity and differentiation in perennial shrubs.

    Science.gov (United States)

    Llorens, Tanya M; Ayre, David J; Whelan, Robert J

    2018-04-01

    Many plant species have pollination and seed dispersal systems and evolutionary histories that have produced strong genetic structuring. These genetic patterns may be consistent with expectations following recent anthropogenic fragmentation, making it difficult to detect fragmentation effects if no prefragmentation genetic data are available. We used microsatellite markers to investigate whether severe habitat fragmentation may have affected the structure and diversity of populations of the endangered Australian bird-pollinated shrub Grevillea caleyi R.Br., by comparing current patterns of genetic structure and diversity with those of the closely related G. longifolia R.Br. that has a similar life history but has not experienced anthropogenic fragmentation. Grevillea caleyi and G. longifolia showed similar and substantial population subdivision at all spatial levels (global F' ST  = 0.615 and 0.454; S p  = 0.039 and 0.066), marked isolation by distance and large heterozygous deficiencies. These characteristics suggest long-term effects of inbreeding in self-compatible species that have poor seed dispersal, limited connectivity via pollen flow and undergo population bottlenecks because of periodic fires. Highly structured allele size distributions, most notably in G. caleyi, imply historical processes of drift and mutation were important in isolated subpopulations. Genetic diversity did not vary with population size but was lower in more isolated populations for both species. Through this comparison, we reject the hypothesis that anthropogenic fragmentation has impacted substantially on the genetic composition or structure of G. caleyi populations. Our results suggest that highly self-compatible species with limited dispersal may be relatively resilient to the genetic changes predicted to follow habitat fragmentation. © 2018 John Wiley & Sons Ltd.

  2. Analyzing and Predicting Micro-Location Patterns of Software Firms

    Directory of Open Access Journals (Sweden)

    Jan Kinne

    2017-12-01

    Full Text Available While the effects of non-geographic aggregation on statistical inference are well studied in economics, research on the effects of geographic aggregation on regression analysis is rather scarce. This knowledge gap, together with the use of aggregated spatial units in previous firm location studies, results in a lack of understanding of firm location determinants at the microgeographic level. Suitable data for microgeographic location analysis has become available only recently through the emergence of Volunteered Geographic Information (VGI, especially the OpenStreetMap (OSM project, and the increasing availability of official (open geodata. In this paper, we use a comprehensive dataset of three million street-level geocoded firm observations to explore the location pattern of software firms in an Exploratory Spatial Data Analysis (ESDA. Based on the ESDA results, we develop a software firm location prediction model using Poisson regression and OSM data. Our findings offer novel insights into the mode of operation of the Modifiable Areal Unit Problem (MAUP in the context of a microgeographic location analysis: We find that non-aggregated data can be used to detect information on location determinants, which are superimposed when aggregated spatial units are analyzed, and that some findings of previous firm location studies are not robust at the microgeographic level. However, we also conclude that the lack of high-resolution geodata on socio-economic population characteristics causes systematic prediction errors, especially in cities with diverse and segregated populations.

  3. Phenotype prediction using regularized regression on genetic data in the DREAM5 Systems Genetics B Challenge.

    Directory of Open Access Journals (Sweden)

    Po-Ru Loh

    Full Text Available A major goal of large-scale genomics projects is to enable the use of data from high-throughput experimental methods to predict complex phenotypes such as disease susceptibility. The DREAM5 Systems Genetics B Challenge solicited algorithms to predict soybean plant resistance to the pathogen Phytophthora sojae from training sets including phenotype, genotype, and gene expression data. The challenge test set was divided into three subcategories, one requiring prediction based on only genotype data, another on only gene expression data, and the third on both genotype and gene expression data. Here we present our approach, primarily using regularized regression, which received the best-performer award for subchallenge B2 (gene expression only. We found that despite the availability of 941 genotype markers and 28,395 gene expression features, optimal models determined by cross-validation experiments typically used fewer than ten predictors, underscoring the importance of strong regularization in noisy datasets with far more features than samples. We also present substantial analysis of the training and test setup of the challenge, identifying high variance in performance on the gold standard test sets.

  4. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

    Science.gov (United States)

    Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

    2018-06-01

    Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

  5. Narcissism predicts impulsive buying: phenotypic and genetic evidence

    Science.gov (United States)

    Cai, Huajian; Shi, Yuanyuan; Fang, Xiang; Luo, Yu L. L.

    2015-01-01

    Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In Study 1, we surveyed an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating 304 twin pairs, Study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship. PMID:26217251

  6. Narcissism predicts impulsive buying: phenotypic and genetic evidence.

    Science.gov (United States)

    Cai, Huajian; Shi, Yuanyuan; Fang, Xiang; Luo, Yu L L

    2015-01-01

    Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In Study 1, we surveyed an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating 304 twin pairs, Study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship.

  7. Flow discharge prediction in compound channels using linear genetic programming

    Science.gov (United States)

    Azamathulla, H. Md.; Zahiri, A.

    2012-08-01

    SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

  8. Narcissism predicts impulsive buying: phenotypic and genetic evidence

    Directory of Open Access Journals (Sweden)

    Huajian eCai

    2015-07-01

    Full Text Available Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In study 1, we surveyed narcissism and the impulsive buying tendency among an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating narcissism and the impulsive buying tendency in 304 twin pairs, study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship.

  9. Recombination in diverse maize is stable, predictable, and associated with genetic load.

    Science.gov (United States)

    Rodgers-Melnick, Eli; Bradbury, Peter J; Elshire, Robert J; Glaubitz, Jeffrey C; Acharya, Charlotte B; Mitchell, Sharon E; Li, Chunhui; Li, Yongxiang; Buckler, Edward S

    2015-03-24

    Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.

  10. Using human genetics to predict the effects and side-effects of drugs

    DEFF Research Database (Denmark)

    Stender, Stefan; Tybjærg-Hansen, Anne

    2016-01-01

    PURPOSE OF REVIEW: 'Genetic proxies' are increasingly being used to predict the effects of drugs. We present an up-to-date overview of the use of human genetics to predict effects and adverse effects of lipid-targeting drugs. RECENT FINDINGS: LDL cholesterol lowering variants in HMG-Coenzyme A re...

  11. Patterns, incidence and predictive factors for pain after interventional radiology

    International Nuclear Information System (INIS)

    England, A.; Tam, C.L.; Thacker, D.E.; Walker, A.L.; Parkinson, A.S.; DeMello, W.; Bradley, A.J.; Tuck, J.S.; Laasch, H.-U.; Butterfield, J.S.; Ashleigh, R.J.; England, R.E.; Martin, D.F.

    2005-01-01

    AIM: To evaluate prospectively the pattern, severity and predictive factors of pain after interventional radiological procedures. MATERIALS AND METHODS: All patients undergoing non-arterial radiological interventional procedures were assessed using a visual-analogue scale (VAS) for pain before and at regular intervals for 24 h after their procedure. RESULTS: One hundred and fifty patients (87 men, mean age 62 years, range 18-92 years) were entered into the study. Significant increases in VAS score occurred 8 h after percutaneous biliary procedures (+47.7 mm, SD 14.9 mm; p=0.001), 6 h after central venous access and gastrostomy insertion (+23.7 mm, SD 19.5 mm; p=0.001 and +28.4 mm, SD 9.7 mm; p=0.007, respectively) and 4 h after oesophageal stenting (+27.8 mm, SD 20.2 mm, p=0.001). Non-significant increases in VAS pain score were observed after duodenal and colonic stenting (duodenal: +5.13 mm, SD 7.47 mm; p=0.055, colonic: +23.3 mm, SD 13.10 mm, p=0.250) at a mean of 5 h (range 4-6 h). Patients reported a significant reduction in pain score for nephrostomy insertion (-28.4 mm, SD 7.11 mm, p=0.001). Post-procedural analgesia was required in 99 patients (69.2%), 40 (28.0%) requiring opiates. Maximum post-procedural VAS pain score was significantly higher in patients who had no pre-procedural analgesia (p=0.003). CONCLUSION: Post-procedural pain is common and the pattern and severity of pain between procedures is variable. Pain control after interventional procedures is often inadequate, and improvements in pain management are required

  12. Investigation on the improvement of genetic algorithm for PWR loading pattern search and its benchmark verification

    International Nuclear Information System (INIS)

    Li Qianqian; Jiang Xiaofeng; Zhang Shaohong

    2009-01-01

    In this study, the age technique, the concepts of relativeness degree and worth function are exploited to improve the performance of genetic algorithm (GA) for PWR loading pattern search. Among them, the age technique endows the algorithm be capable of learning from previous search 'experience' and guides it to do a better search in the vicinity ora local optimal; the introduction of the relativeness degree checks the relativeness of two loading patterns before performing crossover between them, which can significantly reduce the possibility of prematurity of the algorithm; while the application of the worth function makes the algorithm be capable of generating new loading patterns based on the statistics of common features of evaluated good loading patterns. Numerical verification against a loading pattern search benchmark problem ora two-loop reactor demonstrates that the adoption of these techniques is able to significantly enhance the efficiency of the genetic algorithm while improves the quality of the final solution as well. (authors)

  13. Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

    Science.gov (United States)

    Chen, Chia-Jeng; Lee, Tsung-Yu

    2017-04-01

    Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping

  14. Climatic extremes improve predictions of spatial patterns of tree species

    Science.gov (United States)

    Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

    2009-01-01

    Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

  15. Adult Attachment Interview Discourse Patterns Predict Metabolic Syndrome in Midlife

    Science.gov (United States)

    Davis, Cynthia R.; Usher, Nicole; Dearing, Eric; Barkai, Ayelet R.; Crowell-Doom, Cindy; Mantzoros, Christos S.; Crowell, Judith A.

    2017-01-01

    Objective Adult attachment discourse patterns and current family relationship quality were examined as predictors of health behaviors and number of Metabolic Syndrome (MetS) criteria met. Methods A sample of 215 White/European American and Black/African American adults, aged 35 to 55, were examined cross-sectionally. Discourse was assessed with the Adult Attachment Interview (AAI), specifically: 1) coherence, a marker of attachment security, 2) unresolved trauma/loss, a marker of disorganized and distorted cognition related to trauma, and 3) idealization, the tendency to minimize the impact of stressful experiences. Health behaviors of diet, exercise, smoking and alcohol use were also assessed, as were adverse childhood experiences, current depressive symptoms and relationship functioning. MetS includes hypertension, hyperglycemia, high triglycerides, low HDL cholesterol, and obesity. Results Using path analysis and accounting for childhood adversity and depressive symptoms, AAI coherence and unresolved trauma or loss were directly linked to number of MetS criteria met (β = −.22 and .21 respectively). Idealization was indirectly linked to MetS through poor diet (β = −.26 and −.36 respectively), predicting 21% of the variance in number of MetS criteria met. Conclusions Attachment representations related to stress appraisal and care-seeking behaviors appear to serve as cognitive mechanisms increasing risk of MetS. PMID:25264975

  16. Genetic structuring and migration patterns of Atlantic bigeye tuna, Thunnus obesus (Lowe, 1839)

    OpenAIRE

    Gonzalez, Elena G; Beerli, Peter; Zardoya, Rafael

    2008-01-01

    Abstract Background Large pelagic fishes are generally thought to have little population genetic structuring based on their cosmopolitan distribution, large population sizes and high dispersal capacities. However, gene flow can be influenced by ecological (e.g. homing behaviour) and physical (e.g. present-day ocean currents, past changes in sea temperature and levels) factors. In this regard, Atlantic bigeye tuna shows an interesting genetic structuring pattern with two highly divergent mitoc...

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

    Directory of Open Access Journals (Sweden)

    Yiming Hu

    2017-06-01

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

  18. Postglacial recolonization in a cold climate specialist in western Europe: patterns of genetic diversity in the adder (Vipera berus) support the central-marginal hypothesis.

    Science.gov (United States)

    Ursenbacher, Sylvain; Guillon, Michaël; Cubizolle, Hervé; Dupoué, Andréaz; Blouin-Demers, Gabriel; Lourdais, Olivier

    2015-07-01

    Understanding the impact of postglacial recolonization on genetic diversity is essential in explaining current patterns of genetic variation. The central-marginal hypothesis (CMH) predicts a reduction in genetic diversity from the core of the distribution to peripheral populations, as well as reduced connectivity between peripheral populations. While the CMH has received considerable empirical support, its broad applicability is still debated and alternative hypotheses predict different spatial patterns of genetic diversity. Using microsatellite markers, we analysed the genetic diversity of the adder (Vipera berus) in western Europe to reconstruct postglacial recolonization. Approximate Bayesian Computation (ABC) analyses suggested a postglacial recolonization from two routes: a western route from the Atlantic Coast up to Belgium and a central route from the Massif Central to the Alps. This cold-adapted species likely used two isolated glacial refugia in southern France, in permafrost-free areas during the last glacial maximum. Adder populations further from putative glacial refugia had lower genetic diversity and reduced connectivity; therefore, our results support the predictions of the CMH. Our study also illustrates the utility of highly variable nuclear markers, such as microsatellites, and ABC to test competing recolonization hypotheses. © 2015 John Wiley & Sons Ltd.

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  20. Genetic liability for schizophrenia predicts risk of immune disorders

    NARCIS (Netherlands)

    Stringer, Sven; Kahn, René S.; de Witte, Lot D.; Ophoff, Roel A.; Derks, Eske M.

    2014-01-01

    Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between

  1. Genetic liability for schizophrenia predicts risk of immune disorders

    NARCIS (Netherlands)

    Stringer, Sven; Kahn, René S; de Witte, Lot D; Ophoff, Roel A; Derks, Eske M

    2014-01-01

    BACKGROUND: Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap

  2. Neuroblastoma: morphological pattern, molecular genetic features, and prognostic factors

    Directory of Open Access Journals (Sweden)

    A. M. Stroganova

    2016-01-01

    Full Text Available Neuroblastoma, the most common extracranial tumor of childhood, arises from the developing neurons of the sympathetic nervous system (neural cress stem cells and has various biological and clinical characteristics. The mean age at disease onset is 18 months. Neuroblastoma has a number of unique characteristics: a capacity for spontaneous regression in babies younger than 12 months even in the presence of distant metastases, for differentiation (maturation into ganglioneuroma in infants after the first year of life, and for swift aggressive development and rapid metastasis. There are 2 clinical classifications of neuroblastoma: the International neuroblastoma staging system that is based on surgical results and the International Neuroblastoma Risk Group Staging System. One of the fundamentally important problems for the clinical picture of neuroblastoma is difficulties making its prognosis. Along with clinical parameters (a patient’s age, tumor extent and site, some histological, molecular biochemical (ploidy and genetic (chromosomal aberrations, MYCN gene status, deletion of the locus 1p36 and 11q, the longer arm of chromosome 17, etc. characteristics of tumor cells are of considerable promise. MYCN gene amplification is observed in 20–30 % of primary neuroblastomas and it is one of the major indicators of disease aggressiveness, early chemotherapy resistance, and a poor prognosis. There are 2 types of MYCN gene amplification: extrachromosomal (double acentric chromosomes and intrachromosomal (homogenically painted regions. Examination of double acentric chromosomes revealed an interesting fact that it may be eliminated (removed from the nucleus through the formation of micronuclei. MYCN oncogene amplification is accompanied frequently by 1p36 locus deletion and longer 17q arm and less frequently by 11q23 deletion; these are poor prognostic factors for the disease. The paper considers in detail the specific, unique characteristics of the

  3. Firefighter burn injuries: predictable patterns influenced by turnout gear.

    Science.gov (United States)

    Kahn, Steven A; Patel, Jignesh H; Lentz, Christopher W; Bell, Derek E

    2012-01-01

    /liquid entered the gear via gaps in the sleeve or face mask. Three patients (15%) received injury due to removal/dislodging of their safety equipment, two patients (10%) suffered their injuries during training exercises when they were not wearing their safety equipment, and the final patient (5%) received burns due to sweat evaporation. Firefighter burn injuries occur to predictable anatomic sites with common injury patterns. Modification and optimization of gear to eliminate gaps that allow steam/hot liquid entry may decrease burn injury. Improving education regarding the use of protective equipment may also be beneficial.

  4. Robust dynamical pattern formation from a multifunctional minimal genetic circuit

    Directory of Open Access Journals (Sweden)

    Carrera Javier

    2010-04-01

    Full Text Available Abstract Background A practical problem during the analysis of natural networks is their complexity, thus the use of synthetic circuits would allow to unveil the natural mechanisms of operation. Autocatalytic gene regulatory networks play an important role in shaping the development of multicellular organisms, whereas oscillatory circuits are used to control gene expression under variable environments such as the light-dark cycle. Results We propose a new mechanism to generate developmental patterns and oscillations using a minimal number of genes. For this, we design a synthetic gene circuit with an antagonistic self-regulation to study the spatio-temporal control of protein expression. Here, we show that our minimal system can behave as a biological clock or memory, and it exhibites an inherent robustness due to a quorum sensing mechanism. We analyze this property by accounting for molecular noise in an heterogeneous population. We also show how the period of the oscillations is tunable by environmental signals, and we study the bifurcations of the system by constructing different phase diagrams. Conclusions As this minimal circuit is based on a single transcriptional unit, it provides a new mechanism based on post-translational interactions to generate targeted spatio-temporal behavior.

  5. Technology assessment and resource allocation for predictive genetic testing: A study of the perspectives of Canadian genetic health care providers

    Directory of Open Access Journals (Sweden)

    Einsiedel Edna

    2009-06-01

    Full Text Available Abstract Background With a growing number of genetic tests becoming available to the health and consumer markets, genetic health care providers in Canada are faced with the challenge of developing robust decision rules or guidelines to allocate a finite number of public resources. The objective of this study was to gain Canadian genetic health providers' perspectives on factors and criteria that influence and shape resource allocation decisions for publically funded predictive genetic testing in Canada. Methods The authors conducted semi-structured interviews with 16 senior lab directors and clinicians at publically funded Canadian predictive genetic testing facilities. Participants were drawn from British Columbia, Alberta, Manitoba, Ontario, Quebec and Nova Scotia. Given the community sampled was identified as being relatively small and challenging to access, purposive sampling coupled with snowball sampling methodologies were utilized. Results Surveyed lab directors and clinicians indicated that predictive genetic tests were funded provincially by one of two predominant funding models, but they themselves played a significant role in how these funds were allocated for specific tests and services. They also rated and identified several factors that influenced allocation decisions and patients' decisions regarding testing. Lastly, participants provided recommendations regarding changes to existing allocation models and showed support for a national evaluation process for predictive testing. Conclusion Our findings suggest that largely local and relatively ad hoc decision making processes are being made in relation to resource allocations for predictive genetic tests and that a more coordinated and, potentially, national approach to allocation decisions in this context may be appropriate.

  6. Patterns of ancestry and genetic diversity in reintroduced populations of the slimy sculpin: Implications for conservation

    Science.gov (United States)

    Huff, David D.; Miller, Loren M.; Vondracek, Bruce C.

    2010-01-01

    Reintroductions are a common approach for preserving intraspecific biodiversity in fragmented landscapes. However, they may exacerbate the reduction in genetic diversity initially caused by population fragmentation because the effective population size of reintroduced populations is often smaller and reintroduced populations also tend to be more geographically isolated than native populations. Mixing genetically divergent sources for reintroduction purposes is a practice intended to increase genetic diversity. We documented the outcome of reintroductions from three mixed sources on the ancestral composition and genetic variation of a North American fish, the slimy sculpin (Cottus cognatus). We used microsatellite markers to evaluate allelic richness and heterozygosity in the reintroduced populations relative to computer simulated expectations. Sculpins in reintroduced populations exhibited higher levels of heterozygosity and allelic richness than any single source, but only slightly higher than the single most genetically diverse source population. Simulations intended to mimic an ideal scenario for maximizing genetic variation in the reintroduced populations also predicted increases, but they were only moderately greater than the most variable source population. We found that a single source contributed more than the other two sources at most reintroduction sites. We urge caution when choosing whether to mix source populations in reintroduction programs. Genetic characteristics of candidate source populations should be evaluated prior to reintroduction if feasible. When combined with knowledge of the degree of genetic distinction among sources, simulations may allow the genetic diversity benefits of mixing populations to be weighed against the risks of outbreeding depression in reintroduced and nearby populations.

  7. Could the outcome of the 2016 US elections have been predicted from past voting patterns?

    CSIR Research Space (South Africa)

    Schmitz, Peter MU

    2017-07-01

    Full Text Available In South Africa, a team of analysts has for some years been using statistical techniques to predict election outcomes during election nights in South Africa. The prediction method involves using statistical clusters based on past voting patterns...

  8. Patterns of genetic diversity of local pig populations in the State of Pernambuco, Brazil

    Directory of Open Access Journals (Sweden)

    Elizabete Cristina da Silva

    2011-08-01

    Full Text Available This study estimated the genetic diversity and structure of 12 genetic groups (GG of locally adapted and specialized pigs in the state of Pernambuco using 22 microsatellite markers. Nine locally adapted breeds (Baé, Caruncho, Canastra, Canastrão, Mamelado, Moura, Nilo, Piau and UDB (Undefined Breed and 3 specialized breeds (Duroc, Landrace and Large White, totaling 190 animals, were analyzed. The Analysis of Molecular Variance (AMOVA showed that 3.2% of the total variation was due to differences between genetic groups, and 3.6% to differences between local and commercial pigs. One hundred and ninety eight alleles were identified and apart from the Large White breed, all GG presented Hardy-Weinberg Equilibrium deviations for some loci. The total and effective allele means were lower for Duroc (3.65 and 3.01 and higher for UDB (8.89 and 4.53 and Canastra (8.61 and 4.58. Using Nei's standard genetic distance and the UPGMA method, it was possible to observe that the Landrace breed was grouped with the local genetic groups Canastra, Moura, Canastrão, Baé and Caruncho. Due to the complex admixture pattern, the genetic variability of the 12 genetic groups can be analyzed by distributing the individuals into two populations as demonstrated by a Bayesian analysis, corroborating the results from AMOVA, which revealed a low level of genetic differentiation between the inferred populations.

  9. Genetic relatedness does not predict the queen's successors in the ...

    Indian Academy of Sciences (India)

    SAIKAT CHAKRABORTY

    2018-06-06

    Jun 6, 2018 ... 1Centre for Ecological Sciences, Indian Institute of Science, ... Ropalidia marginata is a social wasp in which colonies consist of a single .... Materials and methods .... Descriptive statistics about the genetic data were estimated.

  10. Metabolic Rate and Climatic Fluctuations Shape Continental Wide Pattern of Genetic Divergence and Biodiversity in Fishes

    Science.gov (United States)

    April, Julien; Hanner, Robert H.; Mayden, Richard L.; Bernatchez, Louis

    2013-01-01

    Taxonomically exhaustive and continent wide patterns of genetic divergence within and between species have rarely been described and the underlying evolutionary causes shaping biodiversity distribution remain contentious. Here, we show that geographic patterns of intraspecific and interspecific genetic divergence among nearly all of the North American freshwater fish species (>750 species) support a dual role involving both the late Pliocene-Pleistocene climatic fluctuations and metabolic rate in determining latitudinal gradients of genetic divergence and very likely influencing speciation rates. Results indicate that the recurrent glacial cycles caused global reduction in intraspecific diversity, interspecific genetic divergence, and species richness at higher latitudes. At the opposite, longer geographic isolation, higher metabolic rate increasing substitution rate and possibly the rapid accumulation of genetic incompatibilities, led to an increasing biodiversity towards lower latitudes. This indicates that both intrinsic and extrinsic factors similarly affect micro and macro evolutionary processes shaping global patterns of biodiversity distribution. These results also indicate that factors favouring allopatric speciation are the main drivers underlying the diversification of North American freshwater fishes. PMID:23922969

  11. Discordant patterns of genetic and phenotypic differentiation in five grasshopper species codistributed across a microreserve network.

    Science.gov (United States)

    Ortego, Joaquín; García-Navas, Vicente; Noguerales, Víctor; Cordero, Pedro J

    2015-12-01

    Conservation plans can be greatly improved when information on the evolutionary and demographic consequences of habitat fragmentation is available for several codistributed species. Here, we study spatial patterns of phenotypic and genetic variation among five grasshopper species that are codistributed across a network of microreserves but show remarkable differences in dispersal-related morphology (body size and wing length), degree of habitat specialization and extent of fragmentation of their respective habitats in the study region. In particular, we tested the hypothesis that species with preferences for highly fragmented microhabitats show stronger genetic and phenotypic structure than codistributed generalist taxa inhabiting a continuous matrix of suitable habitat. We also hypothesized a higher resemblance of spatial patterns of genetic and phenotypic variability among species that have experienced a higher degree of habitat fragmentation due to their more similar responses to the parallel large-scale destruction of their natural habitats. In partial agreement with our first hypothesis, we found that genetic structure, but not phenotypic differentiation, was higher in species linked to highly fragmented habitats. We did not find support for congruent patterns of phenotypic and genetic variability among any studied species, indicating that they show idiosyncratic evolutionary trajectories and distinctive demographic responses to habitat fragmentation across a common landscape. This suggests that conservation practices in networks of protected areas require detailed ecological and evolutionary information on target species to focus management efforts on those taxa that are more sensitive to the effects of habitat fragmentation. © 2015 John Wiley & Sons Ltd.

  12. Evaluation of Genetic Pattern of Non-Tuberculosis Mycobacterium Using VNTR Method

    Directory of Open Access Journals (Sweden)

    Noorozi J

    2011-06-01

    Full Text Available Background and Objectives: Epidemiological studies of Non-tuberculosis Mycobacterium is important because of the drug resistance pattern and worldwide dissemination of these organisms. One of genetic fingerprinting methods for epidemiological studies is VNTR (Variable Number Tandem Repeat. In this study genetic pattern of atypical Mycobacterium was evaluated by VNTR method for epidemiologic studies. Methods: 48 pulmonary and non pulmonary specimens separated from patients with the symptoms of pulmonary tuberculosis (PTB and identified as Non-tuberculosis Mycobacteriumby phenotypic and PCR-RFLP methods were selected for this study. Clinical samples and their standard strains were evaluated according to VNTR pattern using the 7 genetic loci including ETR-B. ETR-F. ETR-C. MPTR-A. ETR-A. ETR-E. ETR-D.Results: The results of VNTR method showed that none of the 7 loci had any polymorphism in the standard strains of atypical mycobacterium. Some of these variable number tandem repeat in 42 clinical samples of non-tuberculosis Mycobacterium were polymorphic while the PCR product (for any loci was not found in the remaining 6 specimens. Conclusion: Although the used genetic loci of this study were suitable for epidemiological studies of Mycobacterium tuberculosis, these loci were not able to determine the diversity of genetics of non-tuberculosis Mycobacterium Therefore, it seems necessary that other loci be studied using VNTR method.

  13. Genomic patterns in Acropora cervicornis show extensive population structure and variable genetic diversity.

    Science.gov (United States)

    Drury, Crawford; Schopmeyer, Stephanie; Goergen, Elizabeth; Bartels, Erich; Nedimyer, Ken; Johnson, Meaghan; Maxwell, Kerry; Galvan, Victor; Manfrino, Carrie; Lirman, Diego

    2017-08-01

    Threatened Caribbean coral communities can benefit from high-resolution genetic data used to inform management and conservation action. We use Genotyping by Sequencing (GBS) to investigate genetic patterns in the threatened coral, Acropora cervicornis , across the Florida Reef Tract (FRT) and the western Caribbean. Results show extensive population structure at regional scales and resolve previously unknown structure within the FRT. Different regions also exhibit up to threefold differences in genetic diversity (He), suggesting targeted management based on the goals and resources of each population is needed. Patterns of genetic diversity have a strong spatial component, and our results show Broward and the Lower Keys are among the most diverse populations in Florida. The genetic diversity of Caribbean staghorn coral is concentrated within populations and within individual reefs (AMOVA), highlighting the complex mosaic of population structure. This variance structure is similar over regional and local scales, which suggests that in situ nurseries are adequately capturing natural patterns of diversity, representing a resource that can replicate the average diversity of wild assemblages, serving to increase intraspecific diversity and potentially leading to improved biodiversity and ecosystem function. Results presented here can be translated into specific goals for the recovery of A. cervicornis , including active focus on low diversity areas, protection of high diversity and connectivity, and practical thresholds for responsible restoration.

  14. Increasing Prediction the Original Final Year Project of Student Using Genetic Algorithm

    Science.gov (United States)

    Saragih, Rijois Iboy Erwin; Turnip, Mardi; Sitanggang, Delima; Aritonang, Mendarissan; Harianja, Eva

    2018-04-01

    Final year project is very important forgraduation study of a student. Unfortunately, many students are not seriouslydidtheir final projects. Many of studentsask for someone to do it for them. In this paper, an application of genetic algorithms to predict the original final year project of a studentis proposed. In the simulation, the data of the final project for the last 5 years is collected. The genetic algorithm has several operators namely population, selection, crossover, and mutation. The result suggest that genetic algorithm can do better prediction than other comparable model. Experimental results of predicting showed that 70% was more accurate than the previous researched.

  15. Genetic variation patterns of American chestnut populations at EST-SSRs

    Science.gov (United States)

    Oliver Gailing; C. Dana Nelson

    2017-01-01

    The objective of this study is to analyze patterns of genetic variation at genic expressed sequence tag - simple sequence repeats (EST-SSRs) and at chloroplast DNA markers in populations of American chestnut (Castanea dentata Borkh.) to assist in conservation and breeding efforts. Allelic diversity at EST-SSRs decreased significantly from southwest to northeast along...

  16. Genetic associations for pathogen-specific clinical mastitis and patterns of peaks in somatic cell count

    NARCIS (Netherlands)

    Haas, de Y.; Barkema, H.W.; Schukken, Y.H.; Veerkamp, R.F.

    2003-01-01

    Genetic associations were estimated between pathogen-specific cases of clinical mastitis (CM), lactational average somatic cell score (LACSCS), and patterns of peaks in somatic cell count (SCC) which were based on deviations from the typical lactation curve for SCC. The dataset contained test-day

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

    Science.gov (United States)

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

  18. Bovine salmonellosis in Northeast of Iran: Frequency, genetic fingerprinting and antimicrobial resistance patterns of Salmonella spp.

    Directory of Open Access Journals (Sweden)

    Hessam A. Halimi

    2014-01-01

    Conclusion: The emergence of multiple antibiotic-resistant strains of Salmonella Typhimurium should be of great concern to the public. No correlation between ERIC fingerprinting and resistance patterns of Salmonella isolates was found, which indicates resistance to antimicrobial agents was not related to specific genetic background.

  19. Insecticide-driven patterns of genetic variation in the dengue vector Aedes aegypti in Martinique Island.

    Directory of Open Access Journals (Sweden)

    Sébastien Marcombe

    Full Text Available Effective vector control is currently challenged worldwide by the evolution of resistance to all classes of chemical insecticides in mosquitoes. In Martinique, populations of the dengue vector Aedes aegypti have been intensively treated with temephos and deltamethrin insecticides over the last fifty years, resulting in heterogeneous levels of resistance across the island. Resistance spreading depends on standing genetic variation, selection intensity and gene flow among populations. To determine gene flow intensity, we first investigated neutral patterns of genetic variability in sixteen populations representative of the many environments found in Martinique and experiencing various levels of insecticide pressure, using 6 microsatellites. Allelic richness was lower in populations resistant to deltamethrin, and consanguinity was higher in populations resistant to temephos, consistent with a negative effect of insecticide pressure on neutral genetic diversity. The global genetic differentiation was low, suggesting high gene flow among populations, but significant structure was found, with a pattern of isolation-by-distance at the global scale. Then, we investigated adaptive patterns of divergence in six out of the 16 populations using 319 single nucleotide polymorphisms (SNPs. Five SNP outliers displaying levels of genetic differentiation out of neutral expectations were detected, including the kdr-V1016I mutation in the voltage-gated sodium channel gene. Association tests revealed a total of seven SNPs associated with deltamethrin resistance. Six other SNPs were associated with temephos resistance, including two non-synonymous substitutions in an alkaline phosphatase and in a sulfotransferase respectively. Altogether, both neutral and adaptive patterns of genetic variation in mosquito populations appear to be largely driven by insecticide pressure in Martinique.

  20. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Science.gov (United States)

    Ober, Ulrike; Huang, Wen; Magwire, Michael; Schlather, Martin; Simianer, Henner; Mackay, Trudy F C

    2015-01-01

    The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  1. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Directory of Open Access Journals (Sweden)

    Ulrike Ober

    Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  2. Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural

    Science.gov (United States)

    Douglas, Karen M.; De Inocencio, Clara

    2017-01-01

    Abstract A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs. PMID:29695889

  3. Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural.

    Science.gov (United States)

    van Prooijen, Jan-Willem; Douglas, Karen M; De Inocencio, Clara

    2018-04-01

    A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs.

  4. The ties that bind: genetic relatedness predicts the fission and fusion of social groups in wild African elephants.

    Science.gov (United States)

    Archie, Elizabeth A; Moss, Cynthia J; Alberts, Susan C

    2006-03-07

    Many social animals live in stable groups. In contrast, African savannah elephants (Loxodonta africana) live in unusually fluid, fission-fusion societies. That is, 'core' social groups are composed of predictable sets of individuals; however, over the course of hours or days, these groups may temporarily divide and reunite, or they may fuse with other social groups to form much larger social units. Here, we test the hypothesis that genetic relatedness predicts patterns of group fission and fusion among wild, female African elephants. Our study of a single Kenyan population spans 236 individuals in 45 core social groups, genotyped at 11 microsatellite and one mitochondrial DNA (mtDNA) locus. We found that genetic relatedness predicted group fission; adult females remained with their first order maternal relatives when core groups fissioned temporarily. Relatedness also predicted temporary fusion between social groups; core groups were more likely to fuse with each other when the oldest females in each group were genetic relatives. Groups that shared mtDNA haplotypes were also significantly more likely to fuse than groups that did not share mtDNA. Our results suggest that associations between core social groups persist for decades after the original maternal kin have died. We discuss these results in the context of kin selection and its possible role in the evolution of elephant sociality.

  5. Hereditary melanoma and predictive genetic testing: why not?

    Science.gov (United States)

    Riedijk, S R; de Snoo, F A; van Dijk, S; Bergman, W; van Haeringen, A; Silberg, S; van Elderen, T M T; Tibben, A

    2005-09-01

    Since p16-Leiden presymptomatic testing for hereditary melanoma has become available in the Netherlands, the benefits and risks of offering such testing are evaluated. The current paper investigated why the non-participants were reluctant to participate in genetic testing. Sixty six eligible individuals, who were knowledgeable about the test but had not participated in genetic testing by January 2003, completed a self-report questionnaire assessing motivation, anxiety, family dynamics, risk knowledge and causal attributions. Non-participants reported anxiety levels below clinical significance. A principal components analysis on reasons for non-participation distinguished two underlying motives: emotional and rational motivation. Rational motivation for non-participation was associated with more accurate risk knowledge, the inclination to preselect mutation carriers within the family and lower scores on anxiety. Emotional motivation for non-participation was associated with disease misperceptions, hesitation to communicate unfavourable test results within the family and higher scores on anxiety. Rational and emotional motivation for non-participation in the genetic test for hereditary melanoma was found. Emotionally motivated individuals may be reluctant to disseminate genetic risk information. Rationally motivated individuals were better informed than emotionally motivated individuals. It is suggested that a leaflet is added to the invitation letter to enhance informed decision-making about genetic testing.

  6. Social interactions predict genetic diversification: an experimental manipulation in shorebirds.

    Science.gov (United States)

    Cunningham, Charles; Parra, Jorge E; Coals, Lucy; Beltrán, Marcela; Zefania, Sama; Székely, Tamás

    2018-01-01

    Mating strategy and social behavior influence gene flow and hence affect levels of genetic differentiation and potentially speciation. Previous genetic analyses of closely related plovers Charadrius spp. found strikingly different population genetic structure in Madagascar: Kittlitz's plovers are spatially homogenous whereas white-fronted plovers have well segregated and geographically distinct populations. Here, we test the hypotheses that Kittlitz's plovers are spatially interconnected and have extensive social interactions that facilitate gene flow, whereas white-fronted plovers are spatially discrete and have limited social interactions. By experimentally removing mates from breeding pairs and observing the movements of mate-searching plovers in both species, we compare the spatial behavior of Kittlitz's and white-fronted plovers within a breeding season. The behavior of experimental birds was largely consistent with expectations: Kittlitz's plovers travelled further, sought new mates in larger areas, and interacted with more individuals than white-fronted plovers, however there was no difference in breeding dispersal. These results suggest that mating strategies, through spatial behavior and social interactions, are predictors of gene flow and thus genetic differentiation and speciation. Our study highlights the importance of using social behavior to understand gene flow. However, further work is needed to investigate the relative importance of social structure, as well as intra- and inter-season dispersal, in influencing the genetic structures of populations.

  7. Performance evaluation of Genetic Algorithms on loading pattern optimization of PWRs

    International Nuclear Information System (INIS)

    Tombakoglu, M.; Bekar, K.B.; Erdemli, A.O.

    2001-01-01

    Genetic Algorithm (GA) based systems are used for search and optimization problems. There are several applications of GAs in literature successfully applied for loading pattern optimization problems. In this study, we have selected loading pattern optimization problem of Pressurised Water Reactor (PWR). The main objective of this work is to evaluate the performance of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection and construction of initial population and its size for PWR loading pattern optimization problems. The performance of GA with antithetic variates is compared to traditional GA. Antithetic variates are used to generate the initial population and its use with GA operators are also discussed. Finally, the results of multi-cycle optimization problems are discussed for objective function taking into account cycle burn-up and discharge burn-up.(author)

  8. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

    OpenAIRE

    Chu Annie TW; Bonanno George A; Ho Judy WC; Ho Samuel MY; Chan Emily MS

    2010-01-01

    Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer R...

  9. Family Conflict Interacts with Genetic Liability in Predicting Childhood and Adolescent Depression

    Science.gov (United States)

    Rice, Frances; Harold, Gordon T.; Shelton, Katherine H.; Thapar, Anita

    2006-01-01

    Objective: To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms…

  10. Prediction Center (CPC) Polar Eurasia Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Polar-Eurasia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  11. Climate Prediction Center (CPC) Pacific Transition Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Pacific Transition teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  12. Climate Prediction Center (CPC) East Atlantic Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the East Atlantic Teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  13. Prediction Center (CPC) Tropical/ Northern Hemisphere Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Tropical/ Northern Hemisphere teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated...

  14. Climate Prediction Center (CPC) West Pacific Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the West Pacific (WP) teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  15. Climate Prediction Center (CPC) Scandinavia Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Scandinavia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal component...

  16. The current and future use of ridge regression for prediction in quantitative genetics

    OpenAIRE

    Vlaming, Ronald; Groenen, Patrick

    2015-01-01

    textabstractIn recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i) the theoretical foundations of ridge regression, (ii) its link to...

  17. A study on effects of cash flow patterns and auditors’ opinions in predicting financial distress

    Directory of Open Access Journals (Sweden)

    Fatemeh Namvar

    2013-07-01

    Full Text Available Bankruptcy has been one of the most important issues among investors in stock market and there are literally different techniques for predicting bankruptcy. In this paper, we study on effects of cash flow patterns and auditors’ opinions in predicting financial distress on some 80 selected firms traded on Tehran Stock Exchange over the period 2005-2011. In this study, the combination of cash flow patterns represent firm’s resource allocations and operational capabilities interacted with their strategy choices. In additions, predictions about each individual cash flow components, operational, investment, financial, are derived from economic theory, which forms a basis for the life proxy. We use cash flow patterns in the decline stage and compare the results with auditors’ opinions. The results indicate that cash flow patterns could predict financial distress companies in Iran. In addition, the effective cash flow patterns in predicting financial distress is more than auditors’ feedbacks.

  18. Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Viranga Tilakaratna

    2017-09-01

    Full Text Available Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae, has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae, including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species.

  19. Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae.

    Science.gov (United States)

    Tilakaratna, Viranga; Bensasson, Douda

    2017-09-07

    Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae , has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae , including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species. Copyright © 2017 Tilakaratna and Bensasson.

  20. Genetic markers for prediction of normal tissue toxicity after radiotherapy

    DEFF Research Database (Denmark)

    Alsner, Jan; Andreassen, Christian Nicolaj; Overgaard, Jens

    2008-01-01

    During the last decade, a number of studies have supported the hypothesis that there is an important genetic component to the observed interpatient variability in normal tissue toxicity after radiotherapy. This review summarizes the candidate gene association studies published so far on the risk...

  1. Predictive genetic testing for cardiovascular diseases: Impact on carrier children

    NARCIS (Netherlands)

    Meulenkamp, Tineke M.; Tibben, Aad; Mollema, Eline D.; Van Langen, Irene M.; Wiegman, Albert; De Wert, Guido M.; De Beaufort, Inez D.; Wilde, Arthur A. M.; Smets, Ellen M. A.

    2008-01-01

    We studied the experiences of children identified by family screening who were found to be a mutation carrier for a genetic cardiovascular disease (Long QT Syndrome (LQTS), Hypertrophic Cardiomyopathy (HCM), Familial Hypercholesterolemia (FH)). We addressed the (a) manner in which they perceive

  2. Genetically Predicted Body Mass Index and Breast Cancer Risk

    DEFF Research Database (Denmark)

    Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou

    2016-01-01

    BACKGROUND: Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or enviro...

  3. Childhood socioeconomic status and longitudinal patterns of alcohol problems: Variation across etiological pathways in genetic risk.

    Science.gov (United States)

    Barr, Peter B; Silberg, Judy; Dick, Danielle M; Maes, Hermine H

    2018-05-14

    Childhood socioeconomic status (SES) is an important aspect of early life environment associated with later life health/health behaviors, including alcohol misuse. However, alcohol misuse is modestly heritable and involves differing etiological pathways. Externalizing disorders show significant genetic overlap with substance use, suggesting an impulsivity pathway to alcohol misuse. Alcohol misuse also overlaps with internalizing disorders, suggesting alcohol is used to cope. These differing pathways could lead to different patterns over time and/or differential susceptibility to environmental conditions, such as childhood SES. We examine whether: 1) genetic risk for externalizing and internalizing disorders influence trajectories of alcohol problems across adolescence to adulthood, 2) childhood SES alters genetic risk these disorders on trajectories of alcohol problems, and 3) these patterns are consistent across sex. We find modest evidence of gene-environment interaction. Higher childhood SES increases the risk of alcohol problems in late adolescence/early adulthood, while lower childhood SES increases the risk of alcohol problems in later adulthood, but only among males at greater genetic risk of externalizing disorders. Females from lower SES families with higher genetic risk of internalizing or externalizing disorders have greater risk of developing alcohol problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. Influence of ethnolinguistic diversity on the sorghum genetic patterns in subsistence farming systems in eastern Kenya.

    Directory of Open Access Journals (Sweden)

    Vanesse Labeyrie

    Full Text Available Understanding the effects of actions undertaken by human societies on crop evolution processes is a major challenge for the conservation of genetic resources. This study investigated the mechanisms whereby social boundaries associated with patterns of ethnolinguistic diversity have influenced the on-farm distribution of sorghum diversity. Social boundaries limit the diffusion of planting material, practices and knowledge, thus shaping crop diversity in situ. To assess the effect of social boundaries, this study was conducted in the contact zone between the Chuka, Mbeere and Tharaka ethnolinguistic groups in eastern Kenya. Sorghum varieties were inventoried and samples collected in 130 households. In all, 297 individual plants derived from seeds collected under sixteen variety names were characterized using a set of 18 SSR molecular markers and 15 morphological descriptors. The genetic structure was investigated using both a Bayesian assignment method and distance-based clustering. Principal Coordinates Analysis was used to describe the structure of the morphological diversity of the panicles. The distribution of the varieties and the main genetic clusters across ethnolinguistic groups was described using a non-parametric MANOVA and pairwise Fisher tests. The spatial distribution of landrace names and the overall genetic spatial patterns were significantly correlated with ethnolinguistic partition. However, the genetic structure inferred from molecular makers did not discriminate the short-cycle landraces despite their morphological distinctness. The cases of two improved varieties highlighted possible fates of improved materials. The most recent one was often given the name of local landraces. The second one, that was introduced a dozen years ago, displays traces of admixture with local landraces with differential intensity among ethnic groups. The patterns of congruence or discordance between the nomenclature of farmers' varieties and the

  5. Different protein-protein interface patterns predicted by different machine learning methods.

    Science.gov (United States)

    Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi

    2017-11-22

    Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

  6. Genetics and other factors in the aetiology of female pattern hair loss.

    Science.gov (United States)

    Redler, Silke; Messenger, Andrew G; Betz, Regina C

    2017-06-01

    Pattern hair loss is the most common form of hair loss in both women and men. Male pattern hair loss, also termed male androgenetic alopecia (M-AGA), is an androgen-dependent trait that is predominantly genetically determined. Androgen-mediated mechanisms are probably involved in female pattern hair loss (FPHL) in some women but the evidence is less strong than in M-AGA; other non-androgenic pathways, including environmental influences, may contribute to the aetiology. Genome-wide association studies have identified several genetic loci for M-AGA and have provided better insight into the underlying biology. However, the role of heritable factors in Female Pattern Hair Loss (FPHL) is largely unknown. Recently published studies have been restricted to candidate gene approaches and could not clearly identify any susceptibility locus/gene for FPHL but suggest that the aetiology differs substantially from that of M-AGA. Hypotheses about possible pathomechanisms of FPHL as well as the results of the genetic studies performed to date are summarized. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Study of Relationship between Genetic Pattern and Susceptibility to Fluconazole in Clinical Isolated of Trichophyton rubrum

    Directory of Open Access Journals (Sweden)

    F Hadadi

    2015-06-01

    Full Text Available Background & objectives: Trichophyton rubrum is one of the most common pathogenic causes of dermatophytosis. One of the drugs prescribed for fungal infections is fluconazole which belongs to Azoles group of antifungal agents. Recently molecular typing methods have been developed for answering the epidemiological questions and disease recurrence problems. Current study has been conducted on 22 isolates of Trichophyton rubrum obtained from patients randomly. Our aim was the investigation of correlation between genetic pattern and sensitivity to Fluconazole in clinical isolates of Trichophyton rubrum .   Methods: Firstly the genus and species of isolated fungi from patients have been confirmed by macroscopic and microscopic methods. Then, the resistance and sensitivity of isolates against drug have been determined using culture medium containing defined amount of drug. In next step fungal DNA has been extracted by RAPD-PCR (random amplified polymorphic DNA with random sequences of 3 primers.   Results: Each primer produced different amplified pattern, and differences have been observed in genetic pattern of resistant and sensitive samples using each 3 primers, but there was no bond with 100% specificity.   Conclusion: The 12 sensitive isolates which didn’t grow in 50µg/ml concentration of drug, also had limited growth at the lower concentration of drug. Ten resistant isolates which grew in 50µg/ml of drug, also showed resistant to lower concentration of drug. There are differences in genetic pattern of resistant and sensitive samples. RAPD analysis for molecular typing of Trichophyton rubrum seems to be completely suitable.

  8. Integument pattern formation involves genetic and epigenetic controls: feather arrays simulated by digital hormone models.

    Science.gov (United States)

    Jiang, Ting-Xin; Widelitz, Randall B; Shen, Wei-Min; Will, Peter; Wu, Da-Yu; Lin, Chih-Min; Jung, Han-Sung; Chuong, Cheng-Ming

    2004-01-01

    Pattern formation is a fundamental morphogenetic process. Models based on genetic and epigenetic control have been proposed but remain controversial. Here we use feather morphogenesis for further evaluation. Adhesion molecules and/or signaling molecules were first expressed homogenously in feather tracts (restrictive mode, appear earlier) or directly in bud or inter-bud regions ( de novo mode, appear later). They either activate or inhibit bud formation, but paradoxically colocalize in the bud. Using feather bud reconstitution, we showed that completely dissociated cells can reform periodic patterns without reference to previous positional codes. The patterning process has the characteristics of being self-organizing, dynamic and plastic. The final pattern is an equilibrium state reached by competition, and the number and size of buds can be altered based on cell number and activator/inhibitor ratio, respectively. We developed a Digital Hormone Model which consists of (1) competent cells without identity that move randomly in a space, (2) extracellular signaling hormones which diffuse by a reaction-diffusion mechanism and activate or inhibit cell adhesion, and (3) cells which respond with topological stochastic actions manifested as changes in cell adhesion. Based on probability, the results are cell clusters arranged in dots or stripes. Thus genetic control provides combinational molecular information which defines the properties of the cells but not the final pattern. Epigenetic control governs interactions among cells and their environment based on physical-chemical rules (such as those described in the Digital Hormone Model). Complex integument patterning is the sum of these two components of control and that is why integument patterns are usually similar but non-identical. These principles may be shared by other pattern formation processes such as barb ridge formation, fingerprints, pigmentation patterning, etc. The Digital Hormone Model can also be applied to

  9. MiRNA expression patterns predict survival in glioblastoma

    International Nuclear Information System (INIS)

    Niyazi, Maximilian; Belka, Claus; Zehentmayr, Franz; Niemöller, Olivier M; Eigenbrod, Sabina; Kretzschmar, Hans; Osthoff, Klaus-Schulze; Tonn, Jörg-Christian; Atkinson, Mike; Mörtl, Simone

    2011-01-01

    In order to define new prognostic subgroups in patients with glioblastoma a miRNA screen (> 1000 miRNAs) from paraffin tissues followed by a bio-mathematical analysis was performed. 35 glioblastoma patients treated between 7/2005 - 8/2008 at a single institution with surgery and postoperative radio(chemo)therapy were included in this retrospective analysis. For microarray analysis the febit biochip 'Geniom ® Biochip MPEA homo-sapiens' was used. Total RNA was isolated from FFPE tissue sections and 1100 different miRNAs were analyzed. It was possible to define a distinct miRNA expression pattern allowing for a separation of distinct prognostic subgroups. The defined miRNA pattern was significantly associated with early death versus long-term survival (split at 450 days) (p = 0.01). The pattern and the prognostic power were both independent of the MGMT status. At present, this is the first dataset defining a prognostic role of miRNA expression patterns in patients with glioblastoma. Having defined such a pattern, a prospective validation of this observation is required

  10. Using soil seed banks to assess temporal patterns of genetic variation in invasive plant populations.

    Science.gov (United States)

    Fennell, Mark; Gallagher, Tommy; Vintro, Luis Leon; Osborne, Bruce

    2014-05-01

    Most research on the genetics of invasive plant species has focused on analyzing spatial differences among existing populations. Using a long-established Gunnera tinctoria population from Ireland, we evaluated the potential of using plants derived from seeds associated with different soil layers to track genetic variation through time. This species and site were chosen because (1) G. tinctoria produces a large and persistent seed bank; (2) it has been present in this locality, Sraheens, for ∼90 years; (3) the soil is largely undisturbed; and (4) the soil's age can be reliably determined radiometrically at different depths. Amplified fragment length polymorphic markers (AFLPs) were used to assess differences in the genetic structure of 75 individuals sampled from both the standing population and from four soil layers, which spanned 18 cm (estimated at ∼90 years based on (210)Pb and (137)Cs dating). While there are difficulties in interpreting such data, including accounting for the effects of selection, seed loss, and seed migration, a clear pattern of lower total allele counts, percentage polymorphic loci, and genetic diversity was observed in deeper soils. The greatest percentage increase in the measured genetic variables occurred prior to the shift from the lag to the exponential range expansion phases and may be of adaptive significance. These findings highlight that seed banks in areas with long-established invasive populations can contain valuable genetic information relating to invasion processes and as such, should not be overlooked.

  11. Gaming Device Usage Patterns Predict Internet Gaming Disorder: Comparison across Different Gaming Device Usage Patterns

    OpenAIRE

    Soo-Hyun Paik; Hyun Cho; Ji-Won Chun; Jo-Eun Jeong; Dai-Jin Kim

    2017-01-01

    Gaming behaviors have been significantly influenced by smartphones. This study was designed to explore gaming behaviors and clinical characteristics across different gaming device usage patterns and the role of the patterns on Internet gaming disorder (IGD). Responders of an online survey regarding smartphone and online game usage were classified by different gaming device usage patterns: (1) individuals who played only computer games; (2) individuals who played computer games more than smart...

  12. An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

    Science.gov (United States)

    Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

    2017-12-01

    Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

  13. Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

    Science.gov (United States)

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

    2017-03-02

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

  14. Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

    Science.gov (United States)

    Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

    There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

  15. Genetic algorithm for the optimization of the loading pattern for reactor core fuel management

    International Nuclear Information System (INIS)

    Zhou Sheng; Hu Yongming; zheng Wenxiang

    2000-01-01

    The paper discusses the application of a genetic algorithm to the optimization of the loading pattern for in-core fuel management with the NP characteristics. The algorithm develops a matrix model for the fuel assembly loading pattern. The burnable poisons matrix was assigned randomly considering the distributed nature of the poisons. A method based on the traveling salesman problem was used to solve the problem. A integrated code for in-core fuel management was formed by combining this code with a reactor physics code

  16. Development of a BWR loading pattern design system based on modified genetic algorithms and knowledge

    International Nuclear Information System (INIS)

    Martin-del-Campo, Cecilia; Francois, Juan Luis; Avendano, Linda; Gonzalez, Mario

    2004-01-01

    An optimization system based on Genetic Algorithms (GAs), in combination with expert knowledge coded in heuristics rules, was developed for the design of optimized boiling water reactor (BWR) fuel loading patterns. The system was coded in a computer program named Loading Pattern Optimization System based on Genetic Algorithms, in which the optimization code uses GAs to select candidate solutions, and the core simulator code CM-PRESTO to evaluate them. A multi-objective function was built to maximize the cycle energy length while satisfying power and reactivity constraints used as BWR design parameters. Heuristic rules were applied to satisfy standard fuel management recommendations as the Control Cell Core and Low Leakage loading strategies, and octant symmetry. To test the system performance, an optimized cycle was designed and compared against an actual operating cycle of Laguna Verde Nuclear Power Plant, Unit I

  17. Searching for full power control rod patterns in a boiling water reactor using genetic algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Montes, Jose Luis [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jlmt@nuclear.inin.mx; Ortiz, Juan Jose [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: jjortiz@nuclear.inin.mx; Requena, Ignacio [Departamento Ciencias Computacion e I.A. ETSII, Informatica, Universidad de Granada, C. Daniel Saucedo Aranda s/n. 18071 Granada (Spain)]. E-mail: requena@decsai.ugr.es; Perusquia, Raul [Departamento Sistemas Nucleares, ININ, Carr. Mexico-Toluca Km. 36.5, Ocoyoacac, Edo. de Mexico (Mexico)]. E-mail: rpc@nuclear.inin.mx

    2004-11-01

    One of the most important questions related to both safety and economic aspects in a nuclear power reactor operation, is without any doubt its reactivity control. During normal operation of a boiling water reactor, the reactivity control of its core is strongly determined by control rods patterns efficiency. In this paper, GACRP system is proposed based on the concepts of genetic algorithms for full power control rod patterns search. This system was carried out using LVNPP transition cycle characteristics, being applied too to an equilibrium cycle. Several operation scenarios, including core water flow variation throughout the cycle and different target axial power distributions, are considered. Genetic algorithm fitness function includes reactor security parameters, such as MLHGR, MCPR, reactor k{sub eff} and axial power density.

  18. Geographic patterns of genetic variation and conservation consequences in three South American rodents.

    Science.gov (United States)

    Miranda, Gustavo B; Andrades-Miranda, Jaqueline; Oliveira, Luiz F B; Langguth, Alfredo; Mattevi, Margarete S

    2007-12-01

    In this study, the geographic patterns of genetic variation of three rodent species belonging to the tribe Oryzomyini were investigated using the mitochondrial cytochrome b and nuclear IRBP genes in biomes that are undergoing degradation processes to a greater or lesser degree. The samples are from 25 collecting localities distributed throughout the Amazon, Cerrado, Atlantic Forest, and Pampa biomes. The results show that the three species have a population and geographic structure, besides being in demographic equilibrium. The phylogenetic analyses performed on Euryoryzomys russatus and Hylaeamys megacephalus showed these specimens grouped in three distinct clades forming geographic gradients (North-South direction in H. megacephalus). Intraspecific genetic divergence was higher in H. megacephalus (4.53%), followed by E. russatus (1.79%), and lowest in Sooretamys angouya (0.88%). The results obtained indicate that, necessarily, the management strategies to preserve genetic diversity should be different for each species, since each of them presented specific population parameters.

  19. The potential of large studies for building genetic risk prediction models

    Science.gov (United States)

    NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

  20. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    Science.gov (United States)

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  1. Optimal Refueling Pattern Search for a CANDU Reactor Using a Genetic Algorithm

    International Nuclear Information System (INIS)

    Quang Binh, DO; Gyuhong, ROH; Hangbok, CHOI

    2006-01-01

    This paper presents the results from the application of genetic algorithms to a refueling optimization of a Canada deuterium uranium (CANDU) reactor. This work aims at making a mathematical model of the refueling optimization problem including the objective function and constraints and developing a method based on genetic algorithms to solve the problem. The model of the optimization problem and the proposed method comply with the key features of the refueling strategy of the CANDU reactor which adopts an on-power refueling operation. In this study, a genetic algorithm combined with an elitism strategy was used to automatically search for the refueling patterns. The objective of the optimization was to maximize the discharge burn-up of the refueling bundles, minimize the maximum channel power, or minimize the maximum change in the zone controller unit (ZCU) water levels. A combination of these objectives was also investigated. The constraints include the discharge burn-up, maximum channel power, maximum bundle power, channel power peaking factor and the ZCU water level. A refueling pattern that represents the refueling rate and channels was coded by a one-dimensional binary chromosome, which is a string of binary numbers 0 and 1. A computer program was developed in FORTRAN 90 running on an HP 9000 workstation to conduct the search for the optimal refueling patterns for a CANDU reactor at the equilibrium state. The results showed that it was possible to apply genetic algorithms to automatically search for the refueling channels of the CANDU reactor. The optimal refueling patterns were compared with the solutions obtained from the AUTOREFUEL program and the results were consistent with each other. (authors)

  2. Revealing life-history traits by contrasting genetic estimations with predictions of effective population size.

    Science.gov (United States)

    Greenbaum, Gili; Renan, Sharon; Templeton, Alan R; Bouskila, Amos; Saltz, David; Rubenstein, Daniel I; Bar-David, Shirli

    2017-12-22

    Effective population size, a central concept in conservation biology, is now routinely estimated from genetic surveys and can also be theoretically predicted from demographic, life-history, and mating-system data. By evaluating the consistency of theoretical predictions with empirically estimated effective size, insights can be gained regarding life-history characteristics and the relative impact of different life-history traits on genetic drift. These insights can be used to design and inform management strategies aimed at increasing effective population size. We demonstrated this approach by addressing the conservation of a reintroduced population of Asiatic wild ass (Equus hemionus). We estimated the variance effective size (N ev ) from genetic data (N ev =24.3) and formulated predictions for the impacts on N ev of demography, polygyny, female variance in lifetime reproductive success (RS), and heritability of female RS. By contrasting the genetic estimation with theoretical predictions, we found that polygyny was the strongest factor affecting genetic drift because only when accounting for polygyny were predictions consistent with the genetically measured N ev . The comparison of effective-size estimation and predictions indicated that 10.6% of the males mated per generation when heritability of female RS was unaccounted for (polygyny responsible for 81% decrease in N ev ) and 19.5% mated when female RS was accounted for (polygyny responsible for 67% decrease in N ev ). Heritability of female RS also affected N ev ; hf2=0.91 (heritability responsible for 41% decrease in N ev ). The low effective size is of concern, and we suggest that management actions focus on factors identified as strongly affecting Nev, namely, increasing the availability of artificial water sources to increase number of dominant males contributing to the gene pool. This approach, evaluating life-history hypotheses in light of their impact on effective population size, and contrasting

  3. Stream Flow Prediction by Remote Sensing and Genetic Programming

    Science.gov (United States)

    Chang, Ni-Bin

    2009-01-01

    A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

  4. Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy

    Directory of Open Access Journals (Sweden)

    Hanson Jesse E

    2010-08-01

    Full Text Available Abstract Background Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1 Strength of long-term potentiation (LTP, 2 Strength of long-term depression (LTD, 3 Relative inhibition levels (Inhibition, and 4 Excitatory connectivity levels (Connectivity. Results To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties. Conclusions Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.

  5. Genetic algorithms and artificial neural networks for loading pattern optimisation of advanced gas-cooled reactors

    Energy Technology Data Exchange (ETDEWEB)

    Ziver, A.K. E-mail: a.k.ziver@imperial.ac.uk; Pain, C.C; Carter, J.N.; Oliveira, C.R.E. de; Goddard, A.J.H.; Overton, R.S

    2004-03-01

    A non-generational genetic algorithm (GA) has been developed for fuel management optimisation of Advanced Gas-Cooled Reactors, which are operated by British Energy and produce around 20% of the UK's electricity requirements. An evolutionary search is coded using the genetic operators; namely selection by tournament, two-point crossover, mutation and random assessment of population for multi-cycle loading pattern (LP) optimisation. A detailed description of the chromosomes in the genetic algorithm coded is presented. Artificial Neural Networks (ANNs) have been constructed and trained to accelerate the GA-based search during the optimisation process. The whole package, called GAOPT, is linked to the reactor analysis code PANTHER, which performs fresh fuel loading, burn-up and power shaping calculations for each reactor cycle by imposing station-specific safety and operational constraints. GAOPT has been verified by performing a number of tests, which are applied to the Hinkley Point B and Hartlepool reactors. The test results giving loading pattern (LP) scenarios obtained from single and multi-cycle optimisation calculations applied to realistic reactor states of the Hartlepool and Hinkley Point B reactors are discussed. The results have shown that the GA/ANN algorithms developed can help the fuel engineer to optimise loading patterns in an efficient and more profitable way than currently available for multi-cycle refuelling of AGRs. Research leading to parallel GAs applied to LP optimisation are outlined, which can be adapted to present day LWR fuel management problems.

  6. Patterning and predicting aquatic macroinvertebrate diversities using artificial neural network

    NARCIS (Netherlands)

    Park, Y.S.; Verdonschot, P.F.M.; Chon, T.S.; Lek, S.

    2003-01-01

    A counterpropagation neural network (CPN) was applied to predict species richness (SR) and Shannon diversity index (SH) of benthic macroinvertebrate communities using 34 environmental variables. The data were collected at 664 sites at 23 different water types such as springs, streams, rivers,

  7. Predicting STEM Career Success by STI Knowledge Utilization Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Bozeman, B.; Youtie, J.; Bretschneider, S.

    2016-07-01

    As a part of discussion on knowledge utilization on science and technology, the mixed of papers presented in the panel discussion is designed to illustrate the patterns of collaboration, mobility, and diffusion of knowledge as well as those of labor force. In particular, the first two papers presented in the panel explore the potential of STEM career success through cosmopolitan collaboration and international community collaboration (focused on the relationships between China and Russia) in nanotechnology, which would provide implications on national and international benchmarking of innovation. For policy implications on graduate education and innovation, mobility pattern of non-U.S. Ph.D. degree holders is examined, and impact of a policy report on the target academic communities is investigated through development of credibility map. This panel is designed to highlight a recent effort of understanding geographical, cognitive or social spaces that are present in the scientific and technological activity as well as in doctoral education. The papers presented in this panel, therefore, will provide a rich set of significant and relevant insights drawn from examining STI knowledge utilization patterns to the STI-ENID community. The anticipated length of the event may be 90 minutes and there is no preferred number of attendees in particular although it is expected to be in between 35 and 60 at the minimum. (Author)

  8. Mitochondrial DNA variability among eight Tikúna villages: evidence for an intratribal genetic heterogeneity pattern.

    Science.gov (United States)

    Mendes-Junior, Celso Teixeira; Simões, Aguinaldo Luiz

    2009-11-01

    To study the genetic structure of the Tikúna tribe, four major Native American mitochondrial DNA (mtDNA) founder haplogroups were analyzed in 187 Amerindians from eight Tikúna villages located in the Brazilian Amazon. The central position of these villages in the continent makes them relevant for attempts to reconstruct population movements in South America. In this geographic region, there is particular concern regarding the genetic structure of the Tikúna tribe, formerly designated "enigmatic" due to its remarkable degree of intratribal homogeneity and the scarcity of private protein variants. In spite of its large population size and geographic distribution, the Tikúna tribe presents marked genetic and linguistic isolation. All individuals presented indigenous mtDNA haplogroups. An intratribal genetic heterogeneity pattern characterized by two highly homogeneous Tikúna groups that differ considerably from each other was observed. Such a finding was unexpected, since the Tikúna tribe is characterized by a social system that favors intratribal exogamy and patrilocality that would lead to a higher female migration rate and homogenization of the mtDNA gene pool. Demographic explosions and religious events, which significantly changed the sizes and compositions of many Tikúna villages, may be reflected in the genetic results presented here.

  9. Genetic enhancement, social justice, and welfare-oriented patterns of distribution.

    Science.gov (United States)

    Etieyibo, Edwin

    2012-07-01

    The debate over the host of moral issues that genetic enhancement technology (GET) raises has been significant. One argument that has been advanced to impugn its moral legitimacy is the 'unfair advantage argument' (UAA), which states: allowing access to GET to be determined by socio-economic status would lead to unjust outcomes, namely, create a genetic caste system, and with it the exacerbation and perpetuation of existing socio-economic inequalities. Fritz Allhoff has recently objected to the argument, the kernel of which is that it conflates the use of the technology with its distribution. GET, he argues, would generate unjust outcomes only if it is distributed according to principles of an unjust pattern of distribution; for if we can determine what constitutes a 'just' distributive scheme, then the technology can be allocated according to the principles of that scheme. In this paper I argue the following cluster of related claims: (1) both UAA and Allhoff's proposed distributive schemes ignore the importance of non-genetic factors in the development of an individual's characteristics and capacities; (2) if we accept the view that it is good to prevent unjust outcomes that arise because some have exclusive access to GET, then we have to accept wide-ranging distributive schemes; (3) by tracking genetic and non-genetic factors wide-ranging schemes do violate in some sense the widely shared value of neutrality in liberal democracies. © 2011 Blackwell Publishing Ltd.

  10. Contrasting patterns of genetic divergence in two sympatric pseudo-metallophytes: Rumex acetosa L. and Commelina communis L.

    Directory of Open Access Journals (Sweden)

    Ye M

    2012-06-01

    Full Text Available Abstract Background Patterns of genetic divergence between populations of facultative metallophytes have been investigated extensively. However, most previous investigations have focused on a single plant species making it unclear if genetic divergence shows common patterns or, conversely, is species-specific. The herbs Rumex acetosa L. and Commelina communis L. are two pseudo-metallophytes thriving in both normal and cupriferous soils along the middle and lower reaches of the Yangtze River in China. Their non-metallicolous and metallicolous populations are often sympatric thus providing an ideal opportunity for comparative estimation of genetic structures and divergence under the selective pressure derived from copper toxicity. Results In the present study, patterns of genetic divergence of R. acetosa and C. communis , including metal tolerance, genetic structure and genetic relationships between populations, were investigated and compared using hydroponic experiments, AFLP, ISSR and chloroplast genetic markers. Our results show a significant reduction in genetic diversity in metallicolous populations of C. communis but not in R. acetosa . Moreover, genetic differentiation is less in R. acetosa than in C. communis , the latter species also shows a clustering of its metallicolous populations. Conclusions We propose that the genetic divergences apparent in R. acetosa and C. communis , and the contrasting responses of the two species to copper contamination, might be attributed to the differences in their intrinsic physiological and ecological properties. No simple and generalised conclusions on genetic divergence in pseudo-metallophytes can thus be drawn.

  11. A method of predicting changes in human gene splicing induced by genetic variants in context of cis-acting elements

    Directory of Open Access Journals (Sweden)

    Hicks Chindo

    2010-01-01

    Full Text Available Abstract Background Polymorphic variants and mutations disrupting canonical splicing isoforms are among the leading causes of human hereditary disorders. While there is a substantial evidence of aberrant splicing causing Mendelian diseases, the implication of such events in multi-genic disorders is yet to be well understood. We have developed a new tool (SpliceScan II for predicting the effects of genetic variants on splicing and cis-regulatory elements. The novel Bayesian non-canonical 5'GC splice site (SS sensor used in our tool allows inference on non-canonical exons. Results Our tool performed favorably when compared with the existing methods in the context of genes linked to the Autism Spectrum Disorder (ASD. SpliceScan II was able to predict more aberrant splicing isoforms triggered by the mutations, as documented in DBASS5 and DBASS3 aberrant splicing databases, than other existing methods. Detrimental effects behind some of the polymorphic variations previously associated with Alzheimer's and breast cancer could be explained by changes in predicted splicing patterns. Conclusions We have developed SpliceScan II, an effective and sensitive tool for predicting the detrimental effects of genomic variants on splicing leading to Mendelian and complex hereditary disorders. The method could potentially be used to screen resequenced patient DNA to identify de novo mutations and polymorphic variants that could contribute to a genetic disorder.

  12. Inflammatory Dietary Pattern, IL-17F Genetic Variant, and the Risk of Colorectal Cancer.

    Science.gov (United States)

    Cho, Young Ae; Lee, Jeonghee; Oh, Jae Hwan; Chang, Hee Jin; Sohn, Dae Kyung; Shin, Aesun; Kim, Jeongseon

    2018-06-05

    A proinflammatory diet may increase the risk of colorectal cancer, but its role may differ according to individuals' genetic variants. We aimed to examine whether a specific dietary pattern reflecting inflammation was associated with a risk of colorectal cancer and whether IL-17F genetic variant altered this association. In a study of 695 colorectal cancer cases and 1846 controls, we derived a reduced rank regression dietary pattern using 32 food groups as predictors and the plasma C-reactive protein (CRP) concentration as the response. High CRP levels were associated with a high risk of colorectal cancer (OR (95% CI) = 3.58 (2.65⁻4.82) for the highest quartile vs. lowest quartile). After adjusting for potential confounding factors, high pattern scores were associated with a high risk of colorectal cancer (OR (95% CI) = 9.98 (6.81⁻14.62) for the highest quartile vs. lowest quartile). When stratified by the IL-17F rs763780 genotype, this association was stronger for individuals carrying the C allele ( p for interaction = 0.034), particularly for individuals with rectal cancer ( p for interaction = 0.011). In conclusion, a dietary pattern reflecting inflammation was significantly associated with colorectal cancer risk. Moreover, this association could be modified according to the IL-17F rs763780 genotype and anatomic site.

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

    DEFF Research Database (Denmark)

    Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage

    2012-01-01

    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...

  14. Reloading pattern optimization of VVER-1000 reactors in transient cycles using genetic algorithm

    International Nuclear Information System (INIS)

    Rahmani, Yashar

    2017-01-01

    Highlights: • The genetic algorithm (GA) and the innovative weighting factors method were used. • The coupling of WIMSD5-B and CITATION-LDI2 neutronic codes with the thermohydraulic WERL code was employed. • Optimization of reloading patterns was carried out in two states. • First an arrangement with satisfactory excess reactivity and the flattest power distribution was searched. • Second, it is tried to obtain an arrangement with satisfactory safety threshold and the maximum K_e_f_f. - Abstract: The present paper proposes application of the genetic algorithm (GA) and the innovative weighting factor method to optimize the reloading pattern of Bushehr VVER-1000 reactor in the second cycle. To estimate the composition of fuel assemblies remaining from the first cycle and precisely calculate the objective parameters of each reloading pattern in the second cycle, coupling of WIMSD5-B and CITATION-LDI2 codes in the neutronic section and the WERL code in the thermo-hydraulic section was employed. Optimization of the reloading patterns was carried out in two states. To meet the mentioned objective, with application of the weighting factor method in the first state, the type and quantity of the loadable fresh assemblies were determined to enable the reactor core to maintain the core criticality over the entire cycle length. Afterwards, the genetic algorithm was used to optimize the reloading pattern of the reactor to obtain an arrangement with flat radial power distribution. In the second state, the optimization algorithm was free to select the type and number of fresh fuel assemblies to be able to search for an arrangement with the maximum effective multiplication factor and the safe power peaking factor. In addition, in order to ensure the safety and desirability of the proposed patterns in both states, a time-dependent examination of the thermo-neutronic behavior of the reactor core was carried out during the second cycle. With consideration of the new

  15. Adaboost Ensemble with Simple Genetic Algorithm for Student Prediction Mode

    OpenAIRE

    AhmedSharaf ElDen; ElDen1Malaka A. Moustafa2Hany; M. Harb; AbdelH.Emara

    2013-01-01

    Predicting the student performance is a great concern to the higher education managements.Thisprediction helps to identify and to improve students' performance.Several factors may improve thisperformance.In the present study, we employ the data mining processes, particularly classification, toenhance the quality of the higher educational system. Recently, a new direction is used for the improvementof the classification accuracy by combining classifiers.In thispaper, we design and evaluate a f...

  16. Molecular genetic features of polyploidization and aneuploidization reveal unique patterns for genome duplication in diploid Malus.

    Directory of Open Access Journals (Sweden)

    Michael J Considine

    Full Text Available Polyploidization results in genome duplication and is an important step in evolution and speciation. The Malus genome confirmed that this genus was derived through auto-polyploidization, yet the genetic and meiotic mechanisms for polyploidization, particularly for aneuploidization, are unclear in this genus or other woody perennials. In fact the contribution of aneuploidization remains poorly understood throughout Plantae. We add to this knowledge by characterization of eupolyploidization and aneuploidization in 27,542 F₁ seedlings from seven diploid Malus populations using cytology and microsatellite markers. We provide the first evidence that aneuploidy exceeds eupolyploidy in the diploid crosses, suggesting aneuploidization is a leading cause of genome duplication. Gametes from diploid Malus had a unique combinational pattern; ova preserved euploidy exclusively, while spermatozoa presented both euploidy and aneuploidy. All non-reduced gametes were genetically heterozygous, indicating first-division restitution was the exclusive mode for Malus eupolyploidization and aneuploidization. Chromosome segregation pattern among aneuploids was non-uniform, however, certain chromosomes were associated for aneuploidization. This study is the first to provide molecular evidence for the contribution of heterozygous non-reduced gametes to fitness in polyploids and aneuploids. Aneuploidization can increase, while eupolyploidization may decrease genetic diversity in their newly established populations. Auto-triploidization is important for speciation in the extant Malus. The features of Malus polyploidization confer genetic stability and diversity, and present heterozygosity, heterosis and adaptability for evolutionary selection. A protocol using co-dominant markers was proposed for accelerating apple triploid breeding program. A path was postulated for evolution of numerically odd basic chromosomes. The model for Malus derivation was considerably revised

  17. Molecular genetic features of polyploidization and aneuploidization reveal unique patterns for genome duplication in diploid Malus.

    Science.gov (United States)

    Considine, Michael J; Wan, Yizhen; D'Antuono, Mario F; Zhou, Qian; Han, Mingyu; Gao, Hua; Wang, Man

    2012-01-01

    Polyploidization results in genome duplication and is an important step in evolution and speciation. The Malus genome confirmed that this genus was derived through auto-polyploidization, yet the genetic and meiotic mechanisms for polyploidization, particularly for aneuploidization, are unclear in this genus or other woody perennials. In fact the contribution of aneuploidization remains poorly understood throughout Plantae. We add to this knowledge by characterization of eupolyploidization and aneuploidization in 27,542 F₁ seedlings from seven diploid Malus populations using cytology and microsatellite markers. We provide the first evidence that aneuploidy exceeds eupolyploidy in the diploid crosses, suggesting aneuploidization is a leading cause of genome duplication. Gametes from diploid Malus had a unique combinational pattern; ova preserved euploidy exclusively, while spermatozoa presented both euploidy and aneuploidy. All non-reduced gametes were genetically heterozygous, indicating first-division restitution was the exclusive mode for Malus eupolyploidization and aneuploidization. Chromosome segregation pattern among aneuploids was non-uniform, however, certain chromosomes were associated for aneuploidization. This study is the first to provide molecular evidence for the contribution of heterozygous non-reduced gametes to fitness in polyploids and aneuploids. Aneuploidization can increase, while eupolyploidization may decrease genetic diversity in their newly established populations. Auto-triploidization is important for speciation in the extant Malus. The features of Malus polyploidization confer genetic stability and diversity, and present heterozygosity, heterosis and adaptability for evolutionary selection. A protocol using co-dominant markers was proposed for accelerating apple triploid breeding program. A path was postulated for evolution of numerically odd basic chromosomes. The model for Malus derivation was considerably revised. Impacts of

  18. Differing patterns of selection and geospatial genetic diversity within two leading Plasmodium vivax candidate vaccine antigens.

    Directory of Open Access Journals (Sweden)

    Christian M Parobek

    2014-04-01

    Full Text Available Although Plasmodium vivax is a leading cause of malaria around the world, only a handful of vivax antigens are being studied for vaccine development. Here, we investigated genetic signatures of selection and geospatial genetic diversity of two leading vivax vaccine antigens--Plasmodium vivax merozoite surface protein 1 (pvmsp-1 and Plasmodium vivax circumsporozoite protein (pvcsp. Using scalable next-generation sequencing, we deep-sequenced amplicons of the 42 kDa region of pvmsp-1 (n = 44 and the complete gene of pvcsp (n = 47 from Cambodian isolates. These sequences were then compared with global parasite populations obtained from GenBank. Using a combination of statistical and phylogenetic methods to assess for selection and population structure, we found strong evidence of balancing selection in the 42 kDa region of pvmsp-1, which varied significantly over the length of the gene, consistent with immune-mediated selection. In pvcsp, the highly variable central repeat region also showed patterns consistent with immune selection, which were lacking outside the repeat. The patterns of selection seen in both genes differed from their P. falciparum orthologs. In addition, we found that, similar to merozoite antigens from P. falciparum malaria, genetic diversity of pvmsp-1 sequences showed no geographic clustering, while the non-merozoite antigen, pvcsp, showed strong geographic clustering. These findings suggest that while immune selection may act on both vivax vaccine candidate antigens, the geographic distribution of genetic variability differs greatly between these two genes. The selective forces driving this diversification could lead to antigen escape and vaccine failure. Better understanding the geographic distribution of genetic variability in vaccine candidate antigens will be key to designing and implementing efficacious vaccines.

  19. Exploring the significance of human mobility patterns in social link prediction

    KAUST Repository

    Alharbi, Basma Mohammed

    2014-01-01

    Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper explores the effect of in-depth mobility patterns. Specifically, we study individuals\\' movement behavior, and quantify mobility on the basis of trip frequency, travel purpose and transportation mode. Our hybrid link prediction model is composed of two modules. The first module extracts mobility patterns, including travel purpose and mode, from raw trajectory data. The second module employs the extracted patterns for link prediction. We evaluate our method on two real data sets, GeoLife [15] and Reality Mining [5]. Experimental results show that our hybrid model significantly improves the accuracy of social link prediction, when comparing to primary topology-based solutions. Copyright 2014 ACM.

  20. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs

    Directory of Open Access Journals (Sweden)

    Sungjun Lee

    2016-01-01

    Full Text Available Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user’s next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user’s past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user’s next places than the previous approaches considered in most cases.

  1. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

    Science.gov (United States)

    Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

    2016-01-23

    Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases.

  2. Ethnicity prediction and classification from iris texture patterns: A survey on recent advances

    CSIR Research Space (South Africa)

    Mabuza-Hocquet, Gugulethu

    2017-03-01

    Full Text Available The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research...

  3. Exploring the significance of human mobility patterns in social link prediction

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2014-01-01

    Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper

  4. Expression patterns of the aquaporin gene family during renal development: influence of genetic variability.

    Science.gov (United States)

    Parreira, Kleber S; Debaix, Huguette; Cnops, Yvette; Geffers, Lars; Devuyst, Olivier

    2009-08-01

    High-throughput analyses have shown that aquaporins (AQPs) belong to a cluster of genes that are differentially expressed during kidney organogenesis. However, the spatiotemporal expression patterns of the AQP gene family during tubular maturation and the potential influence of genetic variation on these patterns and on water handling remain unknown. We investigated the expression patterns of all AQP isoforms in fetal (E13.5 to E18.5), postnatal (P1 to P28), and adult (9 weeks) kidneys of inbred (C57BL/6J) and outbred (CD-1) mice. Using quantitative polymerase chain reaction (PCR), we evidenced two mRNA patterns during tubular maturation in C57 mice. The AQPs 1-7-11 showed an early (from E14.5) and progressive increase to adult levels, similar to the mRNA pattern observed for proximal tubule markers (Megalin, NaPi-IIa, OAT1) and reflecting the continuous increase in renal cortical structures during development. By contrast, AQPs 2-3-4 showed a later (E15.5) and more abrupt increase, with transient postnatal overexpression. Most AQP genes were expressed earlier and/or stronger in maturing CD-1 kidneys. Furthermore, adult CD-1 kidneys expressed more AQP2 in the collecting ducts, which was reflected by a significant delay in excreting a water load. The expression patterns of proximal vs. distal AQPs and the earlier expression in the CD-1 strain were confirmed by immunoblotting and immunostaining. These data (1) substantiate the clustering of important genes during tubular maturation and (2) demonstrate that genetic variability influences the regulation of the AQP gene family during tubular maturation and water handling by the mature kidney.

  5. Predictive patterns of early medication adherence in renal transplantation.

    Science.gov (United States)

    Nevins, Thomas E; Robiner, William N; Thomas, William

    2014-10-27

    Patients' adherence with posttransplant immunosuppression is known to affect renal transplant outcomes. Prospectively, individual medication adherence patterns in 195 kidney transplant recipients were quantified with electronic medication monitors. Monitored drugs were mycophenolate mofetil, sirolimus, or azathioprine. Monitoring began at hospital discharge and continued an average of 15±8 months. Patient follow-up for clinical outcomes averaged 8±3 years. Each month's adherence percentage was calculated as the sum of daily adherence percents, divided by the number of evaluable days. During the first 3 months after transplantation, patients (n=44) with declining medication adherence, defined as dropping by 7% or higher (equal to missing 2 days) between months 1 and 2, later experienced lower mean medication adherence for months 6 to 12, 73% versus 92% respectively (Padherence, they also had more frequent (P=0.034) and earlier (P=0.065) acute rejection episodes. This was additionally associated with more frequent (P=0.017) and earlier (P=0.046) death-censored graft loss.In addition, daily medication adherence, expressed as the percentage of doses taken, decreased as the number of prescribed daily doses increased. During the first 3 months after transplantation, adherence with four doses per day averaged 84%, compared to 91% for patients on twice-daily dosing (P=0.024) and 93.5% for patients on once-daily dosing (P=0.008). Early declining medication nonadherence is associated with adverse clinical outcomes. This pattern is detectable during the first 2 months after transplantation. Early detection of nonadherence provides opportunities to target interventions toward patients at the highest risk for adverse behaviors and events.

  6. Patterns of genetic diversity in three plant lineages endemic to the Cape Verde Islands.

    Science.gov (United States)

    Romeiras, Maria M; Monteiro, Filipa; Duarte, M Cristina; Schaefer, Hanno; Carine, Mark

    2015-05-15

    Conservation of plant diversity on islands relies on a good knowledge of the taxonomy, distribution and genetic diversity of species. In recent decades, a combination of morphology- and DNA-based approaches has become the standard for investigating island plant lineages and this has led, in some cases, to the discovery of previously overlooked diversity, including 'cryptic species'. The flora of the Cape Verde archipelago in the North Atlantic is currently thought to comprise ∼740 vascular plant species, 92 of them endemics. Despite the fact that it is considered relatively well known, there has been a 12 % increase in the number of endemics in the last two decades. Relatively few of the Cape Verde plant lineages have been included in genetic studies so far and little is known about the patterns of diversification in the archipelago. Here we present an updated list for the endemic Cape Verde flora and analyse diversity patterns for three endemic plant lineages (Cynanchum, Globularia and Umbilicus) based on one nuclear (ITS) and four plastid DNA regions. In all three lineages, we find genetic variation. In Cynanchum, we find two distinct haplotypes with no clear geographical pattern, possibly reflecting different ploidy levels. In Globularia and Umbilicus, differentiation is evident between populations from northern and southern islands. Isolation and drift resulting from the small and fragmented distributions, coupled with the significant distances separating the northern and southern islands, could explain this pattern. Overall, our study suggests that the diversity in the endemic vascular flora of Cape Verde is higher than previously thought and further work is necessary to characterize the flora. Published by Oxford University Press on behalf of the Annals of Botany Company.

  7. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

    Science.gov (United States)

    Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A

    2018-03-01

    Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

  8. Distinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders

    Directory of Open Access Journals (Sweden)

    Nhat Trung Doan

    2017-01-01

    Full Text Available The brain underpinnings of schizophrenia and bipolar disorders are multidimensional, reflecting complex pathological processes and causal pathways, requiring multivariate techniques to disentangle. Furthermore, little is known about the complementary clinical value of brain structural phenotypes when combined with data on cognitive performance and genetic risk. Using data-driven fusion of cortical thickness, surface area, and gray matter density maps (GMD, we found six biologically meaningful patterns showing strong group effects, including four statistically independent multimodal patterns reflecting co-occurring alterations in thickness and GMD in patients, over and above two other independent patterns of widespread thickness and area reduction. Case-control classification using cognitive scores alone revealed high accuracy, and adding imaging features or polygenic risk scores increased performance, suggesting their complementary predictive value with cognitive scores being the most sensitive features. Multivariate pattern analyses reveal distinct patterns of brain morphology in mental disorders, provide insights on the relative importance between brain structure, cognitive and polygenetic risk score in classification of patients, and demonstrate the importance of multivariate approaches in studying the pathophysiological substrate of these complex disorders.

  9. Genetic Differentiation in Insular Lowland Rainforests: Insights from Historical Demographic Patterns in Philippine Birds.

    Science.gov (United States)

    Sánchez-González, Luis Antonio; Hosner, Peter A; Moyle, Robert G

    2015-01-01

    Phylogeographic studies of Philippine birds support that deep genetic structure occurs across continuous lowland forests within islands, despite the lack of obvious contemporary isolation mechanisms. To examine the pattern and tempo of diversification within Philippine island forests, and test if common mechanisms are responsible for observed differentiation, we focused on three co-distributed lowland bird taxa endemic to Greater Luzon and Greater Negros-Panay: Blue-headed Fantail (Rhipidura cyaniceps), White-browed Shama (Copsychus luzoniensis), and Lemon-throated Leaf-Warbler (Phylloscopus cebuensis). Each species has two described subspecies within Greater Luzon, and a single described subspecies on Greater Negros/Panay. Each of the three focal species showed a common geographic pattern of two monophyletic groups in Greater Luzon sister to a third monophyletic group found in Greater Negros-Panay, suggesting that common or similar biogeographic processes may have produced similar distributions. However, studied species displayed variable levels of mitochondrial DNA differentiation between clades, and genetic differentiation within Luzon was not necessarily concordant with described subspecies boundaries. Population genetic parameters for the three species suggested both rapid population growth from small numbers and geographic expansion across Luzon Island. Estimates of the timing of population expansion further supported that these events occurred asynchronously throughout the Pleistocene in the focal species, demanding particular explanations for differentiation, and support that co-distribution may be secondarily congruent.

  10. Simple regional strain pattern analysis to predict response to cardiac resynchronization therapy

    DEFF Research Database (Denmark)

    Risum, Niels; Jons, Christian; Olsen, Niels T

    2012-01-01

    A classical strain pattern of early contraction in one wall and prestretching of the opposing wall followed by late contraction has previously been associated with left bundle branch block (LBBB) activation and short-term response to cardiac resynchronization therapy (CRT). Aims of this study were...... to establish the long-term predictive value of an LBBB-related strain pattern and to identify changes in contraction patterns during short-term and long-term CRT....

  11. Dispersal ability and habitat requirements determine landscape-level genetic patterns in desert aquatic insects.

    Science.gov (United States)

    Phillipsen, Ivan C; Kirk, Emily H; Bogan, Michael T; Mims, Meryl C; Olden, Julian D; Lytle, David A

    2015-01-01

    Species occupying the same geographic range can exhibit remarkably different population structures across the landscape, ranging from highly diversified to panmictic. Given limitations on collecting population-level data for large numbers of species, ecologists seek to identify proximate organismal traits-such as dispersal ability, habitat preference and life history-that are strong predictors of realized population structure. We examined how dispersal ability and habitat structure affect the regional balance of gene flow and genetic drift within three aquatic insects that represent the range of dispersal abilities and habitat requirements observed in desert stream insect communities. For each species, we tested for linear relationships between genetic distances and geographic distances using Euclidean and landscape-based metrics of resistance. We found that the moderate-disperser Mesocapnia arizonensis (Plecoptera: Capniidae) has a strong isolation-by-distance pattern, suggesting migration-drift equilibrium. By contrast, population structure in the flightless Abedus herberti (Hemiptera: Belostomatidae) is influenced by genetic drift, while gene flow is the dominant force in the strong-flying Boreonectes aequinoctialis (Coleoptera: Dytiscidae). The best-fitting landscape model for M. arizonensis was based on Euclidean distance. Analyses also identified a strong spatial scale-dependence, where landscape genetic methods only performed well for species that were intermediate in dispersal ability. Our results highlight the fact that when either gene flow or genetic drift dominates in shaping population structure, no detectable relationship between genetic and geographic distances is expected at certain spatial scales. This study provides insight into how gene flow and drift interact at the regional scale for these insects as well as the organisms that share similar habitats and dispersal abilities. © 2014 John Wiley & Sons Ltd.

  12. Gaming Device Usage Patterns Predict Internet Gaming Disorder: Comparison across Different Gaming Device Usage Patterns

    Science.gov (United States)

    Cho, Hyun; Chun, Ji-Won; Jeong, Jo-Eun; Kim, Dai-Jin

    2017-01-01

    Gaming behaviors have been significantly influenced by smartphones. This study was designed to explore gaming behaviors and clinical characteristics across different gaming device usage patterns and the role of the patterns on Internet gaming disorder (IGD). Responders of an online survey regarding smartphone and online game usage were classified by different gaming device usage patterns: (1) individuals who played only computer games; (2) individuals who played computer games more than smartphone games; (3) individuals who played computer and smartphone games evenly; (4) individuals who played smartphone games more than computer games; (5) individuals who played only smartphone games. Data on demographics, gaming-related behaviors, and scales for Internet and smartphone addiction, depression, anxiety disorder, and substance use were collected. Combined users, especially those who played computer and smartphone games evenly, had higher prevalence of IGD, depression, anxiety disorder, and substance use disorder. These subjects were more prone to develop IGD than reference group (computer only gamers) (B = 0.457, odds ratio = 1.579). Smartphone only gamers had the lowest prevalence of IGD, spent the least time and money on gaming, and showed lowest scores of Internet and smartphone addiction. Our findings suggest that gaming device usage patterns may be associated with the occurrence, course, and prognosis of IGD. PMID:29206183

  13. Gaming Device Usage Patterns Predict Internet Gaming Disorder: Comparison across Different Gaming Device Usage Patterns.

    Science.gov (United States)

    Paik, Soo-Hyun; Cho, Hyun; Chun, Ji-Won; Jeong, Jo-Eun; Kim, Dai-Jin

    2017-12-05

    Gaming behaviors have been significantly influenced by smartphones. This study was designed to explore gaming behaviors and clinical characteristics across different gaming device usage patterns and the role of the patterns on Internet gaming disorder (IGD). Responders of an online survey regarding smartphone and online game usage were classified by different gaming device usage patterns: (1) individuals who played only computer games; (2) individuals who played computer games more than smartphone games; (3) individuals who played computer and smartphone games evenly; (4) individuals who played smartphone games more than computer games; (5) individuals who played only smartphone games. Data on demographics, gaming-related behaviors, and scales for Internet and smartphone addiction, depression, anxiety disorder, and substance use were collected. Combined users, especially those who played computer and smartphone games evenly, had higher prevalence of IGD, depression, anxiety disorder, and substance use disorder. These subjects were more prone to develop IGD than reference group (computer only gamers) (B = 0.457, odds ratio = 1.579). Smartphone only gamers had the lowest prevalence of IGD, spent the least time and money on gaming, and showed lowest scores of Internet and smartphone addiction. Our findings suggest that gaming device usage patterns may be associated with the occurrence, course, and prognosis of IGD.

  14. Gaming Device Usage Patterns Predict Internet Gaming Disorder: Comparison across Different Gaming Device Usage Patterns

    Directory of Open Access Journals (Sweden)

    Soo-Hyun Paik

    2017-12-01

    Full Text Available Gaming behaviors have been significantly influenced by smartphones. This study was designed to explore gaming behaviors and clinical characteristics across different gaming device usage patterns and the role of the patterns on Internet gaming disorder (IGD. Responders of an online survey regarding smartphone and online game usage were classified by different gaming device usage patterns: (1 individuals who played only computer games; (2 individuals who played computer games more than smartphone games; (3 individuals who played computer and smartphone games evenly; (4 individuals who played smartphone games more than computer games; (5 individuals who played only smartphone games. Data on demographics, gaming-related behaviors, and scales for Internet and smartphone addiction, depression, anxiety disorder, and substance use were collected. Combined users, especially those who played computer and smartphone games evenly, had higher prevalence of IGD, depression, anxiety disorder, and substance use disorder. These subjects were more prone to develop IGD than reference group (computer only gamers (B = 0.457, odds ratio = 1.579. Smartphone only gamers had the lowest prevalence of IGD, spent the least time and money on gaming, and showed lowest scores of Internet and smartphone addiction. Our findings suggest that gaming device usage patterns may be associated with the occurrence, course, and prognosis of IGD.

  15. [Analysis of 14 individuals who requested predictive genetic testing for hereditary neuromuscular diseases].

    Science.gov (United States)

    Yoshida, Kunihiro; Tamai, Mariko; Kubota, Takeo; Kawame, Hiroshi; Amano, Naoji; Ikeda, Shu-ichi; Fukushima, Yoshimitsu

    2002-02-01

    Predictive genetic testing for hereditary neuromuscular diseases is a delicate issue for individuals at risk and their families, as well as for medical staff because these diseases are often late-onset and intractable. Therefore careful pre- and post-test genetic counseling and psychosocial support should be provided along with such genetic testing. The Division of Clinical and Molecular Genetics was established at our hospital in May 1996 to provide skilled professional genetic counseling. Since its establishment, 14 individuals have visited our clinic to request predictive genetic testing for hereditary neuromuscular diseases (4 for myotonic dystrophy, 6 for spinocerebellar ataxia, 3 for Huntington's disease, and 1 for Alzheimer's disease). The main reasons for considering testing were to remove uncertainty about the genetic status and to plan for the future. Nine of 14 individuals requested testing for making decisions about a forthcoming marriage or pregnancy (family planning). Other reasons raised by the individuals included career or financial planning, planning for their own health care, and knowing the risk for their children. At the first genetic counseling session, all of the individuals expressed hopes of not being a gene carrier and of escaping from fear of disease, and seemed not to be mentally well prepared for an increased-risk result. To date, 7 of the 14 individuals have received genetic testing and only one, who underwent predictive genetic testing for spinocerebellar ataxia, was given an increased-risk result. The seven individuals including the one with an increased-risk result, have coped well with their new knowledge about their genetic status after the testing results were disclosed. None of them has expressed regret. In pre-test genetic counseling sessions, we consider it quite important not only to determine the psychological status of the individual, but also to make the individual try to anticipate the changes in his/her life upon

  16. Temporal prediction of epidemic patterns in community networks

    International Nuclear Information System (INIS)

    Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Small, Michael

    2013-01-01

    Most previous studies of epidemic dynamics on complex networks suppose that the disease will eventually stabilize at either a disease-free state or an endemic one. In reality, however, some epidemics always exhibit sporadic and recurrent behaviour in one region because of the invasion from an endemic population elsewhere. In this paper we address this issue and study a susceptible–infected–susceptible epidemiological model on a network consisting of two communities, where the disease is endemic in one community but alternates between outbreaks and extinctions in the other. We provide a detailed characterization of the temporal dynamics of epidemic patterns in the latter community. In particular, we investigate the time duration of both outbreak and extinction, and the time interval between two consecutive inter-community infections, as well as their frequency distributions. Based on the mean-field theory, we theoretically analyse these three timescales and their dependence on the average node degree of each community, the transmission parameters and the number of inter-community links, which are in good agreement with simulations, except when the probability of overlaps between successive outbreaks is too large. These findings aid us in better understanding the bursty nature of disease spreading in a local community, and thereby suggesting effective time-dependent control strategies. (paper)

  17. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

    DEFF Research Database (Denmark)

    Baillie, J. Kenneth; Bretherick, Andrew; Haley, Christopher S.

    2018-01-01

    Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcrip...

  18. Into the depth of population genetics: pattern of structuring in mesophotic red coral populations

    Science.gov (United States)

    Costantini, Federica; Abbiati, Marco

    2016-03-01

    Deep-sea reef-building corals are among the most conspicuous invertebrates inhabiting the hard-bottom habitats worldwide and are particularly susceptible to human threats. The precious red coral ( Corallium rubrum, L. 1758) has a wide bathymetric distribution, from shallow up to 800 m depth, and represents a key species in the Mediterranean mesophotic reefs. Several studies have investigated genetic variability in shallow-water red coral populations, while geographic patterns in mesophotic habitats are largely unknown. This study investigated genetic variability of C. rubrum populations dwelling between 55 and 120 m depth, from the Ligurian to the Ionian Sea along about 1500 km of coastline. A total of 18 deep rocky banks were sampled. Colonies were analyzed by means of a set of microsatellite loci and the putative control region of the mitochondrial DNA. Collected data were compared with previous studies. Both types of molecular markers showed high genetic similarity between populations within the northern (Ligurian Sea and Tuscan Archipelago) and the southern (Tyrrhenian and Ionian seas) study areas. Variability in habitat features between the sampling sites did not affect the genetic variability of the populations. Conversely, the patchy distribution of suitable habitats affected populations' connectivity within and among deep coral banks. Based on these results and due to the emphasis on red coral protection in the Mediterranean Sea by international institutions, red coral could be promoted as a `focal species' to develop management plans for the conservation of deep coralligenous reefs, a reservoir of marine biodiversity.

  19. Genetic diversity patterns of arbuscular mycorrhizal fungi associated with the mycoheterotroph Arachnitis uniflora Phil. (Corsiaceae).

    Science.gov (United States)

    Renny, Mauricio; Acosta, M Cristina; Cofré, Noelia; Domínguez, Laura S; Bidartondo, Martin I; Sérsic, Alicia N

    2017-06-01

    Arachnitis uniflora is a mycoheterotrophic plant that exploits arbuscular mycorrhizal fungi of neighbouring plants. We tested A. uniflora 's specificity towards fungi across its large latitudinal range, as well as the role of historical events and current environmental, geographical and altitudinal variables on fungal genetic diversity. Arachnitis uniflora mycorrhizas were sampled at 25 sites. Fungal phylogenetic relationships were reconstructed, genetic diversity was calculated and the main divergent lineages were dated. Phylogeographical analysis was performed with the main fungal clade. Fungal diversity correlations with environmental factors were investigated. Glomeraceae fungi dominated, with a main clade that likely originated in the Upper Cretaceous and diversified in the Miocene. Two other arbuscular mycorrhizal fungal families not previously known to be targeted by A. uniflora were detected rarely and appear to be facultative associations. High genetic diversity, found in Bolivia and both northern and southern Patagonia, was correlated with temperature, rainfall and soil features. Fungal genetic diversity and its distribution can be explained by the ancient evolutionary history of the target fungi and by micro-scale environmental conditions with a geographical mosaic pattern. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  20. Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty.

    Science.gov (United States)

    Du, Lei; Liu, Kefei; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Han, Junwei; Guo, Lei; Saykin, Andrew J; Shen, Li

    2017-10-25

    Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose [Formula: see text]-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the [Formula: see text]-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

  1. Advanced and flexible genetic algorithms for BWR fuel loading pattern optimization

    International Nuclear Information System (INIS)

    Martin-del-Campo, Cecilia; Palomera-Perez, Miguel-Angel; Francois, Juan-Luis

    2009-01-01

    This work proposes advances in the implementation of a flexible genetic algorithm (GA) for fuel loading pattern optimization for Boiling Water Reactors (BWRs). In order to avoid specific implementations of genetic operators and to obtain a more flexible treatment, a binary representation of the solution was implemented; this representation had to take into account that a little change in the genotype must correspond to a little change in the phenotype. An identifier number is assigned to each assembly by means of a Gray Code of 7 bits and the solution (the loading pattern) is represented by a binary chain of 777 bits of length. Another important contribution is the use of a Fitness Function which includes a Heuristic Function and an Objective Function. The Heuristic Function which is defined to give flexibility on the application of a set of positioning rules based on knowledge, and the Objective Function that contains all the parameters which qualify the neutronic and thermal hydraulic performances of each loading pattern. Experimental results illustrating the effectiveness and flexibility of this optimization algorithm are presented and discussed.

  2. Study of Relationship between Genetic Pattern and Susceptibility to Terbinafine in Clinical Isolated of Trichophyton rubrum

    Directory of Open Access Journals (Sweden)

    Fatemeh Hadadi

    2014-06-01

    Full Text Available Background & objectives: Trichophyton rubrum is one of the most common pathogeniccause of dermatophytosis. One of the drugs which have been prescribed widely for fungal infections is terbinafine which belongs to allylamines group of antifungal agents. Recently molecular typing methods have been developed for answering the epidemiological questions and disease recurrence problems. Current study has been conducted on 22 isolates of Trichophyton rubrum obtained from patients randomly. Our aim was the investigation of correlation between genetic pattern and sensitivity to Terbinafine in clinical isolates of Trichophyton rubrum.   Methods: Firstly the genus and species of isolated fungi from patients have been confirmed by macroscopic and microscopic methods, then, the resistance and sensitivity of isolates against drug have been determined using culture medium containing defined amount of drug. In next step fungal DNA has been extracted by RAPD-PCR (random amplified polymorphic DNA with random sequences of 3 primers.   Results: Each primer produced different amplified pattern, and using each 3 primers differences have been observed in genetic pattern of resistant and sensitive samples using each 3 primers, but there was no bond with 100% specificity.   Conclusion: The 12 sensitive isolates which didn’t grow in 0.1 mg concentration of drug, also had limited growth at the low concentration of drug. Ten resistant isolates which grew in 0.1mg/ml of drug, in lower concentration of drug were resisted. RAPD analysis for molecular typing of Trichophyton rubrum seems to be completely suitable.

  3. Application of the distributed genetic algorithm for loading pattern optimization problems

    International Nuclear Information System (INIS)

    Hashimoto, Hiroshi; Yamamoto, Akio

    2000-01-01

    The distributed genetic algorithm (DGA) is applied for loading pattern optimization problems of the pressurized water reactors (PWR). Due to stiff nature of the loading pattern optimizations (e.g. multi-modality and non-linearity), stochastic methods like the simulated annealing or the genetic algorithm (GA) are widely applied for these problems. A basic concept of DGA is based on that of GA. However, DGA equally distributes candidates of solutions (i.e. loading patterns) to several independent 'islands' and evolves them in each island. Migrations of some candidates are performed among islands with a certain period. Since candidates of solutions independently evolve in each island with accepting different genes of migrants from other islands, premature convergence in the traditional GA can be prevented. Because many candidate loading patterns should be evaluated in one generation of GA or DGA, the parallelization in these calculations works efficiently. Parallel efficiency was measured using our optimization code and good load balance was attained even in a heterogeneous cluster environment due to dynamic distribution of the calculation load. The optimization code is based on the client/server architecture with the TCP/IP native socket and a client (optimization module) and calculation server modules communicate the objects of loading patterns each other. Throughout the sensitivity study on optimization parameters of DGA, a suitable set of the parameters for a test problem was identified. Finally, optimization capability of DGA and the traditional GA was compared in the test problem and DGA provided better optimization results than the traditional GA. (author)

  4. Ethical dilemmas in genetic testing: examples from the Cuban program for predictive diagnosis of hereditary ataxias.

    Science.gov (United States)

    Mariño, Tania Cruz; Armiñán, Rubén Reynaldo; Cedeño, Humberto Jorge; Mesa, José Miguel Laffita; Zaldivar, Yanetza González; Rodríguez, Raúl Aguilera; Santos, Miguel Velázquez; Mederos, Luis Enrique Almaguer; Herrera, Milena Paneque; Pérez, Luis Velázquez

    2011-06-01

    Predictive testing protocols are intended to help patients affected with hereditary conditions understand their condition and make informed reproductive choices. However, predictive protocols may expose clinicians and patients to ethical dilemmas that interfere with genetic counseling and the decision making process. This paper describes ethical dilemmas in a series of five cases involving predictive testing for hereditary ataxias in Cuba. The examples herein present evidence of the deeply controversial situations faced by both individuals at risk and professionals in charge of these predictive studies, suggesting a need for expanded guidelines to address such complexities.

  5. Environmental gradients predict the genetic population structure of a coral reef fish in the Red Sea

    KAUST Repository

    Nanninga, Gerrit B.

    2014-01-20

    The relatively recent fields of terrestrial landscape and marine seascape genetics seek to identify the influence of biophysical habitat features on the spatial genetic structure of populations or individuals. Over the last few years, there has been accumulating evidence for the effect of environmental heterogeneity on patterns of gene flow and connectivity in marine systems. Here, we investigate the population genetic patterns of an anemonefish, Amphiprion bicinctus, along the Saudi Arabian coast of the Red Sea. We collected nearly one thousand samples from 19 locations, spanning approximately 1500 km, and genotyped them at 38 microsatellite loci. Patterns of gene flow appeared to follow a stepping-stone model along the northern and central Red Sea, which was disrupted by a distinct genetic break at a latitude of approximately 19°N. The Red Sea is characterized by pronounced environmental gradients along its axis, roughly separating the northern and central from the southern basin. Using mean chlorophyll-a concentrations as a proxy for this gradient, we ran tests of isolation by distance (IBD, R2 = 0.52) and isolation by environment (IBE, R2 = 0.64), as well as combined models using partial Mantel tests and multiple matrix regression with randomization (MMRR). We found that genetic structure across our sampling sites may be best explained by a combined model of IBD and IBE (Mantel: R2 = 0.71, MMRR: R2 = 0.86). Our results highlight the potential key role of environmental patchiness in shaping patterns of gene flow in species with pelagic larval dispersal. We support growing calls for the integration of biophysical habitat characteristics into future studies of population genetic structure. © 2014 John Wiley & Sons Ltd.

  6. Environmental gradients predict the genetic population structure of a coral reef fish in the Red Sea

    KAUST Repository

    Nanninga, Gerrit B.; Saenz Agudelo, Pablo; Manica, Andrea; Berumen, Michael L.

    2014-01-01

    The relatively recent fields of terrestrial landscape and marine seascape genetics seek to identify the influence of biophysical habitat features on the spatial genetic structure of populations or individuals. Over the last few years, there has been accumulating evidence for the effect of environmental heterogeneity on patterns of gene flow and connectivity in marine systems. Here, we investigate the population genetic patterns of an anemonefish, Amphiprion bicinctus, along the Saudi Arabian coast of the Red Sea. We collected nearly one thousand samples from 19 locations, spanning approximately 1500 km, and genotyped them at 38 microsatellite loci. Patterns of gene flow appeared to follow a stepping-stone model along the northern and central Red Sea, which was disrupted by a distinct genetic break at a latitude of approximately 19°N. The Red Sea is characterized by pronounced environmental gradients along its axis, roughly separating the northern and central from the southern basin. Using mean chlorophyll-a concentrations as a proxy for this gradient, we ran tests of isolation by distance (IBD, R2 = 0.52) and isolation by environment (IBE, R2 = 0.64), as well as combined models using partial Mantel tests and multiple matrix regression with randomization (MMRR). We found that genetic structure across our sampling sites may be best explained by a combined model of IBD and IBE (Mantel: R2 = 0.71, MMRR: R2 = 0.86). Our results highlight the potential key role of environmental patchiness in shaping patterns of gene flow in species with pelagic larval dispersal. We support growing calls for the integration of biophysical habitat characteristics into future studies of population genetic structure. © 2014 John Wiley & Sons Ltd.

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

    Directory of Open Access Journals (Sweden)

    Magali Michaut

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

  8. Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification

    Science.gov (United States)

    Korolev, Igor O.; Symonds, Laura L.; Bozoki, Andrea C.

    2016-01-01

    Background Individuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level. Methods Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework. Results Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions. Conclusions We developed an accurate prognostic model for predicting

  9. Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification.

    Directory of Open Access Journals (Sweden)

    Igor O Korolev

    Full Text Available Individuals with mild cognitive impairment (MCI have a substantially increased risk of developing dementia due to Alzheimer's disease (AD. In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139 and those who did not (n = 120 during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87. Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex. Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.We developed an accurate prognostic model for predicting MCI-to-dementia progression

  10. Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

    Science.gov (United States)

    Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

    2018-05-01

    As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

  11. The Impact of Genetic and Non-Genetic Factors on Warfarin Dose Prediction in MENA Region: A Systematic Review.

    Science.gov (United States)

    Bader, Loulia Akram; Elewa, Hazem

    2016-01-01

    Warfarin is the most commonly used oral anticoagulant for the treatment and prevention of thromboembolic disorders. Pharmacogenomics studies have shown that variants in CYP2C9 and VKORC1 genes are strongly and consistently associated with warfarin dose variability. Although different populations from the Middle East and North Africa (MENA) region may share the same ancestry, it is still unclear how they compare in the genetic and non-genetic factors affecting their warfarin dosing. To explore the prevalence of CYP2C9 and VKORC1 variants in MENA, and the effect of these variants along with other non-genetic factors in predicting warfarin dose. In this systematic review, we included observational cross sectional and cohort studies that enrolled patients on stable warfarin dose and had the genetics and non-genetics factors associated with mean warfarin dose as the primary outcome. We searched PubMed, Medline, Scopus, PharmGKB, PHGKB, Google scholar and reference lists of relevant reviews. We identified 17 studies in eight different populations: Iranian, Israeli, Egyptian, Lebanese, Omani, Kuwaiti, Sudanese and Turkish. Most common genetic variant in all populations was the VKORC1 (-1639G>A), with a minor allele frequency ranging from 30% in Egyptians and up to 52% and 56% in Lebanese and Iranian, respectively. Variants in the CYP2C9 were less common, with the highest MAF for CYP2C9*2 among Iranians (27%). Variants in the VKORC1 and CYP2C9 were the most significant predictors of warfarin dose in all populations. Along with other genetic and non-genetic factors, they explained up to 63% of the dose variability in Omani and Israeli patients. Variants of VKORC1 and CYP2C9 are the strongest predictors of warfarin dose variability among the different populations from MENA. Although many of those populations share the same ancestry and are similar in their warfarin dose predictors, a population specific dosing algorithm is needed for the prospective estimation of warfarin

  12. Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm

    Science.gov (United States)

    Mundher Yaseen, Zaher; Abdulmohsin Afan, Haitham; Tran, Minh-Tung

    2018-04-01

    Scientifically evidenced that beam-column joints are a critical point in the reinforced concrete (RC) structure under the fluctuation loads effects. In this novel hybrid data-intelligence model developed to predict the joint shear behavior of exterior beam-column structure frame. The hybrid data-intelligence model is called genetic algorithm integrated with deep learning neural network model (GA-DLNN). The genetic algorithm is used as prior modelling phase for the input approximation whereas the DLNN predictive model is used for the prediction phase. To demonstrate this structural problem, experimental data is collected from the literature that defined the dimensional and specimens’ properties. The attained findings evidenced the efficitveness of the hybrid GA-DLNN in modelling beam-column joint shear problem. In addition, the accurate prediction achived with less input variables owing to the feasibility of the evolutionary phase.

  13. "Eyeball test" of thermographic patterns for predicting a successful lateral infraclavicular block.

    Science.gov (United States)

    Andreasen, Asger M; Linnet, Karen E; Asghar, Semera; Rothe, Christian; Rosenstock, Charlotte V; Lange, Kai H W; Lundstrøm, Lars H

    2017-11-01

    Increased distal skin temperature can be used to predict the success of lateral infraclavicular (LIC) block. We hypothesized that an "eyeball test" of specific infrared thermographic patterns after LIC block could be used to determine block success. In this observational study, five observers trained in four distinct thermographic patterns independently evaluated thermographic images of the hands of 40 patients at baseline and at one-minute intervals for 30 min after a LIC block. Sensitivity, specificity, and predictive values of a positive and a negative test were estimated to evaluate the validity of specific thermographic patterns for predicting a successful block. Sensory and motor block of the musculocutaneous, radial, ulnar, and median nerves defined block success. Fleiss' kappa statistics of multiple interobserver agreements were used to evaluate reliability. As a diagnostic test, the defined specific thermographic patterns of the hand predicted a successful block with increasing accuracy over the 30-min observation period. Block success was predicted with a sensitivity of 92.4% (95% confidence interval [CI], 86.8 to 96.2) and with a specificity of 84.0% (95% CI, 70.3 to 92.4) at min 30. The Fleiss' kappa for the five observers was 0.87 (95% CI, 0.77 to 0.96). We conclude that visual evaluation by an eyeball test of specific thermographic patterns of the blocked hands may be useful as a valid and reliable diagnostic test for predicting a successful LIC block.

  14. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    Science.gov (United States)

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2017-09-01

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. The DNA of coral reef biodiversity: predicting and protecting genetic diversity of reef assemblages.

    Science.gov (United States)

    Selkoe, Kimberly A; Gaggiotti, Oscar E; Treml, Eric A; Wren, Johanna L K; Donovan, Mary K; Toonen, Robert J

    2016-04-27

    Conservation of ecological communities requires deepening our understanding of genetic diversity patterns and drivers at community-wide scales. Here, we use seascape genetic analysis of a diversity metric, allelic richness (AR), for 47 reef species sampled across 13 Hawaiian Islands to empirically demonstrate that large reefs high in coral cover harbour the greatest genetic diversity on average. We found that a species's life history (e.g. depth range and herbivory) mediates response of genetic diversity to seascape drivers in logical ways. Furthermore, a metric of combined multi-species AR showed strong coupling to species richness and habitat area, quality and stability that few species showed individually. We hypothesize that macro-ecological forces and species interactions, by mediating species turnover and occupancy (and thus a site's mean effective population size), influence the aggregate genetic diversity of a site, potentially allowing it to behave as an apparent emergent trait that is shaped by the dominant seascape drivers. The results highlight inherent feedbacks between ecology and genetics, raise concern that genetic resilience of entire reef communities is compromised by factors that reduce coral cover or available habitat, including thermal stress, and provide a foundation for new strategies for monitoring and preserving biodiversity of entire reef ecosystems. © 2016 The Authors.

  16. Complex patterns of genetic and phenotypic divergence in an island bird and the consequences for delimiting conservation units.

    Science.gov (United States)

    Phillimore, A B; Owens, I P F; Black, R A; Chittock, J; Burke, T; Clegg, S M

    2008-06-01

    Substantial phenotypic and genetic variation is often found below the species level and this may be useful in quantifying biodiversity and predicting future diversification. However, relatively few studies have tested whether different aspects of intraspecific variation show congruent patterns across populations. Here, we quantify several aspects of divergence between 13 insular populations of an island endemic bird, the Vanuatu white-eye (Zosterops flavifrons). The components of divergence studied are mitochondrial DNA (mtDNA), nuclear DNA microsatellites and morphology. These different aspects of divergence present subtly different scenarios. For instance, an mtDNA phylogenetic tree reveals a potential cryptic species on the most southerly island in Vanuatu and considerable divergence between at least two other major phylogroups. Microsatellite loci suggest that population genetic divergence between insular populations, both between and within phylogroups, is substantial, a result that is consistent with a low level of interisland gene flow. Finally, most populations were found to be strongly morphologically divergent, but no single population was morphologically diagnosable from all others. Taken together, our results show that, although many measures of divergence are concordant in this system, the number of divergent units identified varies widely depending on the characters considered and approach used. A continuum of divergence and a degree of discordance between different characters are both to be expected under simple models of evolution, but they present problems in terms of delimiting conservation units.

  17. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

    Directory of Open Access Journals (Sweden)

    Ronald de Vlaming

    2015-01-01

    Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  18. Spatial extent of analysis influences observed patterns of population genetic structure in a widespread darter species (Percidae)

    Science.gov (United States)

    Argentina, Jane E.; Angermeier, Paul L.; Hallerman, Eric M.; Welsh, Stuart A.

    2018-01-01

    Connectivity among stream fish populations allows for exchange of genetic material and helps maintain genetic diversity, adaptive potential and population stability over time. Changes in species demographics and population connectivity have the potential to permanently alter the genetic patterns of stream fish, although these changes through space and time are variable and understudied in small‐bodied freshwater fish.As a spatially widespread, common species of benthic freshwater fish, the variegate darter (Etheostoma variatum) is a model species for documenting how patterns of genetic structure and diversity respond to increasing isolation due to large dams and how scale of study may shape our understanding of these patterns. We sampled variegate darters from 34 sites across their range in the North American Ohio River basin and examined how patterns of genetic structure and diversity within and between populations responded to historical population changes and dams within and between populations.Spatial scale and configuration of genetic structure varied across the eight identified populations, from tributaries within a watershed, to a single watershed, to multiple watersheds that encompass Ohio River mainstem habitats. This multiwatershed pattern of population structuring suggests genetic dispersal across large distances was and may continue to be common, although some populations remain isolated despite no apparent structural dispersal barriers. Populations with low effective population sizes and evidence of past population bottlenecks showed low allelic richness, but diversity patterns were not related to watershed size, a surrogate for habitat availability. Pairwise genetic differentiation (FST) increased with fluvial distance and was related to both historic and contemporary processes. Genetic diversity changes were influenced by underlying population size and stability, and while instream barriers were not strong determinants of genetic structuring or

  19. Ngram-derived pattern recognition for the detection and prediction of epileptic seizures.

    Directory of Open Access Journals (Sweden)

    Amir Eftekhar

    Full Text Available This work presents a new method that combines symbol dynamics methodologies with an Ngram algorithm for the detection and prediction of epileptic seizures. The presented approach specifically applies Ngram-based pattern recognition, after data pre-processing, with similarity metrics, including the Hamming distance and Needlman-Wunsch algorithm, for identifying unique patterns within epochs of time. Pattern counts within each epoch are used as measures to determine seizure detection and prediction markers. Using 623 hours of intracranial electrocorticogram recordings from 21 patients containing a total of 87 seizures, the sensitivity and false prediction/detection rates of this method are quantified. Results are quantified using individual seizures within each case for training of thresholds and prediction time windows. The statistical significance of the predictive power is further investigated. We show that the method presented herein, has significant predictive power in up to 100% of temporal lobe cases, with sensitivities of up to 70-100% and low false predictions (dependant on training procedure. The cases of highest false predictions are found in the frontal origin with 0.31-0.61 false predictions per hour and with significance in 18 out of 21 cases. On average, a prediction sensitivity of 93.81% and false prediction rate of approximately 0.06 false predictions per hour are achieved in the best case scenario. This compares to previous work utilising the same data set that has shown sensitivities of up to 40-50% for a false prediction rate of less than 0.15/hour.

  20. Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle.

    Science.gov (United States)

    Yin, T; Pinent, T; Brügemann, K; Simianer, H; König, S

    2015-08-01

    This study presents an approach combining phenotypes from novel traits, deterministic equations from cattle nutrition, and stochastic simulation techniques from animal breeding to generate test-day methane emissions (MEm) of dairy cows. Data included test-day production traits (milk yield, fat percentage, protein percentage, milk urea nitrogen), conformation traits (wither height, hip width, body condition score), female fertility traits (days open, calving interval, stillbirth), and health traits (clinical mastitis) from 961 first lactation Brown Swiss cows kept on 41 low-input farms in Switzerland. Test-day MEm were predicted based on the traits from the current data set and 2 deterministic prediction equations, resulting in the traits labeled MEm1 and MEm2. Stochastic simulations were used to assign individual concentrate intake in dependency of farm-type specifications (requirement when calculating MEm2). Genetic parameters for MEm1 and MEm2 were estimated using random regression models. Predicted MEm had moderate heritabilities over lactation and ranged from 0.15 to 0.37, with highest heritabilities around DIM 100. Genetic correlations between MEm1 and MEm2 ranged between 0.91 and 0.94. Antagonistic genetic correlations in the range from 0.70 to 0.92 were found for the associations between MEm2 and milk yield. Genetic correlations between MEm with days open and with calving interval increased from 0.10 at the beginning to 0.90 at the end of lactation. Genetic relationships between MEm2 and stillbirth were negative (0 to -0.24) from the beginning to the peak phase of lactation. Positive genetic relationships in the range from 0.02 to 0.49 were found between MEm2 with clinical mastitis. Interpretation of genetic (co)variance components should also consider the limitations when using data generated by prediction equations. Prediction functions only describe that part of MEm which is dependent on the factors and effects included in the function. With high

  1. Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

    Science.gov (United States)

    The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

  2. Genetic Counseling and Cardiac Care in Predictively Tested Hypertrophic Cardiomyopathy Mutation Carriers: The Patients' Perspective

    NARCIS (Netherlands)

    Christiaans, Imke; van Langen, Irene M.; Birnie, Erwin; Bonsel, Gouke J.; Wilde, Arthur A. M.; Smets, Ellen M. A.

    2009-01-01

    Hypertrophic cardiomyopathy (HCM) is a common hereditary heart disease associated with sudden cardiac death. predictive genetic counseling and testing are performed using adapted Huntington guidelines, that is, psychosocial care and time for reflection are not obligatory and the test result can be

  3. Genetic vulnerability interacts with parenting and early care education to predict increasing externalizing behavior.

    Science.gov (United States)

    Lipscomb, Shannon T; Laurent, Heidemarie; Neiderhiser, Jenae M; Shaw, Daniel S; Natsuaki, Misaki N; Reiss, David; Leve, Leslie D

    2014-01-01

    The current study examined interactions among genetic influences and children's early environments on the development of externalizing behaviors from 18 months to 6 years of age. Participants included 233 families linked through adoption (birth parents and adoptive families). Genetic influences were assessed by birth parent temperamental regulation. Early environments included both family (overreactive parenting) and out-of-home factors (center-based Early Care and Education; ECE). Overreactive parenting predicted more child externalizing behaviors. Attending center-based ECE was associated with increasing externalizing behaviors only for children with genetic liability for dysregulation. Additionally, children who were at risk for externalizing behaviors due to both genetic variability and exposure to center-based ECE were more sensitive to the effects of overreactive parenting on externalizing behavior than other children.

  4. Factors Motivating Individuals to Consider Genetic Testing for Type 2 Diabetes Risk Prediction.

    Directory of Open Access Journals (Sweden)

    Jennifer Wessel

    Full Text Available The purpose of this study was to identify attitudes and perceptions of willingness to participate in genetic testing for type 2 diabetes (T2D risk prediction in the general population. Adults (n = 598 were surveyed on attitudes about utilizing genetic testing to predict future risk of T2D. Participants were recruited from public libraries (53%, online registry (37% and a safety net hospital emergency department (10%. Respondents were 37 ± 11 years old, primarily White (54%, female (69%, college educated (46%, with an annual income ≥$25,000 (56%. Half of participants were interested in genetic testing for T2D (52% and 81% agreed/strongly agreed genetic testing should be available to the public. Only 57% of individuals knew T2D is preventable. A multivariate model to predict interest in genetic testing was adjusted for age, gender, recruitment location and BMI; significant predictors were motivation (high perceived personal risk of T2D [OR = 4.38 (1.76, 10.9]; family history [OR = 2.56 (1.46, 4.48]; desire to know risk prior to disease onset [OR = 3.25 (1.94, 5.42]; and knowing T2D is preventable [OR = 2.11 (1.24, 3.60], intention (if the cost is free [OR = 10.2 (4.27, 24.6]; and learning T2D is preventable [OR = 5.18 (1.95, 13.7] and trust of genetic testing results [OR = 0.03 (0.003, 0.30]. Individuals are interested in genetic testing for T2D risk which offers unique information that is personalized. Financial accessibility, validity of the test and availability of diabetes prevention programs were identified as predictors of interest in T2D testing.

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

    Science.gov (United States)

    He, Dan; Kuhn, David; Parida, Laxmi

    2016-06-15

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

  6. Identifying shared genetic structure patterns among Pacific Northwest forest taxa: insights from use of visualization tools and computer simulations.

    Directory of Open Access Journals (Sweden)

    Mark P Miller

    2010-10-01

    Full Text Available Identifying causal relationships in phylogeographic and landscape genetic investigations is notoriously difficult, but can be facilitated by use of multispecies comparisons.We used data visualizations to identify common spatial patterns within single lineages of four taxa inhabiting Pacific Northwest forests (northern spotted owl: Strix occidentalis caurina; red tree vole: Arborimus longicaudus; southern torrent salamander: Rhyacotriton variegatus; and western white pine: Pinus monticola. Visualizations suggested that, despite occupying the same geographical region and habitats, species responded differently to prevailing historical processes. S. o. caurina and P. monticola demonstrated directional patterns of spatial genetic structure where genetic distances and diversity were greater in southern versus northern locales. A. longicaudus and R. variegatus displayed opposite patterns where genetic distances were greater in northern versus southern regions. Statistical analyses of directional patterns subsequently confirmed observations from visualizations. Based upon regional climatological history, we hypothesized that observed latitudinal patterns may have been produced by range expansions. Subsequent computer simulations confirmed that directional patterns can be produced by expansion events.We discuss phylogeographic hypotheses regarding historical processes that may have produced observed patterns. Inferential methods used here may become increasingly powerful as detailed simulations of organisms and historical scenarios become plausible. We further suggest that inter-specific comparisons of historical patterns take place prior to drawing conclusions regarding effects of current anthropogenic change within landscapes.

  7. Evolutionary and demographic processes shaping geographic patterns of genetic diversity in a keystone species, the African forest elephant (Loxodonta cyclotis).

    Science.gov (United States)

    Ishida, Yasuko; Gugala, Natalie A; Georgiadis, Nicholas J; Roca, Alfred L

    2018-05-01

    The past processes that have shaped geographic patterns of genetic diversity may be difficult to infer from current patterns. However, in species with sex differences in dispersal, differing phylogeographic patterns between mitochondrial (mt) and nuclear (nu) DNA may provide contrasting insights into past events. Forest elephants ( Loxodonta cyclotis ) were impacted by climate and habitat change during the Pleistocene, which likely shaped phylogeographic patterns in mitochondrial (mt) DNA that have persisted due to limited female dispersal. By contrast, the nuclear (nu) DNA phylogeography of forest elephants in Central Africa has not been determined. We therefore examined the population structure of Central African forest elephants by genotyping 94 individuals from six localities at 21 microsatellite loci. Between forest elephants in western and eastern Congolian forests, there was only modest genetic differentiation, a pattern highly discordant with that of mtDNA. Nuclear genetic patterns are consistent with isolation by distance. Alternatively, male-mediated gene flow may have reduced the previous regional differentiation in Central Africa suggested by mtDNA patterns, which likely reflect forest fragmentation during the Pleistocene. In species like elephants, male-mediated gene flow erases the nuclear genetic signatures of past climate and habitat changes, but these continue to persist as patterns in mtDNA because females do not disperse. Conservation implications of these results are discussed.

  8. Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Xiaochen Zhang

    2017-01-01

    Full Text Available To predict the remaining life of ball screw, a screw remaining life prediction method based on quantum genetic algorithm (QGA and support vector machine (SVM is proposed. A screw accelerated test bench is introduced. Accelerometers are installed to monitor the performance degradation of ball screw. Combined with wavelet packet decomposition and isometric mapping (Isomap, the sensitive feature vectors are obtained and stored in database. Meanwhile, the sensitive feature vectors are randomly chosen from the database and constitute training samples and testing samples. Then the optimal kernel function parameter and penalty factor of SVM are searched with the method of QGA. Finally, the training samples are used to train optimized SVM while testing samples are adopted to test the prediction accuracy of the trained SVM so the screw remaining life prediction model can be got. The experiment results show that the screw remaining life prediction model could effectively predict screw remaining life.

  9. Melanoma risk prediction using a multilocus genetic risk score in the Women's Health Initiative cohort.

    Science.gov (United States)

    Cho, Hyunje G; Ransohoff, Katherine J; Yang, Lingyao; Hedlin, Haley; Assimes, Themistocles; Han, Jiali; Stefanick, Marcia; Tang, Jean Y; Sarin, Kavita Y

    2018-07-01

    Single-nucleotide polymorphisms (SNPs) associated with melanoma have been identified though genome-wide association studies. However, the combined impact of these SNPs on melanoma development remains unclear, particularly in postmenopausal women who carry a lower melanoma risk. We examine the contribution of a combined polygenic risk score on melanoma development in postmenopausal women. Genetic risk scores were calculated using 21 genome-wide association study-significant SNPs. Their combined effect on melanoma development was evaluated in 19,102 postmenopausal white women in the clinical trial and observational study arms of the Women's Health Initiative dataset. Compared to the tertile of weighted genetic risk score with the lowest genetic risk, the women in the tertile with the highest genetic risk were 1.9 times more likely to develop melanoma (95% confidence interval 1.50-2.42). The incremental change in c-index from adding genetic risk scores to age were 0.075 (95% confidence interval 0.041-0.109) for incident melanoma. Limitations include a lack of information on nevi count, Fitzpatrick skin type, family history of melanoma, and potential reporting and selection bias in the Women's Health Initiative cohort. Higher genetic risk is associated with increased melanoma prevalence and incidence in postmenopausal women, but current genetic information may have a limited role in risk prediction when phenotypic information is available. Copyright © 2018 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

  10. Retrospective lifetime dietary patterns predict cognitive performance in community-dwelling older Australians.

    Science.gov (United States)

    Hosking, Diane E; Nettelbeck, Ted; Wilson, Carlene; Danthiir, Vanessa

    2014-07-28

    Dietary intake is a modifiable exposure that may have an impact on cognitive outcomes in older age. The long-term aetiology of cognitive decline and dementia, however, suggests that the relevance of dietary intake extends across the lifetime. In the present study, we tested whether retrospective dietary patterns from the life periods of childhood, early adulthood, adulthood and middle age predicted cognitive performance in a cognitively healthy sample of 352 older Australian adults >65 years. Participants completed the Lifetime Diet Questionnaire and a battery of cognitive tests designed to comprehensively assess multiple cognitive domains. In separate regression models, lifetime dietary patterns were the predictors of cognitive factor scores representing ten constructs derived by confirmatory factor analysis of the cognitive test battery. All regression models were progressively adjusted for the potential confounders of current diet, age, sex, years of education, English as native language, smoking history, income level, apoE ɛ4 status, physical activity, other past dietary patterns and health-related variables. In the adjusted models, lifetime dietary patterns predicted cognitive performance in this sample of older adults. In models additionally adjusted for intake from the other life periods and mechanistic health-related variables, dietary patterns from the childhood period alone reached significance. Higher consumption of the 'coffee and high-sugar, high-fat extras' pattern predicted poorer performance on simple/choice reaction time, working memory, retrieval fluency, short-term memory and reasoning. The 'vegetable and non-processed' pattern negatively predicted simple/choice reaction time, and the 'traditional Australian' pattern positively predicted perceptual speed and retrieval fluency. Identifying early-life dietary antecedents of older-age cognitive performance contributes to formulating strategies for delaying or preventing cognitive decline.

  11. Mediterranean Dietary Pattern Adherence Modify the Association between FTO Genetic Variations and Obesity Phenotypes

    Directory of Open Access Journals (Sweden)

    Firoozeh Hosseini-Esfahani

    2017-09-01

    Full Text Available There is increasing interest of which dietary patterns can modify the association of fat mass and obesity associated (FTO variants with obesity. This study was aimed at investigating the interaction of the Mediterranean dietary pattern (Med Diet with FTO polymorphisms in relation to obesity phenotypes. Subjects of this nested case-control study were selected from the Tehran Lipid and Glucose Study participants. Each case was individually matched with a normal weight control (n = 1254. Selected polymorphisms (rs1421085, rs1121980, rs17817449, rs8050136, rs9939973, and rs3751812 were genotyped. Genetic risk score (GRS were calculated using the weighted method. The Mediterranean dietary score (MDS was computed. Individuals with minor allele carriers of rs9939973, rs8050136, rs1781749, and rs3751812 had lower risk of obesity when they had higher MDS, compared to wild-type homozygote genotype carriers. The obesity risk was decreased across quartiles of MDS in participants with high GRS (OR: 1, 0.8, 0.79, 0.67 compared to individuals with low GRS (OR: 1.33, 1.06, 0.97, 1.12 (Pinteraction < 0.05. No significant interaction between the GRS and MDS on abdominal obesity was found. A higher Med Diet adherence was associated with lower obesity risk in subjects with more genetic predisposition to obesity, compared to those with lower adherence to the Med Diet and lower GRS.

  12. Multicycle Optimization of Advanced Gas-Cooled Reactor Loading Patterns Using Genetic Algorithms

    International Nuclear Information System (INIS)

    Ziver, A. Kemal; Carter, Jonathan N.; Pain, Christopher C.; Oliveira, Cassiano R.E. de; Goddard, Antony J. H.; Overton, Richard S.

    2003-01-01

    A genetic algorithm (GA)-based optimizer (GAOPT) has been developed for in-core fuel management of advanced gas-cooled reactors (AGRs) at HINKLEY B and HARTLEPOOL, which employ on-load and off-load refueling, respectively. The optimizer has been linked to the reactor analysis code PANTHER for the automated evaluation of loading patterns in a two-dimensional geometry, which is collapsed from the three-dimensional reactor model. GAOPT uses a directed stochastic (Monte Carlo) algorithm to generate initial population members, within predetermined constraints, for use in GAs, which apply the standard genetic operators: selection by tournament, crossover, and mutation. The GAOPT is able to generate and optimize loading patterns for successive reactor cycles (multicycle) within acceptable CPU times even on single-processor systems. The algorithm allows radial shuffling of fuel assemblies in a multicycle refueling optimization, which is constructed to aid long-term core management planning decisions. This paper presents the application of the GA-based optimization to two AGR stations, which apply different in-core management operational rules. Results obtained from the testing of GAOPT are discussed

  13. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

    Science.gov (United States)

    Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

    2007-01-01

    To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

  14. Crystal structure prediction of flexible molecules using parallel genetic algorithms with a standard force field.

    Science.gov (United States)

    Kim, Seonah; Orendt, Anita M; Ferraro, Marta B; Facelli, Julio C

    2009-10-01

    This article describes the application of our distributed computing framework for crystal structure prediction (CSP) the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of flexible molecules using the general Amber force field (GAFF) and the CHARMM program. The MGAC distributed computing framework includes a series of tightly integrated computer programs for generating the molecule's force field, sampling crystal structures using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential. Copyright 2009 Wiley Periodicals, Inc.

  15. Genetic evidence for a worldwide chaotic dispersion pattern of the arbovirus vector, Aedes albopictus.

    Directory of Open Access Journals (Sweden)

    Mosè Manni

    2017-01-01

    Full Text Available Invasive species represent a global concern for their rapid spread and the possibility of infectious disease transmission. This is the case of the global invader Aedes albopictus, the Asian tiger mosquito. This species is a vector of medically important arboviruses, notably chikungunya (CHIKV, dengue (DENV and Zika (ZIKV. The reconstruction of the complex colonization pattern of this mosquito has great potential for mitigating its spread and, consequently, disease risks.Classical population genetics analyses and Approximate Bayesian Computation (ABC approaches were combined to disentangle the demographic history of Aedes albopictus populations from representative countries in the Southeast Asian native range and in the recent and more recently colonized areas. In Southeast Asia, the low differentiation and the high co-ancestry values identified among China, Thailand and Japan indicate that, in the native range, these populations maintain high genetic connectivity, revealing their ancestral common origin. China appears to be the oldest population. Outside Southeast Asia, the invasion process in La Réunion, America and the Mediterranean Basin is primarily supported by a chaotic propagule distribution, which cooperates in maintaining a relatively high genetic diversity within the adventive populations.From our data, it appears that independent and also trans-continental introductions of Ae. albopictus may have facilitated the rapid establishment of adventive populations through admixture of unrelated genomes. As a consequence, a great amount of intra-population variability has been detected, and it is likely that this variability may extend to the genetic mechanisms controlling vector competence. Thus, in the context of the invasion process of this mosquito, it is possible that both population ancestry and admixture contribute to create the conditions for the efficient transmission of arboviruses and for outbreak establishment.

  16. Dynamical patterning modules: physico-genetic determinants of morphological development and evolution

    International Nuclear Information System (INIS)

    Newman, Stuart A; Bhat, Ramray

    2008-01-01

    The shapes and forms of multicellular organisms arise by the generation of new cell states and types and changes in the numbers and rearrangements of the various kinds of cells. While morphogenesis and pattern formation in all animal species are widely recognized to be mediated by the gene products of an evolutionarily conserved 'developmental-genetic toolkit', the link between these molecular players and the physics underlying these processes has been generally ignored. This paper introduces the concept of 'dynamical patterning modules' (DPMs), units consisting of one or more products of the 'toolkit' genes that mobilize physical processes characteristic of chemically and mechanically excitable meso- to macroscopic systems such as cell aggregates: cohesion, viscoelasticity, diffusion, spatiotemporal heterogeneity based on lateral inhibition and multistable and oscillatory dynamics. We suggest that ancient toolkit gene products, most predating the emergence of multicellularity, assumed novel morphogenetic functions due to change in the scale and context inherent to multicellularity. We show that DPMs, acting individually and in concert with each other, constitute a 'pattern language' capable of generating all metazoan body plans and organ forms. The physical dimension of developmental causation implies that multicellular forms during the explosive radiation of animal body plans in the middle Cambrian, approximately 530 million years ago, could have explored an extensive morphospace without concomitant genotypic change or selection for adaptation. The morphologically plastic body plans and organ forms generated by DPMs, and their ontogenetic trajectories, would subsequently have been stabilized and consolidated by natural selection and genetic drift. This perspective also solves the apparent 'molecular homology-analogy paradox', whereby widely divergent modern animal types utilize the same molecular toolkit during development by proposing, in contrast to the Neo

  17. Intraspecific morphological and genetic variation of common species predicts ranges of threatened ones

    Science.gov (United States)

    Fuller, Trevon L.; Thomassen, Henri A.; Peralvo, Manuel; Buermann, Wolfgang; Milá, Borja; Kieswetter, Charles M.; Jarrín-V, Pablo; Devitt, Susan E. Cameron; Mason, Eliza; Schweizer, Rena M.; Schlunegger, Jasmin; Chan, Janice; Wang, Ophelia; Schneider, Christopher J.; Pollinger, John P.; Saatchi, Sassan; Graham, Catherine H.; Wayne, Robert K.; Smith, Thomas B.

    2013-01-01

    Predicting where threatened species occur is useful for making informed conservation decisions. However, because they are usually rare, surveying threatened species is often expensive and time intensive. Here, we show how regions where common species exhibit high genetic and morphological divergence among populations can be used to predict the occurrence of species of conservation concern. Intraspecific variation of common species of birds, bats and frogs from Ecuador were found to be a significantly better predictor for the occurrence of threatened species than suites of environmental variables or the occurrence of amphibians and birds. Fully 93 per cent of the threatened species analysed had their range adequately represented by the geographical distribution of the morphological and genetic variation found in seven common species. Both higher numbers of threatened species and greater genetic and morphological variation of common species occurred along elevation gradients. Higher levels of intraspecific divergence may be the result of disruptive selection and/or introgression along gradients. We suggest that collecting data on genetic and morphological variation in common species can be a cost effective tool for conservation planning, and that future biodiversity inventories include surveying genetic and morphological data of common species whenever feasible. PMID:23595273

  18. Predictive Psychiatric Genetic Testing in Minors: An Exploration of the Non-Medical Benefits.

    Science.gov (United States)

    Manzini, Arianna; Vears, Danya F

    2018-03-01

    Predictive genetic testing for susceptibility to psychiatric conditions is likely to become part of standard practice. Because the onset of most psychiatric diseases is in late adolescence or early adulthood, testing minors could lead to early identification that may prevent or delay the development of these disorders. However, due to their complex aetiology, psychiatric genetic testing does not provide the immediate medical benefits that current guidelines require for testing minors. While several authors have argued non-medical benefits may play a crucial role in favour of predictive testing for other conditions, little research has explored such a role in psychiatric disorders. This paper outlines the potential non-medical benefits and harms of psychiatric genetic testing in minors in order to consider whether the non-medical benefits could ever make such testing appropriate. Five non-medical themes arise in the literature: psychological impacts, autonomy/self-determination, implications of the biomedical approach, use of financial and intellectual resources, and discrimination. Non-medical benefits were prominent in all of them, suggesting that psychiatric genetic testing in minors may be appropriate in some circumstances. Further research needs to empirically assess these potential non-medical benefits, incorporate minors in the debate, and include normative reflection to evaluate the very purposes and motivations of psychiatric genetic testing in minors.

  19. Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

    Science.gov (United States)

    Wang, D; Salah El-Basyoni, I; Stephen Baenziger, P; Crossa, J; Eskridge, K M; Dweikat, I

    2012-11-01

    Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.

  20. Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses.

    Science.gov (United States)

    Lehermeier, Christina; Teyssèdre, Simon; Schön, Chris-Carolin

    2017-12-01

    A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs. Copyright © 2017 by the Genetics Society of America.

  1. Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

    Directory of Open Access Journals (Sweden)

    Guosheng Su

    Full Text Available 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.

  2. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio

    2013-10-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  3. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio; Cannistraci, Carlo; Ravasi, Timothy

    2013-01-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  4. Genetic structuring and migration patterns of Atlantic bigeye tuna, Thunnus obesus (Lowe, 1839

    Directory of Open Access Journals (Sweden)

    Beerli Peter

    2008-09-01

    Full Text Available Abstract Background Large pelagic fishes are generally thought to have little population genetic structuring based on their cosmopolitan distribution, large population sizes and high dispersal capacities. However, gene flow can be influenced by ecological (e.g. homing behaviour and physical (e.g. present-day ocean currents, past changes in sea temperature and levels factors. In this regard, Atlantic bigeye tuna shows an interesting genetic structuring pattern with two highly divergent mitochondrial clades (Clades I and II, which are assumed to have been originated during the last Pleistocene glacial maxima. We assess genetic structure patterns of Atlantic bigeye tuna at the nuclear level, and compare them with mitochondrial evidence. Results We examined allele size variation of nine microsatellite loci in 380 individuals from the Gulf of Guinea, Canary, Azores, Canada, Indian Ocean, and Pacific Ocean. To investigate temporal stability of genetic structure, three Atlantic Ocean sites were re-sampled a second year. Hierarchical AMOVA tests, RST pairwise comparisons, isolation by distance (Mantel tests, Bayesian clustering analyses, and coalescence-based migration rate inferences supported unrestricted gene flow within the Atlantic Ocean at the nuclear level, and therefore interbreeding between individuals belonging to both mitochondrial clades. Moreover, departures from HWE in several loci were inferred for the samples of Guinea, and attributed to a Wahlund effect supporting the role of this region as a spawning and nursery area. Our microsatellite data supported a single worldwide panmictic unit for bigeye tunas. Despite the strong Agulhas Current, immigration rates seem to be higher from the Atlantic Ocean into the Indo-Pacific Ocean, but the actual number of individuals moving per generation is relatively low compared to the large population sizes inhabiting each ocean basin. Conclusion Lack of congruence between mt and nuclear evidences, which

  5. Genetic structuring and migration patterns of Atlantic bigeye tuna, Thunnus obesus (Lowe, 1839).

    Science.gov (United States)

    Gonzalez, Elena G; Beerli, Peter; Zardoya, Rafael

    2008-09-17

    Large pelagic fishes are generally thought to have little population genetic structuring based on their cosmopolitan distribution, large population sizes and high dispersal capacities. However, gene flow can be influenced by ecological (e.g. homing behaviour) and physical (e.g. present-day ocean currents, past changes in sea temperature and levels) factors. In this regard, Atlantic bigeye tuna shows an interesting genetic structuring pattern with two highly divergent mitochondrial clades (Clades I and II), which are assumed to have been originated during the last Pleistocene glacial maxima. We assess genetic structure patterns of Atlantic bigeye tuna at the nuclear level, and compare them with mitochondrial evidence. We examined allele size variation of nine microsatellite loci in 380 individuals from the Gulf of Guinea, Canary, Azores, Canada, Indian Ocean, and Pacific Ocean. To investigate temporal stability of genetic structure, three Atlantic Ocean sites were re-sampled a second year. Hierarchical AMOVA tests, RST pairwise comparisons, isolation by distance (Mantel) tests, Bayesian clustering analyses, and coalescence-based migration rate inferences supported unrestricted gene flow within the Atlantic Ocean at the nuclear level, and therefore interbreeding between individuals belonging to both mitochondrial clades. Moreover, departures from HWE in several loci were inferred for the samples of Guinea, and attributed to a Wahlund effect supporting the role of this region as a spawning and nursery area. Our microsatellite data supported a single worldwide panmictic unit for bigeye tunas. Despite the strong Agulhas Current, immigration rates seem to be higher from the Atlantic Ocean into the Indo-Pacific Ocean, but the actual number of individuals moving per generation is relatively low compared to the large population sizes inhabiting each ocean basin. Lack of congruence between mt and nuclear evidences, which is also found in other species, most likely reflects

  6. Genetic Dissection of Dual Roles for the Transcription Factor six7 in Photoreceptor Development and Patterning in Zebrafish.

    Directory of Open Access Journals (Sweden)

    Mailin Sotolongo-Lopez

    2016-04-01

    Full Text Available The visual system of a particular species is highly adapted to convey detailed ecological and behavioral information essential for survival. The consequences of structural mutations of opsins upon spectral sensitivity and environmental adaptation have been studied in great detail, but lacking is knowledge of the potential influence of alterations in gene regulatory networks upon the diversity of cone subtypes and the variation in the ratio of rods and cones observed in numerous diurnal and nocturnal species. Exploiting photoreceptor patterning in cone-dominated zebrafish, we uncovered two independent mechanisms by which the sine oculis homeobox homolog 7 (six7 regulates photoreceptor development. In a genetic screen, we isolated the lots-of-rods-junior (ljrp23ahub mutation that resulted in an increased number and uniform distribution of rods in otherwise normal appearing larvae. Sequence analysis, genome editing using TALENs and knockdown strategies confirm ljrp23ahub as a hypomorphic allele of six7, a teleost orthologue of six3, with known roles in forebrain patterning and expression of opsins. Based on the lack of predicted protein-coding changes and a deletion of a conserved element upstream of the transcription start site, a cis-regulatory mutation is proposed as the basis of the reduced expression of six7 in ljrp23ahub. Comparison of the phenotypes of the hypomorphic and knock-out alleles provides evidence of two independent roles in photoreceptor development. EdU and PH3 labeling show that the increase in rod number is associated with extended mitosis of photoreceptor progenitors, and TUNEL suggests that the lack of green-sensitive cones is the result of cell death of the cone precursor. These data add six7 to the small but growing list of essential genes for specification and patterning of photoreceptors in non-mammalian vertebrates, and highlight alterations in transcriptional regulation as a potential source of photoreceptor variation

  7. How agricultural management shapes soil microbial communities: patterns emerging from genetic and genomic studies

    Science.gov (United States)

    Daly, Amanda; Grandy, A. Stuart

    2016-04-01

    Agriculture is a predominant land use and thus a large influence on global carbon (C) and nitrogen (N) balances, climate, and human health. If we are to produce food, fiber, and fuel sustainably we must maximize agricultural yield while minimizing negative environmental consequences, goals towards which we have made great strides through agronomic advances. However, most agronomic strategies have been designed with a view of soil as a black box, largely ignoring the way management is mediated by soil biota. Because soil microbes play a central role in many of the processes that deliver nutrients to crops and support their health and productivity, agricultural management strategies targeted to exploit or support microbial activity should deliver additional benefits. To do this we must determine how microbial community structure and function are shaped by agricultural practices, but until recently our characterizations of soil microbial communities in agricultural soils have been largely limited to broad taxonomic classes due to methodological constraints. With advances in high-throughput genetic and genomic sequencing techniques, better taxonomic resolution now enables us to determine how agricultural management affects specific microbes and, in turn, nutrient cycling outcomes. Here we unite findings from published research that includes genetic or genomic data about microbial community structure (e.g. 454, Illumina, clone libraries, qPCR) in soils under agricultural management regimes that differ in type and extent of tillage, cropping selections and rotations, inclusion of cover crops, organic amendments, and/or synthetic fertilizer application. We delineate patterns linking agricultural management to microbial diversity, biomass, C- and N-content, and abundance of microbial taxa; furthermore, where available, we compare patterns in microbial communities to patterns in soil extracellular enzyme activities, catabolic profiles, inorganic nitrogen pools, and nitrogen

  8. Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

    Science.gov (United States)

    Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

    2009-07-01

    Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

  9. GRECOS project. The use of genetics to predict the vascular recurrence after stroke

    Science.gov (United States)

    Fernández-Cadenas, Israel; Mendióroz, Maite; Giralt, Dolors; Nafria, Cristina; Garcia, Elena; Carrera, Caty; Gallego-Fabrega, Cristina; Domingues-Montanari, Sophie; Delgado, Pilar; Ribó, Marc; Castellanos, Mar; Martínez, Sergi; Freijo, Mari Mar; Jiménez-Conde, Jordi; Rubiera, Marta; Alvarez-Sabín, José; Molina, Carlos A.; Font, Maria Angels; Olivares, Marta Grau; Palomeras, Ernest; de la Ossa, Natalia Perez; Martinez-Zabaleta, Maite; Masjuan, Jaime; Moniche, Francisco; Canovas, David; Piñana, Carlos; Purroy, Francisco; Cocho, Dolores; Navas, Inma; Tejero, Carlos; Aymerich, Nuria; Cullell, Natalia; Muiño, Elena; Serena, Joaquín; Rubio, Francisco; Davalos, Antoni; Roquer, Jaume; Arenillas, Juan Francisco; Martí-Fábregas, Joan; Keene, Keith; Chen, Wei-Min; Worrall, Bradford; Sale, Michele; Arboix, Adrià; Krupinski, Jerzy; Montaner, Joan

    2017-01-01

    Background and Purpose Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack (TIA). Clinical scores do not predict the whole vascular recurrence risk, therefore we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS. Methods We analyzed 256 polymorphisms from 115 candidate genes in three patient cohorts comprising 4,482 IS or TIA patients. The discovery cohort was prospectively recruited and included 1,494 patients, 6.2% of them developed a new IS during the first year of follow-up. Replication analysis was performed in 2,988 patients using SNPlex or HumanOmni1-Quad technology. We generated a predictive model using Cox regression (GRECOS score), and generated risk groups using a classification tree method. Results The analyses revealed that rs1800801 in the MGP gene (HR: 1.33, p= 9×10−03), a gene related to artery calcification, was associated with new IS during the first year of follow-up. This polymorphism was replicated in a Spanish cohort (n=1.305), however it was not significantly associated in a North American cohort (n=1.683). The GRECOS score predicted new IS (p= 3.2×10−09) and could classify patients, from low risk of stroke recurrence (1.9%) to high risk (12.6%). Moreover, the addition of genetic risk factors to the GRECOS score improves the prediction compared to previous SPI-II score (p=0.03). Conclusions The use of genetics could be useful to estimate vascular recurrence risk after IS. Genetic variability in the MGP gene was associated with vascular recurrence in the Spanish population. PMID:28411264

  10. Predictable patterns of the May-June rainfall anomaly over East Asia

    Science.gov (United States)

    Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

    2017-02-01

    During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

  11. Fuel spill identification by gas chromatography -- genetic algorithms/pattern recognition techniques

    International Nuclear Information System (INIS)

    Lavine, B.K.; Moores, A.J.; Faruque, A.

    1998-01-01

    Gas chromatography and pattern recognition methods were used to develop a potential method for typing jet fuels so a spill sample in the environment can be traced to its source. The test data consisted of 256 gas chromatograms of neat jet fuels. 31 fuels that have undergone weathering in a subsurface environment were correctly identified by type using discriminants developed from the gas chromatograms of the neat jet fuels. Coalescing poorly resolved peaks, which occurred during preprocessing, diminished the resolution and hence information content of the GC profiles. Nevertheless a genetic algorithm was able to extract enough information from these profiles to correctly classify the chromatograms of weathered fuels. This suggests that cheaper and simpler GC instruments ca be used to type jet fuels

  12. A population-based survey in Australia of men's and women's perceptions of genetic risk and predictive genetic testing and implications for primary care.

    Science.gov (United States)

    Taylor, S

    2011-01-01

    Community attitudes research regarding genetic issues is important when contemplating the potential value and utilisation of predictive testing for common diseases in mainstream health services. This article aims to report population-based attitudes and discuss their relevance to integrating genetic services in primary health contexts. Men's and women's attitudes were investigated via population-based omnibus telephone survey in Queensland, Australia. Randomly selected adults (n = 1,230) with a mean age of 48.8 years were interviewed regarding perceptions of genetic determinants of health; benefits of genetic testing that predict 'certain' versus 'probable' future illness; and concern, if any, regarding potential misuse of genetic test information. Most (75%) respondents believed genetic factors significantly influenced health status; 85% regarded genetic testing positively although attitudes varied with age. Risk-based information was less valued than certainty-based information, but women valued risk information significantly more highly than men. Respondents reported 'concern' (44%) and 'no concern' (47%) regarding potential misuse of genetic information. This study contributes important population-based data as most research has involved selected individuals closely impacted by genetic disorders. While community attitudes were positive regarding genetic testing, genetic literacy is important to establish. The nature of gender differences regarding risk perception merits further study and has policy and service implications. Community concern about potential genetic discrimination must be addressed if health benefits of testing are to be maximised. Larger questions remain in scientific, policy, service delivery, and professional practice domains before predictive testing for common disorders is efficacious in mainstream health care. Copyright © 2011 S. Karger AG, Basel.

  13. Comparison of population genetic patterns in two widespread freshwater mussels with contrasting life histories in western North America.

    Science.gov (United States)

    Mock, K E; Brim Box, J C; Chong, J P; Furnish, J; Howard, J K

    2013-12-01

    We investigate population genetic structuring in Margaritifera falcata, a freshwater mussel native to western North America, across the majority of its geographical range. We find shallow rangewide genetic structure, strong population-level structuring and very low population diversity in this species, using both mitochondrial sequence and nuclear microsatellite data. We contrast these patterns with previous findings in another freshwater mussel species group (Anodonta californiensis/A. nuttalliana) occupying the same continental region and many of the same watersheds. We conclude that differences are likely caused by contrasting life history attributes between genera, particularly host fish requirements and hermaphroditism. Further, we demonstrate the occurrence of a 'hotspot' for genetic diversity in both groups of mussels, occurring in the vicinity of the lower Columbia River drainage. We suggest that stream hierarchy may be responsible for this pattern and may produce similar patterns in other widespread freshwater species. © 2013 John Wiley & Sons Ltd.

  14. Variation and genetic structure of Melipona quadrifasciata Lepeletier (Hymenoptera, Apidae) populations based on ISSR pattern.

    Science.gov (United States)

    Nascimento, Marcília A; Batalha-Filho, Henrique; Waldschmidt, Ana M; Tavares, Mara G; Campos, Lucio A O; Salomão, Tânia M F

    2010-04-01

    For a study of diversity and genetic structuring in Melipona quadrifasciata, 61 colonies were collected in eight locations in the state of Minas Gerais, Brazil. By means of PCR analysis, 119 ISSR bands were obtained, 80 (68%) being polymorphic. H(e) and H (B) were 0.20 and 0.16, respectively. Two large groups were obtained by the UPGMA method, one formed by individuals from Januária, Urucuia, Rio Vermelho and Caeté and the other by individuals from São João Del Rei, Barbacena, Ressaquinha and Cristiano Otoni. The Φst and θ(B) values were 0.65 and 0.58, respectively, thereby indicating high population structuring. UPGMA grouping did not reveal genetic structuring of M. quadrifasciata in function of the tergite stripe pattern. The significant correlation between dissimilarity values and geographic distances (r = 0.3998; p Melipona quadrifasciata population structuring, possibly applicable to the studies of other bee species.

  15. Women's gender role orientation predicts their drinking patterns: a follow-up study of Czech women.

    Science.gov (United States)

    Kubicka, Ludek; Csémy, Ladislav

    2008-06-01

    Evaluation of the hypothesis that women's non-traditional gender role orientation contributes to drinking patterns typical for men. A two-wave prospective study with data collected in 1992 and 1997. The data reflect Czech women's changing gender role orientation and their drinking patterns during a historical period of post-totalitarian societal transformation. A representative cohort of 497 Prague women aged 30-59 years in 1997. Face-to-face interview data on drinking patterns and individually collected original questionnaire on gender role orientation. An analysis of the principal components of the gender role orientation questionnaire has led to four components, designated as egalitarianism, liberalism, feminism and hedonism. Constructed role orientation scales had Cronbachs's alpha reliabilities ranging from 0.57 to 0.74. With possible confounders controlled (thanks mainly to the prospective design), non-traditional gender role orientation components assessed in 1992 predicted the usual quantities of alcohol women have consumed per occasion in 1997, as well as three hazardous drinking patterns (occasional use of > or = 96 g alcohol, usual use of > or = 48 g and daily intake of > or = 40 g). Specifically, women's usual quantity per occasion and occasional use of > or = 96 g were predicted by egalitarianism and hedonism, and hedonism predicted usual use of > or = 48 g as well as average daily intake of > or = 40 g ethanol. Women's gender role orientation can be associated with their drinking patterns with non-traditional gender role identification being associated with greater likelihood of hazardous drinking.

  16. Sympatry Predicts Spot Pigmentation Patterns and Female Association Behavior in the Livebearing Fish Poeciliopsis baenschi

    Science.gov (United States)

    Roth-Monzón, Andrea J.; Scott, Laura E.; Camargo, Ashley A.; Clark, Eliza I.; Schott, Eric E.; Johnson, Jerald B.

    2017-01-01

    In this study, we explored the possibility that differences in pigmentation patterns among populations of the fish Poeciliopsis baenschi were associated with the presence or absence of the closely related species P. turneri. If reproductive character displacement is responsible, spotting patterns in these two species should diverge in sympatry, but not allopatry. We predicted that female P. baenschi from sympatric sites should show a preference for associating with conspecifics vs. heterospecific males, but females from allopatric sites should show no such preferences. To evaluate these predictions, we compared spotting patterns and female association behaviors in populations of P. baenschi from Central Mexico. We found that both of our predictions were supported. Poeciliopsis baenschi that co-occured with P. turneri had spotting patterns significantly different than their counterparts from allopatric sites. Using a simultaneous choice test of video presentations of males, we also found that female P. baenschi from populations that co-occured with P. turneri spent significantly more time with males of their own species than with P. turneri males. In contrast, females from allopatric populations of P. baenschi showed no differences in the amount of time they spent with either conspecific or heterospecific males. Together, our results are consistent with the hypothesis that reproductive character displacement may be responsible for behavioral and spotting pattern differences in these populations of P. baenschi. PMID:28107407

  17. Prevalence of current patterns and predictive trends of multidrug-resistant Salmonella Typhi in Sudan.

    Science.gov (United States)

    Elshayeb, Ayman A; Ahmed, Abdelazim A; El Siddig, Marmar A; El Hussien, Adil A

    2017-11-14

    Enteric fever has persistence of great impact in Sudanese public health especially during rainy season when the causative agent Salmonella enterica serovar Typhi possesses pan endemic patterns in most regions of Sudan - Khartoum. The present study aims to assess the recent state of antibiotics susceptibility of Salmonella Typhi with special concern to multidrug resistance strains and predict the emergence of new resistant patterns and outbreaks. Salmonella Typhi strains were isolated and identified according to the guidelines of the International Standardization Organization and the World Health Organization. The antibiotics susceptibilities were tested using the recommendations of the Clinical Laboratories Standards Institute. Predictions of emerging resistant bacteria patterns and outbreaks in Sudan were done using logistic regression, forecasting linear equations and in silico simulations models. A total of 124 antibiotics resistant Salmonella Typhi strains categorized in 12 average groups were isolated, different patterns of resistance statistically calculated by (y = ax - b). Minimum bactericidal concentration's predication of resistance was given the exponential trend (y = n e x ) and the predictive coefficient R 2  > 0 current antimicrobial drug resistance patterns of community-acquired agents causing outbreaks.

  18. Predicting the effect of fire on large-scale vegetation patterns in North America.

    Science.gov (United States)

    Donald McKenzie; David L. Peterson; Ernesto. Alvarado

    1996-01-01

    Changes in fire regimes are expected across North America in response to anticipated global climatic changes. Potential changes in large-scale vegetation patterns are predicted as a result of altered fire frequencies. A new vegetation classification was developed by condensing Kuchler potential natural vegetation types into aggregated types that are relatively...

  19. Spatio-temporal patterns and predictions of phytoplankton assemblages in a subtropical river delta system

    DEFF Research Database (Denmark)

    Wang, Chao; Li, Xinhui; Wang, Xiangxiu

    2016-01-01

    Spatial and seasonal sampling within a subtropical river delta system, the Pearl River Delta (China), provided data to determine seasonal phytoplankton patterns and develop prediction models. The high nutrient levels and frequent water exchanges resulted in a phytoplankton community with greatest...

  20. Predictable patterns in microtext as seen in educational applications using MXit in South Africa

    CSIR Research Space (South Africa)

    Butgereit, LL

    2013-09-01

    Full Text Available in a country of approximately fifty million people. In order to analyze MXit lingo for educational purposes, it was necessary to first determine whether or not there were any predictable patterns when people chatted using MXit lingo. This paper presents...

  1. How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

    Science.gov (United States)

    Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

    2015-12-01

    Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

  2. White matter tract covariance patterns predict age-declining cognitive abilities.

    Science.gov (United States)

    Gazes, Yunglin; Bowman, F DuBois; Razlighi, Qolamreza R; O'Shea, Deirdre; Stern, Yaakov; Habeck, Christian

    2016-01-15

    Previous studies investigating the relationship of white matter (WM) integrity to cognitive abilities and aging have either focused on a global measure or a few selected WM tracts. Ideally, contribution from all of the WM tracts should be evaluated at the same time. However, the high collinearity among WM tracts precludes systematic examination of WM tracts simultaneously without sacrificing statistical power due to stringent multiple-comparison corrections. Multivariate covariance techniques enable comprehensive simultaneous examination of all WM tracts without being penalized for high collinearity among observations. In this study, Scaled Subprofile Modeling (SSM) was applied to the mean integrity of 18 major WM tracts to extract covariance patterns that optimally predicted four cognitive abilities (perceptual speed, episodic memory, fluid reasoning, and vocabulary) in 346 participants across ages 20 to 79years old. Using expression of the covariance patterns, age-independent effects of white matter integrity on cognition and the indirect effect of WM integrity on age-related differences in cognition were tested separately, but inferences from the indirect analyses were cautiously made given that cross-sectional data set was used in the analysis. A separate covariance pattern was identified that significantly predicted each cognitive ability after controlling for age except for vocabulary, but the age by WM covariance pattern interaction was not significant for any of the three abilities. Furthermore, each of the patterns mediated the effect of age on the respective cognitive ability. A distinct set of WM tracts was most influential in each of the three patterns. The WM covariance pattern accounting for fluid reasoning showed the most number of influential WM tracts whereas the episodic memory pattern showed the least number. Specific patterns of WM tracts make significant contributions to the age-related differences in perceptual speed, episodic memory, and

  3. Short-range dynamics and prediction of mesoscale flow patterns in the MISTRAL field experiment

    Energy Technology Data Exchange (ETDEWEB)

    Weber, R.O.; Kaufmann, P.; Talkner, P. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1997-06-01

    In a limited area of about 50 km by 50 km with complex topography, wind measurements on a dense network were performed during the MISTRAL field experiment in 1991-1992. From these data the characteristic wind fields were identified by an automated classification method. The dynamics of the resulting twelve typical regional flow patterns is studied. It is discussed how transitions between the flow patterns take place and how well the transition probabilities can be described in the framework of a Markov model. Guided by this discussion, a variety of prediction models were tested which allow a short-term forecast of the flow pattern type. It is found that a prediction model which uses forecast information from the synoptic scale has the best forecast skill. (author) 2 figs., 7 refs.

  4. Predictive Control of Hydronic Floor Heating Systems using Neural Networks and Genetic Algorithms

    DEFF Research Database (Denmark)

    Vinther, Kasper; Green, Torben; Østergaard, Søren

    2017-01-01

    This paper presents the use a neural network and a micro genetic algorithm to optimize future set-points in existing hydronic floor heating systems for improved energy efficiency. The neural network can be trained to predict the impact of changes in set-points on future room temperatures. Additio...... space is not guaranteed. Evaluation of the performance of multiple neural networks is performed, using different levels of information, and optimization results are presented on a detailed house simulation model....

  5. Comparative Analysis of the Pattern of Population Genetic Diversity in Three Indo-West Pacific Rhizophora Mangrove Species.

    Science.gov (United States)

    Yan, Yu-Bin; Duke, Norm C; Sun, Mei

    2016-01-01

    Rhizophora species are the most widely distributed mangrove trees in the Indo-West Pacific (IWP) region. Comparative studies of these species with shared life history traits can help identify evolutionary factors that have played most important roles in determining genetic diversity within and between populations in ocean-current dispersed mangrove tree species. We sampled 935 individuals from 54 natural populations for genotyping with 13 microsatellite markers to investigate the level of genetic variation, population structure, and gene flow on a broad geographic scale in Rhizophora apiculata, Rhizophora mucronata , and Rhizophora stylosa across the IWP region. In contrast to the pattern expected of long-lived woody plants with predominant wind-pollination, water-dispersed seeds and wide geographic range, genetic variation within populations was generally low in all the three species, especially in those peripheral populations from geographic range limits. Although the large water-buoyant propagules of Rhizophora have capacity for long distance dispersal, such events might be rare in reality, as reflected by the low level of gene flow and high genetic differentiation between most of population pairs within each species. Phylogeographic separation of Australian and Pacific island populations from SE Asian lineages previously revealed with DNA sequence data was still detectable in R. apiculata based on genetic distances, but this pattern of disjunction was not always evident in R. mucronata and R. stylosa , suggesting that fast-evolving molecular markers could be more suitable for detecting contemporary genetic structure but not deep evolutionary divergence caused by historical vicariance. Given that mangrove species generally have small effective population sizes, we conclude that genetic drift coupled with limited gene flow have played a dominant role in producing the current pattern of population genetic diversity in the IWP Rhizophora species, overshadowing the

  6. Comparative Analysis of the Pattern of Population Genetic Diversity in Three Indo-West Pacific Rhizophora Mangrove Species

    Directory of Open Access Journals (Sweden)

    Yu-Bin Yan

    2016-09-01

    Full Text Available Rhizophora species are the most widely distributed mangrove trees in the Indo-West Pacific (IWP region. Comparative studies of these species with shared life history traits can help identify evolutionary factors that have played most important roles in determining genetic diversity within and between populations in ocean-current dispersed mangrove tree species. We sampled 935 individuals from 54 natural populations for genotyping with 13 microsatellite markers to investigate the level of genetic variation, population structure, and gene flow on a broad geographic scale in Rhizophora apiculata, R. mucronata, and R. stylosa across the IWP region. In contrast to the pattern expected of long-lived woody plants with predominant wind-pollination, water-dispersed seeds and wide geographic range, genetic variation within populations was generally low in all the three species, especially in those peripheral populations from geographic range limits. Although the large water-buoyant propagules of Rhizophora have capacity for long distance dispersal, such events might be rare in reality, as reflected by the low level of gene flow and high genetic differentiation between most of population pairs within each species. Phylogeographic separation of Australian and Pacific island populations from SE Asian lineages previously revealed with DNA sequence data was still detectable in R. apiculata based on genetic distances, but this pattern of disjunction was not always evident in R. mucronata and R. stylosa, suggesting that fast-evolving molecular markers could be more suitable for detecting contemporary genetic structure but not deep evolutionary divergence caused by historical vicariance. Given that mangrove species generally have small effective population sizes, we conclude that genetic drift coupled with limited gene flow have played a dominant role in producing the current pattern of population genetic diversity in the IWP Rhizophora species, overshadowing the

  7. Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology.

    Science.gov (United States)

    Grimm, Volker; Railsback, Steven F

    2012-01-19

    Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.

  8. Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

    Science.gov (United States)

    Grimm, Volker; Railsback, Steven F.

    2012-01-01

    Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392

  9. Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection.

    Science.gov (United States)

    Müller, Dominik; Schopp, Pascal; Melchinger, Albrecht E

    2017-03-10

    Recurrent selection (RS) has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents [Formula: see text] but little is known about how [Formula: see text] affects genomic selection (GS) in RS, especially the persistency of prediction accuracy ([Formula: see text]) and genetic gain. Synthetics were simulated by intermating [Formula: see text]= 2-32 parent lines from an ancestral population with short- or long-range linkage disequilibrium ([Formula: see text]) and subjected to multiple cycles of GS. We determined [Formula: see text] and genetic gain across 30 cycles for different training set ( TS ) sizes, marker densities, and generations of recombination before model training. Contributions to [Formula: see text] and genetic gain from pedigree relationships, as well as from cosegregation and [Formula: see text] between QTL and markers, were analyzed via four scenarios differing in (i) the relatedness between TS and selection candidates and (ii) whether selection was based on markers or pedigree records. Persistency of [Formula: see text] was high for small [Formula: see text] where predominantly cosegregation contributed to [Formula: see text], but also for large [Formula: see text] where [Formula: see text] replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing [Formula: see text] > 4, given long-range LD A in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to [Formula: see text] for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size ([Formula: see text]) and higher marker density improved persistency of

  10. Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection

    Directory of Open Access Journals (Sweden)

    Dominik Müller

    2017-03-01

    Full Text Available Recurrent selection (RS has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents ( Np , but little is known about how Np affects genomic selection (GS in RS, especially the persistency of prediction accuracy (rg , g ^ and genetic gain. Synthetics were simulated by intermating Np= 2–32 parent lines from an ancestral population with short- or long-range linkage disequilibrium (LDA and subjected to multiple cycles of GS. We determined rg , g ^ and genetic gain across 30 cycles for different training set (TS sizes, marker densities, and generations of recombination before model training. Contributions to rg , g ^ and genetic gain from pedigree relationships, as well as from cosegregation and LDA between QTL and markers, were analyzed via four scenarios differing in (i the relatedness between TS and selection candidates and (ii whether selection was based on markers or pedigree records. Persistency of rg , g ^ was high for small Np , where predominantly cosegregation contributed to rg , g ^ , but also for large Np , where LDA replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing Np > 4, given long-range LDA in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to rg , g ^ for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size (NTS and higher marker density improved persistency of rg , g ^ and hence genetic gain, but additional recombinations could not increase genetic gain.

  11. [Willingness of Students of Economics to Pay for Predictive Oncological Genetic Testing - An Empirical Analysis].

    Science.gov (United States)

    Siol, V; Lange, A; Prenzler, A; Neubauer, S; Frank, M

    2017-05-01

    Objectives: The present study aims to investigate the interest of young adults in predictive oncological genetic testing and their willingness to pay for such a test. Furthermore, major determinants of the 2 variables of interest were identified. Methods: 348 students of economics from the Leibniz University of Hanover were queried in July 2013 using an extensive questionnaire. Among other things, the participants were asked if they are interested in information about the probability to develop cancer in the future and their willingness to pay for such information. Data were analysed using descriptive statistics and ordinal probit regressions. Additionally marginal effects were calculated. Results: About 50% of the students were interested in predictive oncological genetic testing and were willing to pay for the test. Moreover, the participants who were willing to pay for the test partly attach high monetary values to the information that could so be obtained. The study shows that the interest of the students and their willingness to pay were primarily influenced by individual attitudes and perceptions. Conclusions: The study proves that young adults were interested in predictive genetic testing and appreciate information about their probability of develop cancer someday. © Georg Thieme Verlag KG Stuttgart · New York.

  12. Prevalence of current patterns and predictive trends of multidrug-resistant Salmonella Typhi in Sudan

    Directory of Open Access Journals (Sweden)

    Ayman A. Elshayeb

    2017-11-01

    Full Text Available Abstract Background Enteric fever has persistence of great impact in Sudanese public health especially during rainy season when the causative agent Salmonella enterica serovar Typhi possesses pan endemic patterns in most regions of Sudan - Khartoum. Objectives The present study aims to assess the recent state of antibiotics susceptibility of Salmonella Typhi with special concern to multidrug resistance strains and predict the emergence of new resistant patterns and outbreaks. Methods Salmonella Typhi strains were isolated and identified according to the guidelines of the International Standardization Organization and the World Health Organization. The antibiotics susceptibilities were tested using the recommendations of the Clinical Laboratories Standards Institute. Predictions of emerging resistant bacteria patterns and outbreaks in Sudan were done using logistic regression, forecasting linear equations and in silico simulations models. Results A total of 124 antibiotics resistant Salmonella Typhi strains categorized in 12 average groups were isolated, different patterns of resistance statistically calculated by (y = ax − b. Minimum bactericidal concentration’s predication of resistance was given the exponential trend (y = n ex and the predictive coefficient R2 > 0 < 1 are approximately alike. It was assumed that resistant bacteria occurred with a constant rate of antibiotic doses during the whole experimental period. Thus, the number of sensitive bacteria decreases at the same rate as resistant occur following term to the modified predictive model which solved computationally. Conclusion This study assesses the prediction of multi-drug resistance among S. Typhi isolates by applying low cost materials and simple statistical methods suitable for the most frequently used antibiotics as typhoid empirical therapy. Therefore, bacterial surveillance systems should be implemented to present data on the aetiology and current

  13. Does Violence in Adolescence Differentially Predict Offending Patterns in Early Adulthood?

    Science.gov (United States)

    Cardwell, Stephanie M; Piquero, Alex R

    2018-05-01

    Previous research is mixed on whether the commission of a violent offense in adolescence is predictive of criminal career characteristics. In the current study, we addressed the following: (a) What factors predict the commission of serious violence in mid-adolescence? and (b) Does involvement in serious violence in mid-adolescence lead to more chronic and/or more heterogeneous patterns of offending in early adulthood? Data were obtained from the Pathways to Desistance Study, a longitudinal study of serious adolescent offenders in Philadelphia, Pennsylvania, and Phoenix, Arizona. Prior arrests, violence exposure, and gang involvement distinguished adolescents who engaged in violence at baseline. A violent offense at baseline was not predictive of a higher frequency of rearrests but was associated with membership in the low offending trajectory. In conclusion, violent offending in adolescence might be a poor predictor of chronic and heterogeneous patterns of offending throughout the life course.

  14. Optimization of Boiling Water Reactor Loading Pattern Using Two-Stage Genetic Algorithm

    International Nuclear Information System (INIS)

    Kobayashi, Yoko; Aiyoshi, Eitaro

    2002-01-01

    A new two-stage optimization method based on genetic algorithms (GAs) using an if-then heuristic rule was developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). In the first stage, the LP is optimized using an improved GA operator. In the second stage, an exposure-dependent control rod pattern (CRP) is sought using GA with an if-then heuristic rule. The procedure of the improved GA is based on deterministic operators that consist of crossover, mutation, and selection. The handling of the encoding technique and constraint conditions by that GA reflects the peculiar characteristics of the BWR. In addition, strategies such as elitism and self-reproduction are effectively used in order to improve the search speed. The LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and constraints dependent on three dimensions have always necessitated the use of three-dimensional core simulators for BWRs, so that optimization of computational efficiency is required. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant in two phases. One phase is only LP optimization applying the Haling technique. The other phase is an LP optimization that considers the CRP during reactor operation. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained

  15. Genetic diversity and trait genomic prediction in a pea diversity panel.

    Science.gov (United States)

    Burstin, Judith; Salloignon, Pauline; Chabert-Martinello, Marianne; Magnin-Robert, Jean-Bernard; Siol, Mathieu; Jacquin, Françoise; Chauveau, Aurélie; Pont, Caroline; Aubert, Grégoire; Delaitre, Catherine; Truntzer, Caroline; Duc, Gérard

    2015-02-21

    Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being

  16. ["Screening" in special situations. Assessing predictive genetic screening for hereditary breast and colorectal cancer].

    Science.gov (United States)

    Jonas, Susanna; Wild, Claudia; Schamberger, Chantal

    2003-02-01

    The aim of this health technology assessment was to analyse the current scientific and genetic counselling on predictive genetic testing for hereditary breast and colorectal cancer. Predictive genetic testing will be available for several common diseases in the future and questions related to financial issues and quality standards will be raised. This report is based on a systematic/nonsystematic literature search in several databases (e.g. EmBase, Medline, Cochrane Library) and on a specific health technology assessment report (CCOHTA) and review (American Gastroenterological Ass.), respectively. Laboratory test methods, early detection methods and the benefit from prophylactic interventions were analysed and social consequences interpreted. Breast and colorectal cancer are counted among the most frequently cancer diseases. Most of them are based on random accumulation of risk factors, 5-10% show a familial determination. A hereditary modified gene is responsible for the increased cancer risk. In these families, high tumour frequency, young age at diagnosis and multiple primary tumours are remarkable. GENETIC DIAGNOSIS: Sequence analysis is the gold standard. Denaturing high performance liquid chromatography is a quick alternative method. The identification of the responsible gene defect in an affected family member is important. If the test result is positive there is an uncertainty whether the disease will develop or not, when and in which degree, which is founded in the geno-/phenotype correlation. The individual risk estimation is based upon empirical evidence. The test results affect the whole family. Currently, primary prevention is possible for familial adenomatous polyposis (celecoxib, prophylactic colectomy) and for hereditary mamma carcinoma (prophylactic mastectomy). The so-called preventive medical check-ups are early detection examinations. The evidence about early detection methods for colorectal cancer is better than for breast cancer. Prophylactic

  17. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

    Science.gov (United States)

    Sieberts, Solveig K; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S K; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-Ud-Din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R; Marttinen, Pekka; Mezlini, Aziz M; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P; Gerlag, Danielle; Huizinga, Tom W J; Kurreeman, Fina; Allaart, Cornelia F; Louis Bridges, S; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M; Bridges, S Louis; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M

    2016-08-23

    Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

  18. Hypotension Risk Prediction via Sequential Contrast Patterns of ICU Blood Pressure.

    Science.gov (United States)

    Ghosh, Shameek; Feng, Mengling; Nguyen, Hung; Li, Jinyan

    2016-09-01

    Acute hypotension is a significant risk factor for in-hospital mortality at intensive care units. Prolonged hypotension can cause tissue hypoperfusion, leading to cellular dysfunction and severe injuries to multiple organs. Prompt medical interventions are thus extremely important for dealing with acute hypotensive episodes (AHE). Population level prognostic scoring systems for risk stratification of patients are suboptimal in such scenarios. However, the design of an efficient risk prediction system can significantly help in the identification of critical care patients, who are at risk of developing an AHE within a future time span. Toward this objective, a pattern mining algorithm is employed to extract informative sequential contrast patterns from hemodynamic data, for the prediction of hypotensive episodes. The hypotensive and normotensive patient groups are extracted from the MIMIC-II critical care research database, following an appropriate clinical inclusion criteria. The proposed method consists of a data preprocessing step to convert the blood pressure time series into symbolic sequences, using a symbolic aggregate approximation algorithm. Then, distinguishing subsequences are identified using the sequential contrast mining algorithm. These subsequences are used to predict the occurrence of an AHE in a future time window separated by a user-defined gap interval. Results indicate that the method performs well in terms of the prediction performance as well as in the generation of sequential patterns of clinical significance. Hence, the novelty of sequential patterns is in their usefulness as potential physiological biomarkers for building optimal patient risk stratification systems and for further clinical investigation of interesting patterns in critical care patients.

  19. Towards pattern generation and chaotic series prediction with photonic reservoir computers

    Science.gov (United States)

    Antonik, Piotr; Hermans, Michiel; Duport, François; Haelterman, Marc; Massar, Serge

    2016-03-01

    Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.

  20. Gender perceptions predict sex differences in growth patterns of indigenous Guatemalan infants and young children.

    Science.gov (United States)

    Tumilowicz, Alison; Habicht, Jean-Pierre; Pelto, Gretel; Pelletier, David L

    2015-11-01

    Nearly one-half of Guatemalan children experience growth faltering, more so in indigenous than in nonindigenous children. On the basis of ethnographic interviews in Totonicapán, Guatemala, which revealed differences in maternal perceptions about food needs in infant girls and boys, we predicted a cumulative sex difference in favor of girls that occurred at ∼6 mo of age and diminished markedly thereafter. We examined whether the predicted differences in age-sex patterns were observed in the village, replicated the examination nationally for indigenous children, and examined whether the pattern in nonindigenous children was different. Ethnographic interviews (n = 24) in an indigenous village were conducted. Anthropometric measurements of the village children aged 0-35 mo (n = 119) were obtained. National-level growth patterns were analyzed for indigenous (n = 969) and nonindigenous (n = 1374) children aged 0-35 mo with the use of Demographic and Health Survey (DHS) data. Mothers reported that, compared with female infants, male infants were hungrier, were not as satisfied with breastfeeding alone, and required earlier complementary feeding. An anthropometric analysis confirmed the prediction of healthier growth in indigenous girls than in indigenous boys throughout the first year of life, which resulted in a 2.98-cm height-for-age difference (HAD) between sexes in the village and a 1.61-cm HAD (P differences diminished in the second year of life (P differences in the HAD that first favor girls and then favor boys in the indigenous growth patterns are due to feeding patterns on the basis of gendered cultural perceptions. Circumstances that result in differential sex growth patterns need to be elucidated, in particular the favorable growth in girls in the first year of life. © 2015 American Society for Nutrition.

  1. Whole exome sequencing in 342 congenital cardiac left sided lesion cases reveals extensive genetic heterogeneity and complex inheritance patterns

    Directory of Open Access Journals (Sweden)

    Alexander H. Li

    2017-10-01

    Full Text Available Abstract Background Left-sided lesions (LSLs account for an important fraction of severe congenital cardiovascular malformations (CVMs. The genetic contributions to LSLs are complex, and the mutations that cause these malformations span several diverse biological signaling pathways: TGFB, NOTCH, SHH, and more. Here, we use whole exome sequence data generated in 342 LSL cases to identify likely damaging variants in putative candidate CVM genes. Methods Using a series of bioinformatics filters, we focused on genes harboring population-rare, putative loss-of-function (LOF, and predicted damaging variants in 1760 CVM candidate genes constructed a priori from the literature and model organism databases. Gene variants that were not observed in a comparably sequenced control dataset of 5492 samples without severe CVM were then subjected to targeted validation in cases and parents. Whole exome sequencing data from 4593 individuals referred for clinical sequencing were used to bolster evidence for the role of candidate genes in CVMs and LSLs. Results Our analyses revealed 28 candidate variants in 27 genes, including 17 genes not previously associated with a human CVM disorder, and revealed diverse patterns of inheritance among LOF carriers, including 9 confirmed de novo variants in both novel and newly described human CVM candidate genes (ACVR1, JARID2, NR2F2, PLRG1, SMURF1 as well as established syndromic CVM genes (KMT2D, NF1, TBX20, ZEB2. We also identified two genes (DNAH5, OFD1 with evidence of recessive and hemizygous inheritance patterns, respectively. Within our clinical cohort, we also observed heterozygous LOF variants in JARID2 and SMAD1 in individuals with cardiac phenotypes, and collectively, carriers of LOF variants in our candidate genes had a four times higher odds of having CVM (odds ratio = 4.0, 95% confidence interval 2.5–6.5. Conclusions Our analytical strategy highlights the utility of bioinformatic resources, including human

  2. An Automated Defect Prediction Framework using Genetic Algorithms: A Validation of Empirical Studies

    Directory of Open Access Journals (Sweden)

    Juan Murillo-Morera

    2016-05-01

    Full Text Available Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding software practitioners. With timely and accurate defect predictions, practitioners can focus their limited testing resources on higher risk areas. This paper reports the results of three empirical studies that uses an automated genetic defect prediction framework. This framework generates and compares different learning schemes (preprocessing + attribute selection + learning algorithms and selects the best one using a genetic algorithm, with the objective to estimate the defect proneness of a software module. The first empirical study is a performance comparison of our framework with the most important framework of the literature. The second empirical study is a performance and runtime comparison between our framework and an exhaustive framework. The third empirical study is a sensitivity analysis. The last empirical study, is our main contribution in this paper. Performance of the software development defect prediction models (using AUC, Area Under the Curve was validated using NASA-MDP and PROMISE data sets. Seventeen data sets from NASA-MDP (13 and PROMISE (4 projects were analyzed running a NxM-fold cross-validation. A genetic algorithm was used to select the components of the learning schemes automatically, and to assess and report the results. Our results reported similar performance between frameworks. Our framework reported better runtime than exhaustive framework. Finally, we reported the best configuration according to sensitivity analysis.

  3. Impulsive-choice patterns for food in genetically lean and obese Zucker rats.

    Science.gov (United States)

    Boomhower, Steven R; Rasmussen, Erin B; Doherty, Tiffany S

    2013-03-15

    Behavioral-economic studies have shown that differences between lean and obese Zuckers in food consumption depend on the response requirement for food. Since a response requirement inherently increases the delay to reinforcement, differences in sensitivity to delay may also be a relevant mechanism of food consumption in the obese Zucker rat. Furthermore, the endocannabinoid neurotransmitter system has been implicated in impulsivity, but studies that attempt to characterize the effects of cannabinoid drugs (e.g., rimonabant) on impulsive choice may be limited by floor effects. The present study aimed to characterize impulsive-choice patterns for sucrose using an adjusting-delay procedure in genetically lean and obese Zuckers. Ten lean and ten obese Zucker rats chose between one lever that resulted in one pellet after a standard delay (either 1 s or 5 s) and a second lever that resulted in two or three pellets after an adjusting delay. After behavior stabilized under baseline, rimonabant (0-10 mg/kg) was administered prior to some choice sessions in the two-pellet condition. Under baseline, obese Zuckers made more impulsive choices than leans in three of the four standard-delay/pellet conditions. Additionally, in the 2-pellet condition, rimonabant increased impulsive choice in lean rats in the 1-s standard-delay condition; however, rimonabant decreased impulsive choice in obese rats in the 1-s and 5-s standard-delay conditions. These data suggest that genetic factors that influence impulsive choice are stronger in some choice conditions than others, and that the endocannabinoid system may be a relevant neuromechanism. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia.

    Science.gov (United States)

    Alves, Isabel; Arenas, Miguel; Currat, Mathias; Sramkova Hanulova, Anna; Sousa, Vitor C; Ray, Nicolas; Excoffier, Laurent

    2016-04-01

    Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

    Science.gov (United States)

    Jia, Yi; Jannink, Jean-Luc

    2012-01-01

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

  6. On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

    Directory of Open Access Journals (Sweden)

    Julien Becker

    Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

  7. Recovery patterns, histological observations and genetic integrity in Malus shoot tips cryopreserved using droplet vitrification and encapsulation-dehydration procedures

    Science.gov (United States)

    A droplet-vitrification procedure is described for cryopreservation of Malus shoot tips. Survival patterns, recovery types, histological observations, and genetic integrity were compared for Malus shoot tips cryopreserved using this droplet-vitrification procedure and an encapsulation-dehydration pr...

  8. Common genetic variations in CCK, leptin, and leptin receptor genes are associated with specific human eating patterns

    NARCIS (Netherlands)

    de Krom, Mariken; van der Schouw, Yvonne T.; Hendriks, Judith; Ophoff, Roel A.; van Gils, Carla H.; Stolk, Ronald P.; Grobbee, Diederick E.; Adan, Roger

    Obesity has a heritable component; however, the heterogeneity of obesity complicates dissection of its genetic background. In this study, we therefore focused on eating patterns as specific traits within obesity. These traits have a heritable component; genes associated with a specific eating

  9. Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

    Science.gov (United States)

    Hill, William G

    2014-01-01

    Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

  10. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Directory of Open Access Journals (Sweden)

    Montri Inthachot

    2016-01-01

    Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

  11. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Science.gov (United States)

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  12. Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

    Science.gov (United States)

    Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

    2017-05-01

    Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016

  13. Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

    Science.gov (United States)

    Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

    2013-01-01

    In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

  14. Do attachment patterns predict aggression in a context of social rejection? An executive functioning account.

    Science.gov (United States)

    Ma, Yuanxiao; Ma, Haijing; Chen, Xu; Ran, Guangming; Zhang, Xing

    2017-07-01

    People tend to respond to rejection and attack with aggression. The present research examined the modulation role of attachment patterns on provoked aggression following punishment and proposed an executive functioning account of attachment patterns' modulating influence based on the General Aggression Model. Attachment style was measured using the Experiences in Close Relationships inventory. Experiments 1a and b and 2 adopted a social rejection task and assessed subsequent unprovoked and provoked aggression with different attachment patterns. Moreover, Experiment 1b and 2 used a Stroop task to examine whether differences in provoked aggression by attachment patterns are due to the amount of executive functioning following social rejection, or after unprovoked punishment, or even before social rejection. Anxiously attached participants displayed significant more provoked aggression than securely and avoidantly attached participants in provoked aggression following unprovoked punishment in Experiments 1 and 2. Meanwhile, subsequent Stroop tests indicated anxiously attached participants experienced more executive functioning depletion after social rejection and unprovoked aggression. The present findings support the General Aggression Model and suggest that provoked aggression is predicted by attachment patterns in the context of social rejection; different provoked aggression may depend on the degree of executive functioning that individuals preserved in aggressive situations. The current study contributes to our understanding of the importance of the role of attachment patterns in modulating aggressive behavior accompanying unfair social encounters. © 2017 Wiley Periodicals, Inc.

  15. Toward a Predictive Framework for Convergent Evolution: Integrating Natural History, Genetic Mechanisms, and Consequences for the Diversity of Life.

    Science.gov (United States)

    Agrawal, Anurag A

    2017-08-01

    A charm of biology as a scientific discipline is the diversity of life. Although this diversity can make laws of biology challenging to discover, several repeated patterns and general principles govern evolutionary diversification. Convergent evolution, the independent evolution of similar phenotypes, has been at the heart of one approach to understand generality in the evolutionary process. Yet understanding when and why organismal traits and strategies repeatedly evolve has been a central challenge. These issues were the focus of the American Society of Naturalists Vice Presidential Symposium in 2016 and are the subject of this collection of articles. Although naturalists have long made inferences about convergent evolution and its importance, there has been confusion in the interpretation of the pattern of convergence. Does convergence primarily indicate adaptation or constraint? How often should convergence be expected? Are there general principles that would allow us to predict where and when and by what mechanisms convergent evolution should occur? What role does natural history play in advancing our understanding of general evolutionary principles? In this introductory article, I address these questions, review several generalizations about convergent evolution that have emerged over the past 15 years, and present a framework for advancing the study and interpretation of convergence. Perhaps the most important emerging conclusion is that the genetic mechanisms of convergent evolution are phylogenetically conserved; that is, more closely related species tend to share the same genetic basis of traits, even when independently evolved. Finally, I highlight how the articles in this special issue further develop concepts, methodologies, and case studies at the frontier of our understanding of the causes and consequences of convergent evolution.

  16. Patterns of deep-sea genetic connectivity in the New Zealand region: implications for management of benthic ecosystems.

    Directory of Open Access Journals (Sweden)

    Eleanor K Bors

    Full Text Available Patterns of genetic connectivity are increasingly considered in the design of marine protected areas (MPAs in both shallow and deep water. In the New Zealand Exclusive Economic Zone (EEZ, deep-sea communities at upper bathyal depths (<2000 m are vulnerable to anthropogenic disturbance from fishing and potential mining operations. Currently, patterns of genetic connectivity among deep-sea populations throughout New Zealand's EEZ are not well understood. Using the mitochondrial Cytochrome Oxidase I and 16S rRNA genes as genetic markers, this study aimed to elucidate patterns of genetic connectivity among populations of two common benthic invertebrates with contrasting life history strategies. Populations of the squat lobster Munida gracilis and the polychaete Hyalinoecia longibranchiata were sampled from continental slope, seamount, and offshore rise habitats on the Chatham Rise, Hikurangi Margin, and Challenger Plateau. For the polychaete, significant population structure was detected among distinct populations on the Chatham Rise, the Hikurangi Margin, and the Challenger Plateau. Significant genetic differences existed between slope and seamount populations on the Hikurangi Margin, as did evidence of population differentiation between the northeast and southwest parts of the Chatham Rise. In contrast, no significant population structure was detected across the study area for the squat lobster. Patterns of genetic connectivity in Hyalinoecia longibranchiata are likely influenced by a number of factors including current regimes that operate on varying spatial and temporal scales to produce potential barriers to dispersal. The striking difference in population structure between species can be attributed to differences in life history strategies. The results of this study are discussed in the context of existing conservation areas that are intended to manage anthropogenic threats to deep-sea benthic communities in the New Zealand region.

  17. Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

    Science.gov (United States)

    Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

    2015-07-01

    Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

  18. Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

    Science.gov (United States)

    Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

    2016-01-01

    Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

  19. Predicting evolutionary responses when genetic variance and selection covary with the environment: a large-scale Open Access Data approach

    NARCIS (Netherlands)

    Ramakers, J.J.C.; Culina, A.; Visser, M.E.; Gienapp, P.

    2017-01-01

    Additive genetic variance and selection are the key ingredients for evolution. In wild populations, however, predicting evolutionary trajectories is difficult, potentially by an unrecognised underlying environment dependency of both (additive) genetic variance and selection (i.e. G×E and S×E).

  20. Bovine salmonellosis in northeast of Iran: frequency, genetic fingerprinting and antimicrobial resistance patterns of Salmonella spp.

    Science.gov (United States)

    Halimi, Hessam A; Seifi, Hesam A; Rad, Mehrnaz

    2014-01-01

    To evaluate serovar and antimicrobial resistance patterns of Salmonella spp isolated from healthy, diseased and necropsied cows and calves in this observational study. Nineteen isolates recovered from feces and tissues of salmonellosis-affected animals of two commercial farms in north-east of Iran. In second part of the study, the two farms were sampled 4 times with an interval of 2 month. The samples included calves' feces, adult cows' feces, feeds, water, milk filters, and milk fed to calves. Five Salmonella were isolated from 332 fecal samples collected from calves and peri-parturient cows. No Salmonella was recovered from water, feed, milk filers and milk fed to calves. Salmonella Typhimurium was the most frequently isolate among all sero-groups. S. Dublin was only accounted for 8% (two out of 24) of isolates. Isolated Salmonella strains were used for the ERIC PCR DNA fingerprinting assay. Our results grouped Salmonella isolates into 3 clusters, suggesting that specific genotypes were responsible for each sero-group of Salmonella. The results also revealed diversity among Salmonella isolates in cluster III (sero-group B). Eighteen out of 19 Salmonella spp. were resistant to oxytetracycline. Five isolates out of 19 showed more than one drug resistance. Multi-drug resistance was seen only among Salmonella Typhimurium isolates. Enrofloxacin was the most susceptible antibiotic against all isolates in this study. The emergence of multiple antibiotic-resistant strains of Salmonella Typhimurium should be of great concern to the public. No correlation between ERIC fingerprinting and resistance patterns of Salmonella isolates was found, which indicates resistance to antimicrobial agents was not related to specific genetic background. Copyright © 2014 Asian Pacific Tropical Biomedical Magazine. Published by Elsevier B.V. All rights reserved.

  1. Incongruent genetic connectivity patterns for VME indicator taxa: implications for the management of New Zealand's vulnerable marine ecosystems

    Science.gov (United States)

    Clark, M. R.; Gardner, J.; Holland, L.; Zeng, C.; Hamilton, J. S.; Rowden, A. A.

    2016-02-01

    In the New Zealand region vulnerable marine ecosystems (VMEs) are at risk from commercial fishing activity and future seabed mining. Understanding connectivity among VMEs is important for the design of effective spatial management strategies, i.e. a network of protected areas. To date however, genetic connectivity in the New Zealand region has rarely been documented. As part of a project developing habitat suitability models and spatial management options for VMEs we used DNA sequence data and microsatellite genotyping to assess genetic connectivity for a range of VME indicator taxa, including the coral Desmophyllum dianthus, and the sponges Poecilastra laminaris and Penares palmatoclada. Overall, patterns of connectivity were inconsistent amonst taxa. Nonetheless, genetic data from each taxon were relevant to inform management at a variety of spatial scales. D. dianthus populations in the Kermadec volcanic arc and the Louisville Seamount Chain were indistinguishable, highlighting the importance of considering source-sink dynamics between populations beyond the EEZ in conservation planning. Poecilastra laminaris populations showed significant divergence across the Chatham Rise, in contrast to P. palmatoclada, which had a uniform haplotypic distribution. However, both sponge species exhibited the highest genetic diversity on the Chatham Rise, suggesting that this area is a genetic hotspot. The spatial heterogeneity of genetic patterns of structure suggest that inclusion of several taxa is necessary to facilitate understanding of regional connectivity patterns, variation in which may be attributed to alternate life history strategies, local hydrodynamic regimes, or in some cases, suboptimal sample sizes. Our findings provide important information for use by environmental managers, including summary maps of genetic diversity and barriers to gene flow, which will be used in spatial management decision-support tools.

  2. Prediction of Aerodynamic Coefficients for Wind Tunnel Data using a Genetic Algorithm Optimized Neural Network

    Science.gov (United States)

    Rajkumar, T.; Aragon, Cecilia; Bardina, Jorge; Britten, Roy

    2002-01-01

    A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.

  3. Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging

    Science.gov (United States)

    Prasetiyowati, S. S.; Sibaroni, Y.

    2018-03-01

    Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time.

  4. Predicting risk in space: Genetic markers for differential vulnerability to sleep restriction

    Science.gov (United States)

    Goel, Namni; Dinges, David F.

    2012-08-01

    Several laboratories have found large, highly reliable individual differences in the magnitude of cognitive performance, fatigue and sleepiness, and sleep homeostatic vulnerability to acute total sleep deprivation and to chronic sleep restriction in healthy adults. Such individual differences in neurobehavioral performance are also observed in space flight as a result of sleep loss. The reasons for these stable phenotypic differential vulnerabilities are unknown: such differences are not yet accounted for by demographic factors, IQ or sleep need, and moreover, psychometric scales do not predict those individuals cognitively vulnerable to sleep loss. The stable, trait-like (phenotypic) inter-individual differences observed in response to sleep loss—with intraclass correlation coefficients accounting for 58-92% of the variance in neurobehavioral measures—point to an underlying genetic component. To this end, we utilized multi-day highly controlled laboratory studies to investigate the role of various common candidate gene variants—each independently—in relation to cumulative neurobehavioral and sleep homeostatic responses to sleep restriction. These data suggest that common genetic variations (polymorphisms) involved in sleep-wake, circadian, and cognitive regulation may serve as markers for prediction of inter-individual differences in sleep homeostatic and neurobehavioral vulnerability to sleep restriction in healthy adults. Identification of genetic predictors of differential vulnerability to sleep restriction—as determined from candidate gene studies—will help identify astronauts most in need of fatigue countermeasures in space flight and inform medical standards for obtaining adequate sleep in space. This review summarizes individual differences in neurobehavioral vulnerability to sleep deprivation and ongoing genetic efforts to identify markers of such differences.

  5. Predicting spiral wave patterns from cell properties in a model of biological self-organization.

    Science.gov (United States)

    Geberth, Daniel; Hütt, Marc-Thorsten

    2008-09-01

    In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

  6. Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

    Science.gov (United States)

    Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

    2018-01-01

    T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

  7. Prediction of ion-exchange column breakthrough curves by constant-pattern wave approach.

    Science.gov (United States)

    Lee, I-Hsien; Kuan, Yu-Chung; Chern, Jia-Ming

    2008-03-21

    The release of heavy metals from industrial wastewaters represents one of major threats to environment. Compared with chemical precipitation method, fixed-bed ion-exchange process can effectively remove heavy metals from wastewaters and generate no hazardous sludge. In order to design and operate fixed-bed ion-exchange processes successfully, it is very important to understand the column dynamics. In this study, the column experiments for Cu2+/H+, Zn2+/H+, and Cd2+/H+ systems using Amberlite IR-120 were performed to measure the breakthrough curves under varying operating conditions. The experimental results showed that total cation concentration in the mobile-phase played a key role on the breakthrough curves; a higher feed concentration resulted in an earlier breakthrough. Furthermore, the column dynamics was also predicted by self-sharpening and constant-pattern wave models. The self-sharpening wave model assuming local ion-exchange equilibrium could provide a simple and quick estimation for the breakthrough volume, but the predicted breakthrough curves did not match the experimental data very well. On the contrary, the constant-pattern wave model using a constant driving force model for finite ion-exchange rate provided a better fit to the experimental data. The obtained liquid-phase mass transfer coefficient was correlated to the flow velocity and other operating parameters; the breakthrough curves under varying operating conditions could thus be predicted by the constant-pattern wave model using the correlation.

  8. Personality patterns predict the risk of antisocial behavior in Spanish-speaking adolescents.

    Science.gov (United States)

    Alcázar-Córcoles, Miguel A; Verdejo-García, Antonio; Bouso-Sáiz, José C; Revuelta-Menéndez, Javier; Ramírez-Lira, Ezequiel

    2017-05-01

    There is a renewed interest in incorporating personality variables in criminology theories in order to build models able to integrate personality variables and biological factors with psychosocial and sociocultural factors. The aim of this article is the assessment of personality dimensions that contribute to the prediction of antisocial behavior in adolescents. For this purpose, a sample of adolescents from El Salvador, Mexico, and Spain was obtained. The sample consisted of 1035 participants with a mean age of 16.2. There were 450 adolescents from a forensic population (those who committed a crime) and 585 adolescents from the normal population (no crime committed). All of participants answered personality tests about neuroticism, extraversion, psychoticism, sensation seeking, impulsivity, and violence risk. Principal component analysis of the data identified two independent factors: (i) the disinhibited behavior pattern (PDC), formed by the dimensions of neuroticism, psychoticism, impulsivity and risk of violence; and (ii) the extrovert behavior pattern (PEC), formed by the dimensions of sensation risk and extraversion. Both patterns significantly contributed to the prediction of adolescent antisocial behavior in a logistic regression model which properly classifies a global percentage of 81.9%, 86.8% for non-offense and 72.5% for offense behavior. The classification power of regression equations allows making very satisfactory predictions about adolescent offense commission. Educational level has been classified as a protective factor, while age and gender (male) have been classified as risk factors.

  9. Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis.

    Science.gov (United States)

    Hall, Benjamin A; Jackson, Ethan; Hajnal, Alex; Fisher, Jasmin

    2014-09-06

    Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or 'retrodict', compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  10. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    International Nuclear Information System (INIS)

    Rattá, G.A.; Vega, J.; Murari, A.

    2012-01-01

    Highlights: ► A new signal selection methodology to improve disruption prediction is reported. ► The approach is based on Genetic Algorithms. ► An advanced predictor has been created with the new set of signals. ► The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called “Advanced Predictor Of Disruptions” (APODIS), developed for the “Joint European Torus” (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals’ parameters in order to maximize the performance of the predictor is reported. The approach is based on “Genetic Algorithms” (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  11. Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China.

    Directory of Open Access Journals (Sweden)

    Erxu Pi

    Full Text Available Temperature is a predominant environmental factor affecting grass germination and distribution. Various thermal-germination models for prediction of grass seed germination have been reported, in which the relationship between temperature and germination were defined with kernel functions, such as quadratic or quintic function. However, their prediction accuracies warrant further improvements. The purpose of this study is to evaluate the relative prediction accuracies of genetic algorithm (GA models, which are automatically parameterized with observed germination data. The seeds of five P. pratensis (Kentucky bluegrass, KB cultivars were germinated under 36 day/night temperature regimes ranging from 5/5 to 40/40 °C with 5 °C increments. Results showed that optimal germination percentages of all five tested KB cultivars were observed under a fluctuating temperature regime of 20/25 °C. Meanwhile, the constant temperature regimes (e.g., 5/5, 10/10, 15/15 °C, etc. suppressed the germination of all five cultivars. Furthermore, the back propagation artificial neural network (BP-ANN algorithm was integrated to optimize temperature-germination response models from these observed germination data. It was found that integrations of GA-BP-ANN (back propagation aided genetic algorithm artificial neural network significantly reduced the Root Mean Square Error (RMSE values from 0.21~0.23 to 0.02~0.09. In an effort to provide a more reliable prediction of optimum sowing time for the tested KB cultivars in various regions in the country, the optimized GA-BP-ANN models were applied to map spatial and temporal germination percentages of blue grass cultivars in China. Our results demonstrate that the GA-BP-ANN model is a convenient and reliable option for constructing thermal-germination response models since it automates model parameterization and has excellent prediction accuracy.

  12. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    Energy Technology Data Exchange (ETDEWEB)

    Ratta, G.A., E-mail: garatta@gateme.unsj.edu.ar [GATEME, Facultad de Ingenieria, Universidad Nacional de San Juan, Avda. San Martin 1109 (O), 5400 San Juan (Argentina); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense, 40, 28040 Madrid (Spain); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Murari, A. [Associazione EURATOM-ENEA per la Fusione, Consorzio RFX, 4-35127 Padova (Italy); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer A new signal selection methodology to improve disruption prediction is reported. Black-Right-Pointing-Pointer The approach is based on Genetic Algorithms. Black-Right-Pointing-Pointer An advanced predictor has been created with the new set of signals. Black-Right-Pointing-Pointer The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called 'Advanced Predictor Of Disruptions' (APODIS), developed for the 'Joint European Torus' (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals' parameters in order to maximize the performance of the predictor is reported. The approach is based on 'Genetic Algorithms' (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  13. A fingertip force prediction model for grasp patterns characterised from the chaotic behaviour of EEG.

    Science.gov (United States)

    Roy, Rinku; Sikdar, Debdeep; Mahadevappa, Manjunatha; Kumar, C S

    2018-05-19

    A stable grasp is attained through appropriate hand preshaping and precise fingertip forces. Here, we have proposed a method to decode grasp patterns from motor imagery and subsequent fingertip force estimation model with a slippage avoidance strategy. We have developed a feature-based classification of electroencephalography (EEG) associated with imagination of the grasping postures. Chaotic behaviour of EEG for different grasping patterns has been utilised to capture the dynamics of associated motor activities. We have computed correlation dimension (CD) as the feature and classified with "one against one" multiclass support vector machine (SVM) to discriminate between different grasping patterns. The result of the analysis showed varying classification accuracies at different subband levels. Broad categories of grasping patterns, namely, power grasp and precision grasp, were classified at a 96.0% accuracy rate in the alpha subband. Furthermore, power grasp subtypes were classified with an accuracy of 97.2% in the upper beta subband, whereas precision grasp subtypes showed relatively lower 75.0% accuracy in the alpha subband. Following assessment of fingertip force distributions while grasping, a nonlinear autoregressive (NAR) model with proper prediction of fingertip forces was proposed for each grasp pattern. A slippage detection strategy has been incorporated with automatic recalibration of the regripping force. Intention of each grasp pattern associated with corresponding fingertip force model was virtualised in this work. This integrated system can be utilised as the control strategy for prosthetic hand in the future. The model to virtualise motor imagery based fingertip force prediction with inherent slippage correction for different grasp types ᅟ.

  14. A Simple Predictive Enhancer Syntax for Hindbrain Patterning Is Conserved in Vertebrate Genomes.

    Directory of Open Access Journals (Sweden)

    Joseph Grice

    Full Text Available Determining the function of regulatory elements is fundamental for our understanding of development, disease and evolution. However, the sequence features that mediate these functions are often unclear and the prediction of tissue-specific expression patterns from sequence alone is non-trivial. Previous functional studies have demonstrated a link between PBX-HOX and MEIS/PREP binding interactions and hindbrain enhancer activity, but the defining grammar of these sites, if any exists, has remained elusive.Here, we identify a shared sequence signature (syntax within a heterogeneous set of conserved vertebrate hindbrain enhancers composed of spatially co-occurring PBX-HOX and MEIS/PREP transcription factor binding motifs. We use this syntax to accurately predict hindbrain enhancers in 89% of cases (67/75 predicted elements from a set of conserved non-coding elements (CNEs. Furthermore, mutagenesis of the sites abolishes activity or generates ectopic expression, demonstrating their requirement for segmentally restricted enhancer activity in the hindbrain. We refine and use our syntax to predict over 3,000 hindbrain enhancers across the human genome. These sequences tend to be located near developmental transcription factors and are enriched in known hindbrain activating elements, demonstrating the predictive power of this simple model.Our findings support the theory that hundreds of CNEs, and perhaps thousands of regions across the human genome, function to coordinate gene expression in the developing hindbrain. We speculate that deeply conserved sequences of this kind contributed to the co-option of new genes into the hindbrain gene regulatory network during early vertebrate evolution by linking patterns of hox expression to downstream genes involved in segmentation and patterning, and evolutionarily newer instances may have continued to contribute to lineage-specific elaboration of the hindbrain.

  15. Patterns of ancestry, signatures of natural selection, and genetic association with stature in Western African pygmies.

    Directory of Open Access Journals (Sweden)

    Joseph P Jarvis

    Full Text Available African Pygmy groups show a distinctive pattern of phenotypic variation, including short stature, which is thought to reflect past adaptation to a tropical environment. Here, we analyze Illumina 1M SNP array data in three Western Pygmy populations from Cameroon and three neighboring Bantu-speaking agricultural populations with whom they have admixed. We infer genome-wide ancestry, scan for signals of positive selection, and perform targeted genetic association with measured height variation. We identify multiple regions throughout the genome that may have played a role in adaptive evolution, many of which contain loci with roles in growth hormone, insulin, and insulin-like growth factor signaling pathways, as well as immunity and neuroendocrine signaling involved in reproduction and metabolism. The most striking results are found on chromosome 3, which harbors a cluster of selection and association signals between approximately 45 and 60 Mb. This region also includes the positional candidate genes DOCK3, which is known to be associated with height variation in Europeans, and CISH, a negative regulator of cytokine signaling known to inhibit growth hormone-stimulated STAT5 signaling. Finally, pathway analysis for genes near the strongest signals of association with height indicates enrichment for loci involved in insulin and insulin-like growth factor signaling.

  16. Sexual selection, genetic conflict, selfish genes, and the atypical patterns of gene expression in spermatogenic cells.

    Science.gov (United States)

    Kleene, Kenneth C

    2005-01-01

    This review proposes that the peculiar patterns of gene expression in spermatogenic cells are the consequence of powerful evolutionary forces known as sexual selection. Sexual selection is generally characterized by intense competition of males for females, an enormous variety of the strategies to maximize male reproductive success, exaggerated male traits at all levels of biological organization, co-evolution of sexual traits in males and females, and conflict between the sexual advantage of the male trait and the reproductive fitness of females and the individual fitness of both sexes. In addition, spermatogenesis is afflicted by selfish genes that promote their transmission to progeny while causing deleterious effects. Sexual selection, selfish genes, and genetic conflict provide compelling explanations for many atypical features of gene expression in spermatogenic cells including the gross overexpression of certain mRNAs, transcripts encoding truncated proteins that cannot carry out basic functions of the proteins encoded by the same genes in somatic cells, the large number of gene families containing paralogous genes encoding spermatogenic cell-specific isoforms, the large number of testis-cancer-associated genes that are expressed only in spermatogenic cells and malignant cells, and the overbearing role of Sertoli cells in regulating the number and quality of spermatozoa.

  17. Comparison between Decision Tree and Genetic Programming to distinguish healthy from stroke postural sway patterns.

    Science.gov (United States)

    Marrega, Luiz H G; Silva, Simone M; Manffra, Elisangela F; Nievola, Julio C

    2015-01-01

    Maintaining balance is a motor task of crucial importance for humans to perform their daily activities safely and independently. Studies in the field of Artificial Intelligence have considered different classification methods in order to distinguish healthy subjects from patients with certain motor disorders based on their postural strategies during the balance control. The main purpose of this paper is to compare the performance between Decision Tree (DT) and Genetic Programming (GP) - both classification methods of easy interpretation by health professionals - to distinguish postural sway patterns produced by healthy and stroke individuals based on 16 widely used posturographic variables. For this purpose, we used a posturographic dataset of time-series of center-of-pressure displacements derived from 19 stroke patients and 19 healthy matched subjects in three quiet standing tasks of balance control. Then, DT and GP models were trained and tested under two different experiments where accuracy, sensitivity and specificity were adopted as performance metrics. The DT method has performed statistically significant (P < 0.05) better in both cases, showing for example an accuracy of 72.8% against 69.2% from GP in the second experiment of this paper.

  18. Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

    Directory of Open Access Journals (Sweden)

    Nebot

    2012-04-01

    Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

  19. Genetic risk prediction using a spatial autoregressive model with adaptive lasso.

    Science.gov (United States)

    Wen, Yalu; Shen, Xiaoxi; Lu, Qing

    2018-05-31

    With rapidly evolving high-throughput technologies, studies are being initiated to accelerate the process toward precision medicine. The collection of the vast amounts of sequencing data provides us with great opportunities to systematically study the role of a deep catalog of sequencing variants in risk prediction. Nevertheless, the massive amount of noise signals and low frequencies of rare variants in sequencing data pose great analytical challenges on risk prediction modeling. Motivated by the development in spatial statistics, we propose a spatial autoregressive model with adaptive lasso (SARAL) for risk prediction modeling using high-dimensional sequencing data. The SARAL is a set-based approach, and thus, it reduces the data dimension and accumulates genetic effects within a single-nucleotide variant (SNV) set. Moreover, it allows different SNV sets having various magnitudes and directions of effect sizes, which reflects the nature of complex diseases. With the adaptive lasso implemented, SARAL can shrink the effects of noise SNV sets to be zero and, thus, further improve prediction accuracy. Through simulation studies, we demonstrate that, overall, SARAL is comparable to, if not better than, the genomic best linear unbiased prediction method. The method is further illustrated by an application to the sequencing data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2018 John Wiley & Sons, Ltd.

  20. Linear genetic programming application for successive-station monthly streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

    2014-09-01

    In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

  1. A combination of compositional index and genetic algorithm for predicting transmembrane helical segments.

    Directory of Open Access Journals (Sweden)

    Nazar Zaki

    Full Text Available Transmembrane helix (TMH topology prediction is becoming a focal problem in bioinformatics because the structure of TM proteins is difficult to determine using experimental methods. Therefore, methods that can computationally predict the topology of helical membrane proteins are highly desirable. In this paper we introduce TMHindex, a method for detecting TMH segments using only the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index, which is deduced from a combination of the difference in amino acid occurrences in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, a genetic algorithm was employed to find the optimal threshold value for the separation of TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in a dataset consisting of 70 test protein sequences. The sensitivity and specificity for classifying each amino acid in every protein sequence in the dataset was 0.901 and 0.865, respectively. To assess the generality of TMHindex, we also tested the approach on another standard 73-protein 3D helix dataset. TMHindex correctly predicted 91.8% of proteins based on TM segments. The level of the accuracy achieved using TMHindex in comparison to other recent approaches for predicting the topology of TM proteins is a strong argument in favor of our proposed method.The datasets, software together with supplementary materials are available at: http://faculty.uaeu.ac.ae/nzaki/TMHindex.htm.

  2. Introducing etch kernels for efficient pattern sampling and etch bias prediction

    Science.gov (United States)

    Weisbuch, François; Lutich, Andrey; Schatz, Jirka

    2018-01-01

    Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

  3. Predicting the Location and Time of Mobile Phone Users by Using Sequential Pattern Mining Techniques

    DEFF Research Database (Denmark)

    Ozer, Mert; Keles, Ilkcan; Toroslu, Hakki

    2016-01-01

    In recent years, using cell phone log data to model human mobility patterns became an active research area. This problem is a challenging data mining problem due to huge size and non-uniformity of the log data, which introduces several granularity levels for the specification of temporal...... and spatial dimensions. This paper focuses on the prediction of the location of the next activity of the mobile phone users. There are several versions of this problem. In this work, we have concentrated on the following three problems: predicting the location and the time of the next user activity...... the success of these methods with real data obtained from one of the largest mobile phone operators in Turkey. Our results are very encouraging, since we were able to obtain quite high accuracy results under small prediction sets....

  4. A Study of Pattern Prediction in the Monitoring Data of Earthen Ruins with the Internet of Things.

    Science.gov (United States)

    Xiao, Yun; Wang, Xin; Eshragh, Faezeh; Wang, Xuanhong; Chen, Xiaojiang; Fang, Dingyi

    2017-05-11

    An understanding of the changes of the rammed earth temperature of earthen ruins is important for protection of such ruins. To predict the rammed earth temperature pattern using the air temperature pattern of the monitoring data of earthen ruins, a pattern prediction method based on interesting pattern mining and correlation, called PPER, is proposed in this paper. PPER first finds the interesting patterns in the air temperature sequence and the rammed earth temperature sequence. To reduce the processing time, two pruning rules and a new data structure based on an R-tree are also proposed. Correlation rules between the air temperature patterns and the rammed earth temperature patterns are then mined. The correlation rules are merged into predictive rules for the rammed earth temperature pattern. Experiments were conducted to show the accuracy of the presented method and the power of the pruning rules. Moreover, the Ming Dynasty Great Wall dataset was used to examine the algorithm, and six predictive rules from the air temperature to rammed earth temperature based on the interesting patterns were obtained, with the average hit rate reaching 89.8%. The PPER and predictive rules will be useful for rammed earth temperature prediction in protection of earthen ruins.

  5. Patterns and processes in the genetic differentiation of the Brachionus calyciflorus complex, a passively dispersing freshwater zooplankton.

    Science.gov (United States)

    Xiang, Xian-ling; Xi, Yi-long; Wen, Xin-li; Zhang, Gen; Wang, Jin-xia; Hu, Ke

    2011-05-01

    Elucidating the evolutionary patterns and processes of extant species is an important objective of any research program that seeks to understand population divergence and, ultimately, speciation. The island-like nature and temporal fluctuation of limnetic habitats create opportunities for genetic differentiation in rotifers through space and time. To gain further understanding of spatio-temporal patterns of genetic differentiation in rotifers other than the well-studied Brachionus plicatilis complex in brackish water, a total of 318 nrDNA ITS sequences from the B. calyciflorus complex in freshwater were analysed using phylogenetic and phylogeographic methods. DNA taxonomy conducted by both the sequence divergence and the GMYC model suggested the occurrence of six potential cryptic species, supported also by reproductive isolation among the tested lineages. The significant genetic differentiation and non-significant correlation between geographic and genetic distances existed in the most abundant cryptic species, BcI-W and Bc-SW. The large proportion of genetic variability for cryptic species Bc-SW was due to differences between sampling localities within seasons, rather than between different seasons. Nested Clade Analysis suggested allopatric or past fragmentation, contiguous range expansion and long-distance colonization possibly coupled with subsequent fragmentation as the probable main forces shaping the present-day phylogeographic structure of the B. calyciflorus species complex. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Genetic structure of Quechua-speakers of the Central Andes and geographic patterns of gene frequencies in South Amerindian populations.

    Science.gov (United States)

    Luiselli, D; Simoni, L; Tarazona-Santos, E; Pastor, S; Pettener, D

    2000-09-01

    A sample of 141 Quechua-speaking individuals of the population of Tayacaja, in the Peruvian Central Andes, was typed for the following 16 genetic systems: ABO, Rh, MNSs, P, Duffy, AcP1, EsD, GLOI, PGM1, AK, 6-PGD, Hp, Gc, Pi, C3, and Bf. The genetic structure of the population was analyzed in relation to the allele frequencies available for other South Amerindian populations, using a combination of multivariate and multivariable techniques. Spatial autocorrelation analysis was performed independently for 13 alleles to identify patterns of gene flow in South America as a whole and in more specific geographic regions. We found a longitudinal cline for the AcP1*a and EsD*1 alleles which we interpreted as the result of an ancient longitudinal expansion of a putative ancestral population of modern Amerindians. Monmonnier's algorithm, used to identify areas of sharp genetic discontinuity, suggested a clear east-west differentiation of native South American populations, which was confirmed by analysis of the distribution of genetic distances. We suggest that this pattern of genetic structures is the consequence of the independent peopling of western and eastern South America or to low levels of gene flow between these regions, related to different environmental and demographic histories. Copyright 2000 Wiley-Liss, Inc.

  7. Genome-wide expression patterns and the genetic architecture of a fundamental social trait.

    Science.gov (United States)

    Wang, John; Ross, Kenneth G; Keller, Laurent

    2008-07-18

    Explaining how interactions between genes and the environment influence social behavior is a fundamental research goal, yet there is limited relevant information for species exhibiting natural variation in social organization. The fire ant Solenopsis invicta is characterized by a remarkable form of social polymorphism, with the presence of one or several queens per colony and the expression of other phenotypic and behavioral differences being completely associated with allelic variation at a single Mendelian factor marked by the gene Gp-9. Microarray analyses of adult workers revealed that differences in the Gp-9 genotype are associated with the differential expression of an unexpectedly small number of genes, many of which have predicted functions, implying a role in chemical communication relevant to the regulation of colony queen number. Even more surprisingly, worker gene expression profiles are more strongly influenced by indirect effects associated with the Gp-9 genotypic composition within their colony than by the direct effect of their own Gp-9 genotype. This constitutes an unusual example of an "extended phenotype" and suggests a complex genetic architecture with a single Mendelian factor, directly and indirectly influencing the individual behaviors that, in aggregate, produce an emergent colony-level phenotype.

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

    Directory of Open Access Journals (Sweden)

    Avval Zhila Mohajeri

    2015-01-01

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

  9. Unexpected pattern of pearl millet genetic diversity among ethno-linguistic groups in the Lake Chad Basin.

    Science.gov (United States)

    Naino Jika, A K; Dussert, Y; Raimond, C; Garine, E; Luxereau, A; Takvorian, N; Djermakoye, R S; Adam, T; Robert, T

    2017-05-01

    Despite of a growing interest in considering the role of sociological factors in seed exchanges and their consequences on the evolutionary dynamics of agro-biodiversity, very few studies assessed the link between ethno-linguistic diversity and genetic diversity patterns in small-holder farming systems. This is key for optimal improvement and conservation of crop genetic resources. Here, we investigated genetic diversity at 17 SSR markers of pearl millet landraces (varieties named by farmers) in the Lake Chad Basin. 69 pearl millet populations, representing 27 landraces collected in eight ethno-linguistic farmer groups, were analyzed. We found that the farmers' local taxonomy was not a good proxy for population's genetic differentiation as previously shown at smaller scales. Our results show the existence of a genetic structure of pearl millet mainly associated with ethno-linguistic diversity in the western side of the lake Chad. It suggests there is a limit to gene flow between landraces grown by different ethno-linguistic groups. This result was rather unexpected, because of the highly outcrossing mating system of pearl millet, the high density of pearl millet fields all along the green belt of this Sahelian area and the fact that seed exchanges among ethno-linguistic groups are known to occur. In the eastern side of the Lake, the pattern of genetic diversity suggests a larger efficient circulation of pearl millet genes between ethno-linguistic groups that are less numerous, spatially intermixed and, for some of them, more prone to exogamy. Finally, other historical and environmental factors which may contribute to the observed diversity patterns are discussed.

  10. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Analysis of Genetic Diversity and Structure Pattern of Indigofera Pseudotinctoria in Karst Habitats of the Wushan Mountains Using AFLP Markers.

    Science.gov (United States)

    Fan, Yan; Zhang, Chenglin; Wu, Wendan; He, Wei; Zhang, Li; Ma, Xiao

    2017-10-16

    Indigofera pseudotinctoria Mats is an agronomically and economically important perennial legume shrub with a high forage yield, protein content and strong adaptability, which is subject to natural habitat fragmentation and serious human disturbance. Until now, our knowledge of the genetic relationships and intraspecific genetic diversity for its wild collections is still poor, especially at small spatial scales. Here amplified fragment length polymorphism (AFLP) technology was employed for analysis of genetic diversity, differentiation, and structure of 364 genotypes of I. pseudotinctoria from 15 natural locations in Wushan Montain, a highly structured mountain with typical karst landforms in Southwest China. We also tested whether eco-climate factors has affected genetic structure by correlating genetic diversity with habitat features. A total of 515 distinctly scoreable bands were generated, and 324 of them were polymorphic. The polymorphic information content (PIC) ranged from 0.694 to 0.890 with an average of 0.789 per primer pair. On species level, Nei's gene diversity ( H j ), the Bayesian genetic diversity index ( H B ) and the Shannon information index ( I ) were 0.2465, 0.2363 and 0.3772, respectively. The high differentiation among all sampling sites was detected ( F ST = 0.2217, G ST = 0.1746, G' ST = 0.2060, θ B = 0.1844), and instead, gene flow among accessions ( N m = 1.1819) was restricted. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. This structure pattern may indicate joint effects by the neutral evolution and natural selection. Restricted N m was

  12. Heuristic rules embedded genetic algorithm to solve VVER loading pattern optimization problem

    International Nuclear Information System (INIS)

    Fatih, Alim; Kostandi, Ivanov

    2006-01-01

    Full text: Loading Pattern (LP) optimization is one of the most important aspects of the operation of nuclear reactors. A genetic algorithm (GA) code GARCO (Genetic Algorithm Reactor Optimization Code) has been developed with embedded heuristic techniques to perform optimization calculations for in-core fuel management tasks. GARCO is a practical tool that includes a unique methodology applicable for all types of Pressurized Water Reactor (PWR) cores having different geometries with an unlimited number of FA types in the inventory. GARCO was developed by modifying the classical representation of the genotype. Both the genotype representation and the basic algorithm have been modified to incorporate the in-core fuel management heuristics rules so as to obtain the best results in a shorter time. GARCO has three modes. Mode 1 optimizes the locations of the fuel assemblies (FAs) in the nuclear reactor core, Mode 2 optimizes the placement of the burnable poisons (BPs) in a selected LP, and Mode 3 optimizes simultaneously both the LP and the BP placement in the core. This study describes the basic algorithm for Mode 1. The GARCO code is applied to the VVER-1000 reactor hexagonal geometry core in this study. The M oby-Dick i s used as reactor physics code to deplete FAs in the core. It was developed to analyze the VVER reactors by SKODA Inc. To use these rules for creating the initial population with GA operators, the worth definition application is developed. Each FA has a worth value for each location. This worth is between 0 and 1. If worth of any FA for a location is larger than 0.5, this FA in this location is a good choice. When creating the initial population of LPs, a subroutine provides a percent of individuals, which have genes with higher than the 0.5 worth. The percentage of the population to be created without using worth definition is defined in the GARCO input. And also age concept has been developed to accelerate the GA calculation process in reaching the

  13. New and emerging prognostic and predictive genetic biomarkers in B-cell precursor acute lymphoblastic leukemia

    Science.gov (United States)

    Moorman, Anthony V.

    2016-01-01

    Acute lymphoblastic leukemia (ALL) is a heterogeneous disease at the genetic level. Chromosomal abnormalities are used as diagnostic, prognostic and predictive biomarkers to provide subtype, outcome and drug response information. t(12;21)/ETV6-RUNX1 and high hyper-diploidy are good-risk prognostic biomarkers whereas KMT2A (MLL) translocations, t(17;19)/TCF3-HLF, haploidy or low hypodiploidy are high-risk biomarkers. t(9;22)/BCR-ABL1 patients require targeted treatment (imatinib/dasatinib), whereas iAMP21 patients achieve better outcomes when treated intensively. High-risk genetic biomarkers are four times more prevalent in adults compared to children. The application of genomic technologies to cases without an established abnormality (B-other) reveals copy number alterations which can be used either individually or in combination as prognostic biomarkers. Transcriptome sequencing studies have identified a network of fusion genes involving kinase genes - ABL1, ABL2, PDGFRB, CSF1R, CRLF2, JAK2 and EPOR. In vitro and in vivo studies along with emerging clinical observations indicate that patients with a kinase-activating aberration may respond to treatment with small molecular inhibitors like imatinib/dasatinib and ruxolitinib. Further work is required to determine the true frequency of these abnormalities across the age spectrum and the optimal way to incorporate such inhibitors into protocols. In conclusion, genetic biomarkers are playing an increasingly important role in the management of patients with ALL. PMID:27033238

  14. STOPGAP: a database for systematic target opportunity assessment by genetic association predictions.

    Science.gov (United States)

    Shen, Judong; Song, Kijoung; Slater, Andrew J; Ferrero, Enrico; Nelson, Matthew R

    2017-09-01

    We developed the STOPGAP (Systematic Target OPportunity assessment by Genetic Association Predictions) database, an extensive catalog of human genetic associations mapped to effector gene candidates. STOPGAP draws on a variety of publicly available GWAS associations, linkage disequilibrium (LD) measures, functional genomic and variant annotation sources. Algorithms were developed to merge the association data, partition associations into non-overlapping LD clusters, map variants to genes and produce a variant-to-gene score used to rank the relative confidence among potential effector genes. This database can be used for a multitude of investigations into the genes and genetic mechanisms underlying inter-individual variation in human traits, as well as supporting drug discovery applications. Shell, R, Perl and Python scripts and STOPGAP R data files (version 2.5.1 at publication) are available at https://github.com/StatGenPRD/STOPGAP . Some of the most useful STOPGAP fields can be queried through an R Shiny web application at http://stopgapwebapp.com . matthew.r.nelson@gsk.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  15. Patterns of genetic differentiation at MHC class I genes and microsatellites identify conservation units in the giant panda.

    Science.gov (United States)

    Zhu, Ying; Wan, Qiu-Hong; Yu, Bin; Ge, Yun-Fa; Fang, Sheng-Guo

    2013-10-22

    Evaluating patterns of genetic variation is important to identify conservation units (i.e., evolutionarily significant units [ESUs], management units [MUs], and adaptive units [AUs]) in endangered species. While neutral markers could be used to infer population history, their application in the estimation of adaptive variation is limited. The capacity to adapt to various environments is vital for the long-term survival of endangered species. Hence, analysis of adaptive loci, such as the major histocompatibility complex (MHC) genes, is critical for conservation genetics studies. Here, we investigated 4 classical MHC class I genes (Aime-C, Aime-F, Aime-I, and Aime-L) and 8 microsatellites to infer patterns of genetic variation in the giant panda (Ailuropoda melanoleuca) and to further define conservation units. Overall, we identified 24 haplotypes (9 for Aime-C, 1 for Aime-F, 7 for Aime-I, and 7 for Aime-L) from 218 individuals obtained from 6 populations of giant panda. We found that the Xiaoxiangling population had the highest genetic variation at microsatellites among the 6 giant panda populations and higher genetic variation at Aime-MHC class I genes than other larger populations (Qinling, Qionglai, and Minshan populations). Differentiation index (FST)-based phylogenetic and Bayesian clustering analyses for Aime-MHC-I and microsatellite loci both supported that most populations were highly differentiated. The Qinling population was the most genetically differentiated. The giant panda showed a relatively higher level of genetic diversity at MHC class I genes compared with endangered felids. Using all of the loci, we found that the 6 giant panda populations fell into 2 ESUs: Qinling and non-Qinling populations. We defined 3 MUs based on microsatellites: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. We also recommended 3 possible AUs based on MHC loci: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. Furthermore, we recommend

  16. History, geography and host use shape genomewide patterns of genetic variation in the redheaded pine sawfly (Neodiprion lecontei).

    Science.gov (United States)

    Bagley, Robin K; Sousa, Vitor C; Niemiller, Matthew L; Linnen, Catherine R

    2017-02-01

    Divergent host use has long been suspected to drive population differentiation and speciation in plant-feeding insects. Evaluating the contribution of divergent host use to genetic differentiation can be difficult, however, as dispersal limitation and population structure may also influence patterns of genetic variation. In this study, we use double-digest restriction-associated DNA (ddRAD) sequencing to test the hypothesis that divergent host use contributes to genetic differentiation among populations of the redheaded pine sawfly (Neodiprion lecontei), a widespread pest that uses multiple Pinus hosts throughout its range in eastern North America. Because this species has a broad range and specializes on host plants known to have migrated extensively during the Pleistocene, we first assess overall genetic structure using model-based and model-free clustering methods and identify three geographically distinct genetic clusters. Next, using a composite-likelihood approach based on the site frequency spectrum and a novel strategy for maximizing the utility of linked RAD markers, we infer the population topology and date divergence to the Pleistocene. Based on existing knowledge of Pinus refugia, estimated demographic parameters and patterns of diversity among sawfly populations, we propose a Pleistocene divergence scenario for N. lecontei. Finally, using Mantel and partial Mantel tests, we identify a significant relationship between genetic distance and geography in all clusters, and between genetic distance and host use in two of three clusters. Overall, our results indicate that Pleistocene isolation, dispersal limitation and ecological divergence all contribute to genomewide differentiation in this species and support the hypothesis that host use is a common driver of population divergence in host-specialized insects. © 2016 John Wiley & Sons Ltd.

  17. A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System

    Institute of Scientific and Technical Information of China (English)

    Siva S. Sivatha Sindhu; S. Geetha; M. Marikannan; A. Kannan

    2009-01-01

    Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by "authorized" users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system (IDS) is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference (KDD 2009) intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS (NGIDS) involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this

  18. Spatiotemporal patterns of non-genetically modified crops in the era of expansion of genetically modified food.

    Science.gov (United States)

    Sun, Jing; Wu, Wenbin; Tang, Huajun; Liu, Jianguo

    2015-09-18

    Despite heated debates over the safety of genetically modified (GM) food, GM crops have been expanding rapidly. Much research has focused on the expansion of GM crops. However, the spatiotemporal dynamics of non-genetically modified (non-GM) crops are not clear, although they may have significant environmental and agronomic impacts and important policy implications. To understand the dynamics of non-GM crops and to inform the debates among relevant stakeholders, we conducted spatiotemporal analyses of China's major non-GM soybean production region, the Heilongjiang Province. Even though the total soybean planting area decreased from 2005 to 2010, surprisingly, there were hotspots of increase. The results also showed hotspots of loss as well as a large decline in the number and continuity of soybean plots. Since China is the largest non-GM soybean producer in the world, the decline of its major production region may signal the continual decline of global non-GM soybeans.

  19. A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction

    Directory of Open Access Journals (Sweden)

    Daqing Zhang

    2015-01-01

    Full Text Available Blood-brain barrier (BBB is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration.

  20. The impact of predictive genetic testing for hereditary nonpolyposis colorectal cancer: three years after testing.

    Science.gov (United States)

    Collins, Veronica R; Meiser, Bettina; Ukoumunne, Obioha C; Gaff, Clara; St John, D James; Halliday, Jane L

    2007-05-01

    To fully assess predictive genetic testing programs, it is important to assess outcomes over periods of time longer than the 1-year follow-up reported in the literature. We conducted a 3-year study of individuals who received predictive genetic test results for previously identified familial mutations in Australian Familial Cancer Clinics. Questionnaires were sent before attendance at the familial cancer clinic and 2 weeks, 4 months, 1 year, and 3 years after receiving test results. Psychological measures were included each time, and preventive behaviors were assessed at baseline and 1 and 3 years. Psychological measures were adjusted for age, gender, and baseline score. The study included 19 carriers and 54 non-carriers. We previously reported an increase in mean cancer-specific distress in carriers at 2 weeks with a return to baseline levels by 12 months. This level was maintained until 3 years. Non-carriers showed sustained decreases after testing with a significantly lower level at 3 years compared with baseline (P depression and anxiety scores did not differ between carriers and non-carriers and, at 3 years, were similar to baseline. All carriers and 7% of non-carriers had had a colonoscopy by 3 years, and 69% of 13 female carriers had undergone gynecological screening in the previous 2 years. Prophylactic surgery was rare. This report of long-term data indicates appropriate screening and improved psychological measures for non-carriers with no evidence of undue psychological distress in carriers of hereditary nonpolyposis colorectal cancer mutations.

  1. What should we want to know about our future? A Kantian view on predictive genetic testing.

    Science.gov (United States)

    Heinrichs, Bert

    2005-01-01

    Recent advances in genomic research have led to the development of new diagnostic tools, including tests which make it possible to predict the future occurrence of monogenetic diseases (e.g. Chorea Huntington) or to determine increased susceptibilities to the future development of more complex diseases (e.g. breast cancer). The use of such tests raises a number of ethical, legal and social issues which are usually discussed in terms of rights. However, in the context of predictive genetic tests a key question arises which lies beyond the concept of rights, namely, What should we want to know about our future? In the following I shall discuss this question against the background of Kant's Doctrine of Virtue. It will be demonstrated that the system of duties of virtue that Kant elaborates in the second part of his Metaphysics of Morals offers a theoretical framework for addressing the question of a proper scope of future knowledge as provided by genetic tests. This approach can serve as a source of moral guidance complementary to a justice perspective. It does, however, not rest on the-rather problematic--claim to be able to define what the "good life" is.

  2. Predictable patterns of the Asian and Indo-Pacific summer precipitation in the NCEP CFS

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Jianyin [CMA Institute of Tropical and Marine Meteorology, Guangzhou, Guangdong (China); Yang, Song; Kumar, Arun [NOAA/NWS/NCEP Climate Prediction Center, Camp Springs, MD (United States); Hu, Zeng-Zhen [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Huang, Bohua [George Mason University, Department of Climate Dynamics, Fairfax, VA (United States); Zhang, Zuqiang [CMA National Climate Center, Beijing (China)

    2009-06-15

    The predictable patterns of the Asian and Indo-Pacific summer precipitation in the NCEP climate forecast system (CFS) are depicted by applying a maximized signal-to-noise empirical orthogonal function analysis. The CFS captures the two most dominant modes of observed climate patterns. The first most dominant mode is characterized by the climate features of the onset years of El Nino-Southern Oscillation (ENSO), with strong precipitation signals over the tropical eastern Indian and western Pacific oceans, Southeast Asia, and tropical Asian monsoon regions including the Bay of Bengal and the South China Sea. The second most dominant mode is characterized by the climate features of the decay years of ENSO, with weakening signals over the western-central Pacific and strengthening signals over the Indian Ocean. The CFS is capable of predicting the most dominant modes several months in advance. It is also highly skillful in capturing the air-sea interaction processes associated with the precipitation features, as demonstrated in sea surface temperature and wind patterns. (orig.)

  3. Externalizing Problems in Childhood and Adolescence Predict Subsequent Educational Achievement but for Different Genetic and Environmental Reasons

    Science.gov (United States)

    Lewis, Gary J.; Asbury, Kathryn; Plomin, Robert

    2017-01-01

    Background: Childhood behavior problems predict subsequent educational achievement; however, little research has examined the etiology of these links using a longitudinal twin design. Moreover, it is unknown whether genetic and environmental innovations provide incremental prediction for educational achievement from childhood to adolescence.…

  4. Predictive genetic testing in children and adults: a study of emotional impact.

    Science.gov (United States)

    Michie, S; Bobrow, M; Marteau, T M

    2001-08-01

    To determine whether, following predictive genetic testing for familial adenomatous polyposis (FAP), children or adults receiving positive results experience clinically significant levels of anxiety or depression, and whether children receiving positive results experience higher levels of anxiety or depression than adults receiving positive results. Two studies, one cross sectional and one prospective. 208 unaffected subjects (148 adults and 60 children) at risk for FAP who have undergone genetic testing since 1990. anxiety, depression; independent variables: test results, demographic measures, psychological resources (optimism, self-esteem). Study 1. In children receiving positive results, mean scores for anxiety and depression were within the normal range. There was a trend for children receiving positive results to be more anxious and depressed than those receiving negative results. In adults, mean scores for anxiety were within the normal range for those receiving negative results, but were in the clinical range for those receiving positive results, with 43% (95% CI 23-65) of the latter having scores in this range. Regardless of test result, adults were more likely to be clinically anxious if they were low in optimism or self-esteem. Children receiving positive or negative results did not experience greater anxiety or depression than adults. Study 2. For children receiving a positive test result, mean scores for anxiety, depression, and self-esteem were unchanged over the year following the result, while mean anxiety scores decreased and self-esteem increased after receipt of a negative test result over the same period of time. Children, as a group, did not show clinically significant distress over the first year following predictive genetic testing. Adults were more likely to be clinically anxious if they received a positive result or were low in optimism or self-esteem, with interacting effects. The association between anxiety, self-esteem, and optimism

  5. Do abundance distributions and species aggregation correctly predict macroecological biodiversity patterns in tropical forests?

    Science.gov (United States)

    Wiegand, Thorsten; Lehmann, Sebastian; Huth, Andreas; Fortin, Marie‐Josée

    2016-01-01

    Abstract Aim It has been recently suggested that different ‘unified theories of biodiversity and biogeography’ can be characterized by three common ‘minimal sufficient rules’: (1) species abundance distributions follow a hollow curve, (2) species show intraspecific aggregation, and (3) species are independently placed with respect to other species. Here, we translate these qualitative rules into a quantitative framework and assess if these minimal rules are indeed sufficient to predict multiple macroecological biodiversity patterns simultaneously. Location Tropical forest plots in Barro Colorado Island (BCI), Panama, and in Sinharaja, Sri Lanka. Methods We assess the predictive power of the three rules using dynamic and spatial simulation models in combination with census data from the two forest plots. We use two different versions of the model: (1) a neutral model and (2) an extended model that allowed for species differences in dispersal distances. In a first step we derive model parameterizations that correctly represent the three minimal rules (i.e. the model quantitatively matches the observed species abundance distribution and the distribution of intraspecific aggregation). In a second step we applied the parameterized models to predict four additional spatial biodiversity patterns. Results Species‐specific dispersal was needed to quantitatively fulfil the three minimal rules. The model with species‐specific dispersal correctly predicted the species–area relationship, but failed to predict the distance decay, the relationship between species abundances and aggregations, and the distribution of a spatial co‐occurrence index of all abundant species pairs. These results were consistent over the two forest plots. Main conclusions The three ‘minimal sufficient’ rules only provide an incomplete approximation of the stochastic spatial geometry of biodiversity in tropical forests. The assumption of independent interspecific placements is most

  6. Contrasting the Genetic Patterns of Microbial Communities in Soda Lakes with and without Cyanobacterial Bloom.

    Science.gov (United States)

    Andreote, Ana P D; Dini-Andreote, Francisco; Rigonato, Janaina; Machineski, Gabriela Silva; Souza, Bruno C E; Barbiero, Laurent; Rezende-Filho, Ary T; Fiore, Marli F

    2018-01-01

    Soda lakes have high levels of sodium carbonates and are characterized by salinity and elevated pH. These ecosystems are found across Africa, Europe, Asia, Australia, North, Central, and South America. Particularly in Brazil, the Pantanal region has a series of hundreds of shallow soda lakes (ca. 600) potentially colonized by a diverse haloalkaliphilic microbial community. Biological information of these systems is still elusive, in particular data on the description of the main taxa involved in the biogeochemical cycling of life-important elements. Here, we used metagenomic sequencing to contrast the composition and functional patterns of the microbial communities of two distinct soda lakes from the sub-region Nhecolândia, state of Mato Grosso do Sul, Brazil. These two lakes differ by permanent cyanobacterial blooms (Salina Verde, green-water lake) and by no record of cyanobacterial blooms (Salina Preta, black-water lake). The dominant bacterial species in the Salina Verde bloom was Anabaenopsis elenkinii . This cyanobacterium altered local abiotic parameters such as pH, turbidity, and dissolved oxygen and consequently the overall structure of the microbial community. In Salina Preta, the microbial community had a more structured taxonomic profile. Therefore, the distribution of metabolic functions in Salina Preta community encompassed a large number of taxa, whereas, in Salina Verde, the functional potential was restrained across a specific set of taxa. Distinct signatures in the abundance of genes associated with the cycling of carbon, nitrogen, and sulfur were found. Interestingly, genes linked to arsenic resistance metabolism were present at higher abundance in Salina Verde and they were associated with the cyanobacterial bloom. Collectively, this study advances fundamental knowledge on the composition and genetic potential of microbial communities inhabiting tropical soda lakes.

  7. Contrasting the Genetic Patterns of Microbial Communities in Soda Lakes with and without Cyanobacterial Bloom

    Science.gov (United States)

    Andreote, Ana P. D.; Dini-Andreote, Francisco; Rigonato, Janaina; Machineski, Gabriela Silva; Souza, Bruno C. E.; Barbiero, Laurent; Rezende-Filho, Ary T.; Fiore, Marli F.

    2018-01-01

    Soda lakes have high levels of sodium carbonates and are characterized by salinity and elevated pH. These ecosystems are found across Africa, Europe, Asia, Australia, North, Central, and South America. Particularly in Brazil, the Pantanal region has a series of hundreds of shallow soda lakes (ca. 600) potentially colonized by a diverse haloalkaliphilic microbial community. Biological information of these systems is still elusive, in particular data on the description of the main taxa involved in the biogeochemical cycling of life-important elements. Here, we used metagenomic sequencing to contrast the composition and functional patterns of the microbial communities of two distinct soda lakes from the sub-region Nhecolândia, state of Mato Grosso do Sul, Brazil. These two lakes differ by permanent cyanobacterial blooms (Salina Verde, green-water lake) and by no record of cyanobacterial blooms (Salina Preta, black-water lake). The dominant bacterial species in the Salina Verde bloom was Anabaenopsis elenkinii. This cyanobacterium altered local abiotic parameters such as pH, turbidity, and dissolved oxygen and consequently the overall structure of the microbial community. In Salina Preta, the microbial community had a more structured taxonomic profile. Therefore, the distribution of metabolic functions in Salina Preta community encompassed a large number of taxa, whereas, in Salina Verde, the functional potential was restrained across a specific set of taxa. Distinct signatures in the abundance of genes associated with the cycling of carbon, nitrogen, and sulfur were found. Interestingly, genes linked to arsenic resistance metabolism were present at higher abundance in Salina Verde and they were associated with the cyanobacterial bloom. Collectively, this study advances fundamental knowledge on the composition and genetic potential of microbial communities inhabiting tropical soda lakes. PMID:29520256

  8. Contrasting the Genetic Patterns of Microbial Communities in Soda Lakes with and without Cyanobacterial Bloom

    Directory of Open Access Journals (Sweden)

    Ana P. D. Andreote

    2018-02-01

    Full Text Available Soda lakes have high levels of sodium carbonates and are characterized by salinity and elevated pH. These ecosystems are found across Africa, Europe, Asia, Australia, North, Central, and South America. Particularly in Brazil, the Pantanal region has a series of hundreds of shallow soda lakes (ca. 600 potentially colonized by a diverse haloalkaliphilic microbial community. Biological information of these systems is still elusive, in particular data on the description of the main taxa involved in the biogeochemical cycling of life-important elements. Here, we used metagenomic sequencing to contrast the composition and functional patterns of the microbial communities of two distinct soda lakes from the sub-region Nhecolândia, state of Mato Grosso do Sul, Brazil. These two lakes differ by permanent cyanobacterial blooms (Salina Verde, green-water lake and by no record of cyanobacterial blooms (Salina Preta, black-water lake. The dominant bacterial species in the Salina Verde bloom was Anabaenopsis elenkinii. This cyanobacterium altered local abiotic parameters such as pH, turbidity, and dissolved oxygen and consequently the overall structure of the microbial community. In Salina Preta, the microbial community had a more structured taxonomic profile. Therefore, the distribution of metabolic functions in Salina Preta community encompassed a large number of taxa, whereas, in Salina Verde, the functional potential was restrained across a specific set of taxa. Distinct signatures in the abundance of genes associated with the cycling of carbon, nitrogen, and sulfur were found. Interestingly, genes linked to arsenic resistance metabolism were present at higher abundance in Salina Verde and they were associated with the cyanobacterial bloom. Collectively, this study advances fundamental knowledge on the composition and genetic potential of microbial communities inhabiting tropical soda lakes.

  9. Similar patterns of neural activity predict memory function during encoding and retrieval.

    Science.gov (United States)

    Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

    2017-07-15

    Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Could the outcome of the 2016 US elections have been predicted from past voting patterns?

    Science.gov (United States)

    Schmitz, Peter M. U.; Holloway, Jennifer P.; Dudeni-Tlhone, Nontembeko; Ntlangu, Mbulelo B.; Koen, Renee

    2018-05-01

    In South Africa, a team of analysts has for some years been using statistical techniques to predict election outcomes during election nights in South Africa. The prediction method involves using statistical clusters based on past voting patterns to predict final election outcomes, using a small number of released vote counts. With the US presidential elections in November 2016 hitting the global media headlines during the time period directly after successful predictions were done for the South African elections, the team decided to investigate adapting their meth-od to forecast the final outcome in the US elections. In particular, it was felt that the time zone differences between states would affect the time at which results are released and thereby provide a window of opportunity for doing election night prediction using only the early results from the eastern side of the US. Testing the method on the US presidential elections would have two advantages: it would determine whether the core methodology could be generalised, and whether it would work to include a stronger spatial element in the modelling, since the early results released would be spatially biased due to time zone differences. This paper presents a high-level view of the overall methodology and how it was adapted to predict the results of the US presidential elections. A discussion on the clustering of spatial units within the US is also provided and the spatial distribution of results together with the Electoral College prediction results from both a `test-run' and the final 2016 presidential elections are given and analysed.

  11. Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules

    Science.gov (United States)

    Ranganathan, Rajiv; Krishnan, Chandramouli; Dhaher, Yasin Y.; Rymer, William Z.

    2018-01-01

    The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy. PMID:26916510

  12. Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition.

    Science.gov (United States)

    Lu, Wei; Teng, Jun; Zhou, Qiushi; Peng, Qiexin

    2018-02-01

    The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project.

  13. Theories of Person Perception Predict Patterns of Neural Activity During Mentalizing.

    Science.gov (United States)

    Thornton, Mark A; Mitchell, Jason P

    2017-08-22

    Social life requires making inferences about other people. What information do perceivers spontaneously draw upon to make such inferences? Here, we test 4 major theories of person perception, and 1 synthetic theory that combines their features, to determine whether the dimensions of such theories can serve as bases for describing patterns of neural activity during mentalizing. While undergoing functional magnetic resonance imaging, participants made social judgments about well-known public figures. Patterns of brain activity were then predicted using feature encoding models that represented target people's positions on theoretical dimensions such as warmth and competence. All 5 theories of person perception proved highly accurate at reconstructing activity patterns, indicating that each could describe the informational basis of mentalizing. Cross-validation indicated that the theories robustly generalized across both targets and participants. The synthetic theory consistently attained the best performance-approximately two-thirds of noise ceiling accuracy--indicating that, in combination, the theories considered here can account for much of the neural representation of other people. Moreover, encoding models trained on the present data could reconstruct patterns of activity associated with mental state representations in independent data, suggesting the use of a common neural code to represent others' traits and states. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. On the control and prediction of the heating patterns of the annular phased array hyperthermia system

    International Nuclear Information System (INIS)

    Iskander, M.F.; Turner, P.F.; Knight, G.

    1984-01-01

    In previous publications the authors examined the electromagnetic (EM) power deposition and heating of the Annular Phased Array (APA) system developed by BSD Medical Corporation, using numerical EM and thermodynamics modeling. In this paper the results of recent efforts to vary and control the heating patterns produced by this system are described. in particular, data from several numerical simulations and experimental measurements are presented which illustrate the effect on the heating patterns achieved by varying the phase difference between the different ports of the APA system. Other heating patterns, produced by inactivating some of the APA ports, are also discussed. The remainder of the paper focuses on the feasibility of predicting the EM power depositions patterns of the APA solely through monitoring the E-field in the water bolus around the patient's body. In particular, it is shown that this E-field distribution depends primarily upon the outer geometry of the human body and is largely insensitive to the detailed distribution of inner tissues. Specific suggestions regarding the types, number, and location of E-field probes that can be used for such measurements are also given

  15. Pattern of genetic differentiation of an incipient speciation process: The case of the high Andean killifish Orestias

    Science.gov (United States)

    Guerrero-Jiménez, Claudia Jimena; Peña, Fabiola; Morales, Pamela; Méndez, Marco; Sallaberry, Michel; Vila, Irma; Poulin, Elie

    2017-01-01

    During the Pleistocene and Holocene, the southwest Andean Altiplano (17°-22°S) was affected by repeated fluctuations in water levels, high volcanic activity and major tectonic movements. In the early Holocene the humid Tauca phase shifted to the arid conditions that have lasted until the present, producing endorheic rivers, lakes, lagoons and wetlands. The endemic fish Orestias (Cyprinodontidae) represents a good model to observe the genetic differentiation that characterizes an incipient speciation process in allopatry since the morphospecies described inhabit a restricted geographic area, with present habitat fragmentation. The genetic diversity and population structure of four endemic morphospecies of Orestias (Cyprinodontidae) found in the Lauca National Park (LNP) analyzed with mitochondrial markers (Control Region) and eight microsatellites, revealed the existence of genetic groups that matches the fragmentation of these systems. High values of genetic and phylogeographic differentiation indices were observed between Chungará Lake and Piacota lagoon. The group composed of the Lauca River, Copapujo and Chuviri wetlands sampling sites showed a clear signal of expansion, with a star-like haplotype network. Levels of genetic differentiation were lower than in Chungará and Piacota, suggesting that these localities would have differentiated after the bottlenecks linked to the collapse of Parinacota volcano. The Parinacota sample showed a population signal that differed from the other localities revealing greater genetic diversity and a disperse network, presenting haplotypes shared with other LNP localities. A mixing pattern of the different genetic groups was evident using the microsatellite markers. The chronology of the vicariance events in LNP may indicate that the partition process of the Orestias populations was gradual. Considering this, and in view of the genetic results, we may conclude that the morphospecies from LNP are populations in ongoing

  16. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  17. Seasonal dependence of the predictable low-level circulation patterns over the tropical Indo-Pacific domain

    Science.gov (United States)

    Zhang, Tuantuan; Huang, Bohua; Yang, Song; Laohalertchai, Charoon

    2018-06-01

    The seasonal dependence of the prediction skill of 850-hPa monthly zonal wind over the tropical Indo-Pacific domain is examined using the ensemble reforecasts for 1983-2010 from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis and Reforecast (CFSRR) project. According to a maximum signal-to-noise empirical orthogonal function analysis, the most predictable patterns of atmospheric low-level circulation are associated with the developing and maturing phases of El Niño-Southern Oscillation (ENSO). The CFSv2 is capable of predicting these ENSO-related patterns up to 9-months in advance for all months, except for May-June when the effect of the spring barrier is strong. The other predictable climate processes associated with the low-level atmospheric circulation are more seasonally dependent. For winter and spring, the second most predictable patterns are associated with the ENSO decaying phase. Within these seasons, the monthly evolution of the predictable patterns is characterized by a southward shift of westerly wind anomalies, generated by the interaction between the annual cycle and the ENSO signals (i.e., the combination-mode). In general, the CFSv2 hindcast well predicts these patterns at least 5 months in advance for spring, while shows much lower skills for winter months. In summer, the second predictable patterns are associated with the western North Pacific (WNP) monsoon (i.e., the WNP anticyclone/cyclone) in short leads while associated with ENSO in longer leads (after 4-month lead). The second predictable patterns in fall are mainly associated with tropical Indian Ocean Dipole, which can be predicted 3 months in advance.

  18. Doppler laser imaging predicts response to topical minoxidil in the treatment of female pattern hair loss.

    Science.gov (United States)

    McCoy, J; Kovacevic, M; Situm, M; Stanimirovic, A; Bolanca, Z; Goren, A

    2016-01-01

    Topical minoxidil is the only drug approved by the US FDA for the treatment of female pattern hair loss. Unfortunately, following 16 weeks of daily application, less than 40% of patients regrow hair. Several studies have demonstrated that sulfotransferase enzyme activity in plucked hair follicles predicts topical minoxidil response in female pattern hair loss patients. However, due to patients’ discomfort with the procedure, and the time required to perform the enzymatic assay it would be ideal to develop a rapid, non-invasive test for sulfotransferase enzyme activity. Minoxidil is a pro-drug converted to its active form, minoxidil sulfate, by sulfotransferase enzymes in the outer root sheath of hair. Minoxidil sulfate is the active form required for both the promotion of hair regrowth and the vasodilatory effects of minoxidil. We thus hypothesized that laser Doppler velocimetry measurement of scalp blood perfusion subsequent to the application of topical minoxidil would correlate with sulfotransferase enzyme activity in plucked hair follicles. In this study, plucked hair follicles from female pattern hair loss patients were analyzed for sulfotransferase enzyme activity. Additionally, laser Doppler velocimetry was used to measure the change in scalp perfusion at 15, 30, 45, and 60 minutes, after the application of minoxidil. In agreement with our hypothesis, we discovered a correlation (r=1.0) between the change in scalp perfusion within 60 minutes after topical minoxidil application and sulfotransferase enzyme activity in plucked hairs. To our knowledge, this is the first study demonstrating the feasibility of using laser Doppler imaging as a rapid, non-invasive diagnostic test to predict topical minoxidil response in the treatment of female pattern hair loss.

  19. Hyperextension injuries of the knee. Do patterns of bone bruising predict soft tissue injury?

    Energy Technology Data Exchange (ETDEWEB)

    Ali, A.M.; Gibbons, C.E.R. [Chelsea and Westminster Hospital, Department of Orthopaedic Surgery, London (United Kingdom); Pillai, J.K.; Roberton, B.J. [Chelsea and Westminster Hospital, Department of Radiology, London (United Kingdom); Gulati, V. [Homerton University Hospital, Department of Orthopaedic Surgery, London (United Kingdom)

    2018-02-15

    To establish whether patterns of soft tissue injury following knee hyperextension are associated with post-traumatic 'bone bruise' distribution. Patients with a knee MRI within one year of hyperextension injury were identified at our institution over a 7 year period. MRIs, plain radiographs and clinical details of these patients were reviewed. Twenty-five patients were identified (median time from injury to MRI = 24 days). The most common sites of bone bruising were the anteromedial tibial plateau (48%) and anterolateral tibial plateau (44%). There were high rates of injury to the posterior capsule (52%), ACL (40%) and PCL (40%) but lower rates of injury to the menisci (20%), medial and lateral collateral ligaments (16%) and posterolateral corner (16%). Anterior tibial plateau oedema and rupture of the posterior capsule predicted cruciate ligament injury [OR = 10.5 (p = 0.02) and 24.0 (p = 0.001) respectively]. Whilst anterolateral tibial plateau oedema strongly predicted PCL injury [OR = 26.0, p = 0.003], ACL injury was associated with a variable pattern of bone bruising. Meniscal injury was unrelated to the extent or pattern of bone bruising. 5 out of 8 patients with a 'double sulcus' on the lateral radiograph had ACL injury. The presence of a double sulcus showed significant association with anteromedial kissing contusions (OR = 7.8, p = 0.03). Following knee hyperextension, bone bruising patterns may be associated with cruciate ligament injury. Other structures are injured less frequently and have weaker associations with bone bruise distribution. The double sulcus sign is a radiographic marker that confers a high probability of ACL injury. (orig.)

  20. Regional patterns of genetic diversity in swine influenza A viruses in the United States from 2010 to 2016.

    Science.gov (United States)

    Walia, Rasna R; Anderson, Tavis K; Vincent, Amy L

    2018-04-06

    Regular spatial and temporal analyses of the genetic diversity and evolutionary patterns of influenza A virus (IAV) in swine informs control efforts and improves animal health. Initiated in 2009, the USDA passively surveils IAV in U.S. swine, with a focus on subtyping clinical respiratory submissions, sequencing at minimum the hemagglutinin (HA) and neuraminidase (NA) genes, and sharing these data publicly. In this study, our goal was to quantify and describe regional and national patterns in the genetic diversity and evolution of IAV in U.S. swine from 2010 to 2016. A comprehensive phylogenetic and epidemiological analysis of publicly available HA and NA genes generated by the USDA surveillance system collected from January 2010 to December 2016 was conducted. The dominant subtypes and genetic clades detected during the study period were H1N1 (H1-γ/1A.3.3.3, N1-classical, 29%), H1N2 (H1-δ1/1B.2.2, N2-2002, 27%), and H3N2 (H3-IV-A, N2-2002, 15%), but many other minor clades were also maintained. Year-round circulation was observed, with a primary epidemic peak in October-November and a secondary epidemic peak in March-April. Partitioning these data into 5 spatial zones revealed that genetic diversity varied regionally and was not correlated with aggregated national patterns of HA/NA diversity. These data suggest that vaccine composition and control efforts should consider IAV diversity within swine production regions in addition to aggregated national patterns. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  1. Genetic variability of the pattern of night melatonin blood levels in relation to coat changes development in rabbits

    Directory of Open Access Journals (Sweden)

    Chemineau Philippe

    2004-03-01

    Full Text Available Abstract To assess the genetic variability in both the nocturnal increase pattern of melatonin concentration and photoresponsiveness in coat changes, an experiment on 422 Rex rabbits (from 23 males raised under a constant light programme from birth was performed. The animals were sampled at 12 weeks of age, according to 4 periods over a year. Blood samples were taken 7 times during the dark phase and up to 1 h after the lighting began. Maturity of the fur was assessed at pelting. Heritability estimates of blood melatonin concentration (0.42, 0.17 and 0.11 at mid-night, 13 and 15 h after lights-out respectively and strong genetic correlations between fur maturity and melatonin levels at the end of the dark phase (-0.64 indicates that (i the variability of the nocturnal pattern of melatonin levels is under genetic control and (ii the duration of the nocturnal melatonin increase is a genetic component of photoresponsiveness in coat changes.

  2. Independence and interdependence predict health and wellbeing: divergent patterns in the United States and Japan

    Directory of Open Access Journals (Sweden)

    Shinobu Kitayama

    2010-12-01

    Full Text Available A cross-cultural survey was used to examine two hypotheses designed to link culture to well-being and health. The first hypothesis states that people are motivated toward prevalent cultural mandates of either independence (personal control in the United States or interdependence (relational harmony in Japan. As predicted, Americans with compromised personal control and Japanese with strained relationships reported high perceived constraint. The second hypothesis holds that people achieve well-being and health through actualizing the respective cultural mandates in their modes of being. As predicted, the strongest predictor of well-being and health was personal control in the United States, but the absence of relational strain in Japan. All analyses controlled for age, gender, and personality traits. The overall pattern of findings underscores culturally distinct pathways (independent versus interdependent in achieving these positive life outcomes.

  3. Can superconductivity be predicted with the aid of pattern recognition techniques

    International Nuclear Information System (INIS)

    Pijpers, F.W.

    1982-01-01

    Pattern recognition techniques were employed in order to investigate the possibility to find features of the elements of the periodic system that may be relevant for the description of their behaviour with respect to superconductivity. Learning machines were constructed using those elements of the periodic system whose superconducting properties have been well studied. Relevant features appear to be the electronic work function and the number of valence electrons as given by Miedema, the specific heat, the heat of melting, the heat of sublimation, the melting point and the atomic radius. The learning machines have a predicting capability of the order of 90%. The predictive power of these machines concerning the superconducting behaviour of the alkali and alkaline-earth metals belonging to a given test set, however, appears to be less convincing

  4. Externalizing problems in childhood and adolescence predict subsequent educational achievement but for different genetic and environmental reasons.

    Science.gov (United States)

    Lewis, Gary J; Asbury, Kathryn; Plomin, Robert

    2017-03-01

    Childhood behavior problems predict subsequent educational achievement; however, little research has examined the etiology of these links using a longitudinal twin design. Moreover, it is unknown whether genetic and environmental innovations provide incremental prediction for educational achievement from childhood to adolescence. We examined genetic and environmental influences on parental ratings of behavior problems across childhood (age 4) and adolescence (ages 12 and 16) as predictors of educational achievement at age 16 using a longitudinal classical twin design. Shared-environmental influences on anxiety, conduct problems, and peer problems at age 4 predicted educational achievement at age 16. Genetic influences on the externalizing behaviors of conduct problems and hyperactivity at age 4 predicted educational achievement at age 16. Moreover, novel genetic and (to a lesser extent) nonshared-environmental influences acting on conduct problems and hyperactivity emerged at ages 12 and 16, adding to the genetic prediction from age 4. These findings demonstrate that genetic and shared-environmental factors underpinning behavior problems in early childhood predict educational achievement in midadolescence. These findings are consistent with the notion that early-childhood behavior problems reflect the initiation of a life-course persistent trajectory with concomitant implications for social attainment. However, we also find evidence that genetic and nonshared-environment innovations acting on behavior problems have implications for subsequent educational achievement, consistent with recent work arguing that adolescence represents a sensitive period for socioaffective development. © 2016 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

  5. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

    Science.gov (United States)

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-10-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

  6. Paroxysmal atrial fibrillation prediction based on HRV analysis and non-dominated sorting genetic algorithm III.

    Science.gov (United States)

    Boon, K H; Khalil-Hani, M; Malarvili, M B

    2018-01-01

    This paper presents a method that able to predict the paroxysmal atrial fibrillation (PAF). The method uses shorter heart rate variability (HRV) signals when compared to existing methods, and achieves good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to electrically stabilize and prevent the onset of atrial arrhythmias with different pacing techniques. We propose a multi-objective optimization algorithm based on the non-dominated sorting genetic algorithm III for optimizing the baseline PAF prediction system, that consists of the stages of pre-processing, HRV feature extraction, and support vector machine (SVM) model. The pre-processing stage comprises of heart rate correction, interpolation, and signal detrending. After that, time-domain, frequency-domain, non-linear HRV features are extracted from the pre-processed data in feature extraction stage. Then, these features are used as input to the SVM for predicting the PAF event. The proposed optimization algorithm is used to optimize the parameters and settings of various HRV feature extraction algorithms, select the best feature subsets, and tune the SVM parameters simultaneously for maximum prediction performance. The proposed method achieves an accuracy rate of 87.7%, which significantly outperforms most of the previous works. This accuracy rate is achieved even with the HRV signal length being reduced from the typical 30 min to just 5 min (a reduction of 83%). Furthermore, another significant result is the sensitivity rate, which is considered more important that other performance metrics in this paper, can be improved with the trade-off of lower specificity. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

    Science.gov (United States)

    Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

    2002-01-01

    Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic

  8. Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

    Science.gov (United States)

    Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

    2017-05-01

    Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  9. Predictive genetic testing in children: constitutional mismatch repair deficiency cancer predisposing syndrome.

    Science.gov (United States)

    Bruwer, Zandrè; Algar, Ursula; Vorster, Alvera; Fieggen, Karen; Davidson, Alan; Goldberg, Paul; Wainwright, Helen; Ramesar, Rajkumar

    2014-04-01

    Biallelic germline mutations in mismatch repair genes predispose to constitutional mismatch repair deficiency syndrome (CMMR-D). The condition is characterized by a broad spectrum of early-onset tumors, including hematological, brain and bowel and is frequently associated with features of Neurofibromatosis type 1. Few definitive screening recommendations have been suggested and no published reports have described predictive testing. We report on the first case of predictive testing for CMMR-D following the identification of two non-consanguineous parents, with the same heterozygous mutation in MLH1: c.1528C > T. The genetic counseling offered to the family, for their two at-risk daughters, is discussed with a focus on the ethical considerations of testing children for known cancer-causing variants. The challenges that are encountered when reporting on heterozygosity in a child younger than 18 years (disclosure of carrier status and risk for Lynch syndrome), when discovered during testing for homozygosity, are addressed. In addition, the identification of CMMR-D in a three year old, and the recommended clinical surveillance that was proposed for this individual is discussed. Despite predictive testing and presymptomatic screening, the sudden death of the child with CMMR-D syndrome occurred 6 months after her last surveillance MRI. This report further highlights the difficulty of developing guidelines, as a result of the rarity of cases and diversity of presentation.

  10. Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

    Science.gov (United States)

    Crossa, José; Campos, Gustavo de Los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

    2010-10-01

    The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

  11. A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

    International Nuclear Information System (INIS)

    Bunyamin, Muhammad Afif; Yap, Keem Siah; Aziz, Nur Liyana Afiqah Abdul; Tiong, Sheih Kiong; Wong, Shen Yuong; Kamal, Md Fauzan

    2013-01-01

    This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. It is able to estimate unknown model parameters from inputs data. On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. By combining the LR and GA (GA-LR), this new technique is able to select the most important input features as well as giving more accurate prediction by minimizing the prediction errors. This new technique is able to produce more consistent of gas emission estimation, which may help in reducing population to the environment. In this paper, the study's interest is focused on nitrous oxides (NOx) prediction. The results of the experiment are encouraging.

  12. The fatigue life prediction of aluminium alloy using genetic algorithm and neural network

    Science.gov (United States)

    Susmikanti, Mike

    2013-09-01

    The behavior of the fatigue life of the industrial materials is very important. In many cases, the material with experiencing fatigue life cannot be avoided, however, there are many ways to control their behavior. Many investigations of the fatigue life phenomena of alloys have been done, but it is high cost and times consuming computation. This paper report the modeling and simulation approaches to predict the fatigue life behavior of Aluminum Alloys and resolves some problems of computation. First, the simulation using genetic algorithm was utilized to optimize the load to obtain the stress values. These results can be used to provide N-cycle fatigue life of the material. Furthermore, the experimental data was applied as input data in the neural network learning, while the samples data were applied for testing of the training data. Finally, the multilayer perceptron algorithm is applied to predict whether the given data sets in accordance with the fatigue life of the alloy. To achieve rapid convergence, the Levenberg-Marquardt algorithm was also employed. The simulations results shows that the fatigue behaviors of aluminum under pressure can be predicted. In addition, implementation of neural networks successfully identified a model for material fatigue life.

  13. SESAM – a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

    DEFF Research Database (Denmark)

    Guisan, Antoine; Rahbek, Carsten

    2011-01-01

    Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts...

  14. Dynamical prediction and pattern mapping in short-term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Aguirre, Luis Antonio; Rodrigues, Daniela D.; Lima, Silvio T. [Departamento de Engenharia Eletronica, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil); Martinez, Carlos Barreira [Departamento de Engenharia Hidraulica e Recursos Hidricos, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil)

    2008-01-15

    This work will not put forward yet another scheme for short-term load forecasting but rather will provide evidences that may improve our understanding about fundamental issues which underlay load forecasting problems. In particular, load forecasting will be decomposed into two main problems, namely dynamical prediction and pattern mapping. It is argued that whereas the latter is essentially static and becomes nonlinear when weekly features in the data are taken into account, the former might not be deterministic at all. In such cases there is no determinism (serial correlations) in the data apart from the average cycle and the best a model can do is to perform pattern mapping. Moreover, when there is determinism in addition to the average cycle, the underlying dynamics are sometimes linear, in which case there is no need to resort to nonlinear models to perform dynamical prediction. Such conclusions were confirmed using real load data and surrogate data analysis. In a sense, the paper details and organizes some general beliefs found in the literature on load forecasting. This sheds some light on real model-building and forecasting problems and helps understand some apparently conflicting results reported in the literature. (author)

  15. Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study.

    Directory of Open Access Journals (Sweden)

    Meeshanthini V Dogan

    Full Text Available An improved method for detecting coronary heart disease (CHD could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.

  16. Comparison of genetic algorithm and imperialist competitive algorithms in predicting bed load transport in clean pipe.

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein

    2014-01-01

    The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.

  17. Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers.

    Science.gov (United States)

    Taheri, Mahboobeh; Mohebbi, Ali

    2008-08-30

    In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm (GA), has been used to predict collection efficiency in venturi scrubbers. The experimental input data, including particle diameter, throat gas velocity, liquid to gas flow rate ratio, throat hydraulic diameter, pressure drop across the venturi scrubber and collection efficiency as an output, have been used to create a GA-artificial neural network (ANN) model. The testing results from the model are in good agreement with the experimental data. Comparison of the results of the GA optimized ANN model with the results from the trial-and-error calibrated ANN model indicates that the GA-ANN model is more efficient. Finally, the effects of operating parameters such as liquid to gas flow rate ratio, throat gas velocity, and particle diameter on collection efficiency were determined.

  18. Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data

    Directory of Open Access Journals (Sweden)

    Sungho Won

    2015-01-01

    Full Text Available Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called “large P and small N” problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.

  19. Performance of genetic risk factors in prediction of trichloroethylene induced hypersensitivity syndrome.

    Science.gov (United States)

    Dai, Yufei; Chen, Ying; Huang, Hanlin; Zhou, Wei; Niu, Yong; Zhang, Mingrong; Bin, Ping; Dong, Haiyan; Jia, Qiang; Huang, Jianxun; Yi, Juan; Liao, Qijun; Li, Haishan; Teng, Yanxia; Zang, Dan; Zhai, Qingfeng; Duan, Huawei; Shen, Juan; He, Jiaxi; Meng, Tao; Sha, Yan; Shen, Meili; Ye, Meng; Jia, Xiaowei; Xiang, Yingping; Huang, Huiping; Wu, Qifeng; Shi, Mingming; Huang, Xianqing; Yang, Huanming; Luo, Longhai; Li, Sai; Li, Lin; Zhao, Jinyang; Li, Laiyu; Wang, Jun; Zheng, Yuxin

    2015-07-20

    Trichloroethylene induced hypersensitivity syndrome is dose-independent and potentially life threatening disease, which has become one of the serious occupational health issues and requires intensive treatment. To discover the genetic risk factors and evaluate the performance of risk prediction model for the disease, we conducted genomewide association study and replication study with total of 174 cases and 1761 trichloroethylene-tolerant controls. Fifty seven SNPs that exceeded the threshold for genome-wide significance (P < 5 × 10(-8)) were screened to relate with the disease, among which two independent SNPs were identified, that is rs2857281 at MICA (odds ratio, 11.92; P meta = 1.33 × 10(-37)) and rs2523557 between HLA-B and MICA (odds ratio, 7.33; P meta = 8.79 × 10(-35)). The genetic risk score with these two SNPs explains at least 20.9% of the disease variance and up to 32.5-fold variation in inter-individual risk. Combining of two SNPs as predictors for the disease would have accuracy of 80.73%, the area under receiver operator characteristic curves (AUC) scores was 0.82 with sensitivity of 74% and specificity of 85%, which was considered to have excellent discrimination for the disease, and could be considered for translational application for screening employees before exposure.

  20. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  1. ALDH1 and podoplanin expression patterns predict the risk of malignant transformation in oral leukoplakia.

    Science.gov (United States)

    Habiba, Umma; Hida, Kyoko; Kitamura, Tetsuya; Matsuda, Aya Yanagawa; Higashino, Fumihiro; Ito, Yoichi M; Ohiro, Yoichi; Totsuka, Yasunori; Shindoh, Masanobu

    2017-01-01

    Oral leukoplakia (OL) is a clinically diagnosed preneoplastic lesion of the oral cavity with an increased oral cancer risk. However, the risk of malignant transformation is still difficult to assess. The objective of the present study was to examine the expression patterns of aldehyde dehydrogenase 1 (ALDH1) and podoplanin in OL, and to determine their roles in predicting oral cancer development. In the present study, the expression patterns of ALDH1 and podoplanin were determined in samples from 79 patients with OL. The association between protein expression and clinicopathological parameters, including oral cancer-free survival, was analyzed during a mean follow-up period of 3.4 years. Expression of ALDH1 and podoplanin was observed in 61 and 67% patients, respectively. Kaplan-Meier analysis demonstrated that the expression of the proteins was correlated with the risk of progression to oral cancer. Multivariate analysis revealed that expression of ALDH1 and podoplanin was associated with 3.02- and 2.62-fold increased risk of malignant transformation, respectively. The malignant transformation risk of OL was considerably higher in cases with expression of both proteins. Point-prevalence analysis revealed that 66% of patients with co-expression of ALDH1 and podoplanin developed oral cancer. Taken together, our data indicate that ALDH1 and podoplanin expression patterns in OL are associated with oral cancer development, suggesting that ALDH1 and podoplanin may be useful biomarkers to identify OL patients with a substantially high oral cancer risk.

  2. Prediction of pediatric unipolar depression using multiple neuromorphometric measurements: a pattern classification approach.

    Science.gov (United States)

    Wu, Mon-Ju; Wu, Hanjing Emily; Mwangi, Benson; Sanches, Marsal; Selvaraj, Sudhakar; Zunta-Soares, Giovana B; Soares, Jair C

    2015-03-01

    Diagnosis of pediatric neuropsychiatric disorders such as unipolar depression is largely based on clinical judgment - without objective biomarkers to guide diagnostic process and subsequent therapeutic interventions. Neuroimaging studies have previously reported average group-level neuroanatomical differences between patients with pediatric unipolar depression and healthy controls. In the present study, we investigated the utility of multiple neuromorphometric indices in distinguishing pediatric unipolar depression patients from healthy controls at an individual subject level. We acquired structural T1-weighted scans from 25 pediatric unipolar depression patients and 26 demographically matched healthy controls. Multiple neuromorphometric indices such as cortical thickness, volume, and cortical folding patterns were obtained. A support vector machine pattern classification model was 'trained' to distinguish individual subjects with pediatric unipolar depression from healthy controls based on multiple neuromorphometric indices and model predictive validity (sensitivity and specificity) calculated. The model correctly identified 40 out of 51 subjects translating to 78.4% accuracy, 76.0% sensitivity and 80.8% specificity, chi-square p-value = 0.000049. Volumetric and cortical folding abnormalities in the right thalamus and right temporal pole respectively were most central in distinguishing individual patients with pediatric unipolar depression from healthy controls. These findings provide evidence that a support vector machine pattern classification model using multiple neuromorphometric indices may qualify as diagnostic marker for pediatric unipolar depression. In addition, our results identified the most relevant neuromorphometric features in distinguishing PUD patients from healthy controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. The pattern of eigenfrequencies of radial overtones which is predicted for a specified Earth-model

    Directory of Open Access Journals (Sweden)

    E. R. LAPWOOD

    1977-06-01

    Full Text Available In 1974 Anderssen and Cleary examined the distribution of eigenfrequencies
    of radial overtones in torsional oscillations of Earth-models.
    They pointed out that according to Sturm-Liouville theory this distribution
    should approach asymptotically, for large overtone number m,
    the value nnz/y, where y is the time taken by a shear-wave to travel
    along a radius from the core-mantle interface to the surface, provided
    elastic parameters vary continuously along the radius. They found that,
    for all the models which they considered, the distributions of eigenfrequencies
    deviated from the asymptote by amounts which depended on
    the existence and size of internal discontinuities. Lapwood (1975 showed
    that such deviations were to be expected from Sturm-Liouville theory,
    and McNabb, Anderssen and Lapwood (1976 extended Sturm-Liouville
    theory to apply to differential equations with discontinuous coefficients.
    Anderssen (1977 used their results to show how to predict the pattern
    of deviations —called by McNabb et al. the solotone effect— for a
    given discontinuity in an Earth-model.
    Recently Sato and Lapwood (1977, in a series of papers which will
    be referred to here simply as I, II, III, have explored the solotone effect
    for layered spherical shells, using approximations derived from an exacttheory which holds for uniform layering. They have shown how the
    form of the pattern of eigenfrequencies, which is the graph of
    S — YMUJI/N — m against m, where ,„CJI is the frequency of the m"'
    overtone in the I"' (Legendre mode of torsional oscillation, is determined
    as to periodicity (or quasi-periodicity by the thicknesses and velocities
    of the layers, and as to amplitude by the amounts of the discontinuities
    (III. The pattern of eigenfrequencies proves to be extremely sensitive
    to small changes in layer-thicknesses in a model.
    In

  4. Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry.

    Science.gov (United States)

    Wen, Wanqing; Shu, Xiao-Ou; Guo, Xingyi; Cai, Qiuyin; Long, Jirong; Bolla, Manjeet K; Michailidou, Kyriaki; Dennis, Joe; Wang, Qin; Gao, Yu-Tang; Zheng, Ying; Dunning, Alison M; García-Closas, Montserrat; Brennan, Paul; Chen, Shou-Tung; Choi, Ji-Yeob; Hartman, Mikael; Ito, Hidemi; Lophatananon, Artitaya; Matsuo, Keitaro; Miao, Hui; Muir, Kenneth; Sangrajrang, Suleeporn; Shen, Chen-Yang; Teo, Soo H; Tseng, Chiu-Chen; Wu, Anna H; Yip, Cheng Har; Simard, Jacques; Pharoah, Paul D P; Hall, Per; Kang, Daehee; Xiang, Yongbing; Easton, Douglas F; Zheng, Wei

    2016-12-08

    Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry. We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk. We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively. Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.

  5. Jellyfish prediction of occurrence from remote sensing data and a non-linear pattern recognition approach

    Science.gov (United States)

    Albajes-Eizagirre, Anton; Romero, Laia; Soria-Frisch, Aureli; Vanhellemont, Quinten

    2011-11-01

    Impact of jellyfish in human activities has been increasingly reported worldwide in recent years. Segments such as tourism, water sports and leisure, fisheries and aquaculture are commonly damaged when facing blooms of gelatinous zooplankton. Hence the prediction of the appearance and disappearance of jellyfish in our coasts, which is not fully understood from its biological point of view, has been approached as a pattern recognition problem in the paper presented herein, where a set of potential ecological cues was selected to test their usefulness for prediction. Remote sensing data was used to describe environmental conditions that could support the occurrence of jellyfish blooms with the aim of capturing physical-biological interactions: forcing, coastal morphology, food availability, and water mass characteristics are some of the variables that seem to exert an effect on jellyfish accumulation on the shoreline, under specific spatial and temporal windows. A data-driven model based on computational intelligence techniques has been designed and implemented to predict jellyfish events on the beach area as a function of environmental conditions. Data from 2009 over the NW Mediterranean continental shelf have been used to train and test this prediction protocol. Standard level 2 products are used from MODIS (NASA OceanColor) and MERIS (ESA - FRS data). The procedure for designing the analysis system can be described as following. The aforementioned satellite data has been used as feature set for the performance evaluation. Ground truth has been extracted from visual observations by human agents on different beach sites along the Catalan area. After collecting the evaluation data set, the performance between different computational intelligence approaches have been compared. The outperforming one in terms of its generalization capability has been selected for prediction recall. Different tests have been conducted in order to assess the prediction capability of the

  6. Distinct patterns of ALDH1A1 expression predict metastasis and poor outcome of colorectal carcinoma

    Science.gov (United States)

    Xu, Sen-Lin; Zeng, Dong-Zu; Dong, Wei-Guo; Ding, Yan-Qing; Rao, Jun; Duan, Jiang-Jie; Liu, Qing; Yang, Jing; Zhan, Na; Liu, Ying; Hu, Qi-Ping; Zhang, Xia; Cui, You-Hong; Kung, Hsiang-Fu; Yu, Shi-Cang; Bian, Xiu-Wu

    2014-01-01

    Purpose: Aldehyde dehydrogenase 1A1 (ALDH1A1) has been proposed as a candidate biomarker for colorectal carcinoma (CRC). However, the heterogeneity of its expression makes it difficult to predict the outcome of CRC. The aim of this study was to evaluate the diagnostic and prognostic value of this molecule in CRC. Methods and Results: In this study, we examined ALDH1A1 expression by immunohistochemistry including 406 cases of primary CRC with corresponding adjacent mucosa, with confirmation of real-time PCR and Western blotting. We found that the expression patterns of ALDH1A1 were heterogeneous in the CRC and corresponding adjacent tissues. We defined the ratio of ALDH1A1 level in adjacent mucosa to that in tumor tissues as RA/C and found that the capabilities of tumor invasion and metastasis in the tumors with RA/C < 1 were significantly higher than those with RA/C ≥ 1. Follow-up data showed the worse prognoses in the CRC patients with RA/C < 1. For understanding the underlying mechanism, the localization of β-catenin was detected in the CRC tissues with different patterns of ALDH1A1 expression from 221 patients and β-catenin was found preferentially expressed in cell nuclei of the tumors with RA/C < 1 and ALDH1A1high expression of HT29 cell line, indicating that nuclear translocation of β-catenin might contribute to the increased potentials of invasion and metastasis. Conclusion: Our results indicate that RA/C is a novel biomarker to reflect the distinct expression patterns of ALDH1A1 for predicting metastasis and prognosis of CRC. PMID:25031716

  7. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science

  8. PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation.

    Science.gov (United States)

    Tang, Haiming; Thomas, Paul D

    2016-07-15

    PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database. PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: pdthomas@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Short communication: Genetic study of methane production predicted from milk fat composition in dairy cows.

    Science.gov (United States)

    van Engelen, S; Bovenhuis, H; Dijkstra, J; van Arendonk, J A M; Visker, M H P W

    2015-11-01

    Dairy cows produce enteric methane, a greenhouse gas with 25 times the global warming potential of CO2. Breeding could make a permanent, cumulative, and long-term contribution to methane reduction. Due to a lack of accurate, repeatable, individual methane measurements needed for breeding, indicators of methane production based on milk fatty acids have been proposed. The aim of the present study was to quantify the genetic variation for predicted methane yields. The milk fat composition of 1,905 first-lactation Dutch Holstein-Friesian cows was used to investigate 3 different predicted methane yields (g/kg of DMI): Methane1, Methane2, and Methane3. Methane1 was based on the milk fat proportions of C17:0anteiso, C18:1 rans-10+11, C18:1 cis-11, and C18:1 cis-13 (R(2)=0.73). Methane2 was based on C4:0, C18:0, C18:1 trans-10+11, and C18:1 cis-11 (R(2)=0.70). Methane3 was based on C4:0, C6:0, and C18:1 trans-10+11 (R(2)=0.63). Predicted methane yields were demonstrated to be heritable traits, with heritabilities between 0.12 and 0.44. Breeding can, thus, be used to decrease methane production predicted based on milk fatty acids. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  10. Phylogeographic patterns of Lygus pratensis (Hemiptera: Miridae): Evidence for weak genetic structure and recent expansion in northwest China.

    Science.gov (United States)

    Zhang, Li-Juan; Cai, Wan-Zhi; Luo, Jun-Yu; Zhang, Shuai; Wang, Chun-Yi; Lv, Li-Min; Zhu, Xiang-Zhen; Wang, Li; Cui, Jin-Jie

    2017-01-01

    Lygus pratensis (L.) is an important cotton pest in China, especially in the northwest region. Nymphs and adults cause serious quality and yield losses. However, the genetic structure and geographic distribution of L. pratensis is not well known. We analyzed genetic diversity, geographical structure, gene flow, and population dynamics of L. pratensis in northwest China using mitochondrial and nuclear sequence datasets to study phylogeographical patterns and demographic history. L. pratensis (n = 286) were collected at sites across an area spanning 2,180,000 km2, including the Xinjiang and Gansu-Ningxia regions. Populations in the two regions could be distinguished based on mitochondrial criteria but the overall genetic structure was weak. The nuclear dataset revealed a lack of diagnostic genetic structure across sample areas. Phylogenetic analysis indicated a lack of population level monophyly that may have been caused by incomplete lineage sorting. The Mantel test showed a significant correlation between genetic and geographic distances among the populations based on the mtDNA data. However the nuclear dataset did not show significant correlation. A high level of gene flow among populations was indicated by migration analysis; human activities may have also facilitated insect movement. The availability of irrigation water and ample cotton hosts makes the Xinjiang region well suited for L. pratensis reproduction. Bayesian skyline plot analysis, star-shaped network, and neutrality tests all indicated that L. pratensis has experienced recent population expansion. Climatic changes and extensive areas occupied by host plants have led to population expansion of L. pratensis. In conclusion, the present distribution and phylogeographic pattern of L. pratensis was influenced by climate, human activities, and availability of plant hosts.

  11. Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction.

    Science.gov (United States)

    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

  12. The 5-HT2A receptor binding pattern in the human brain is strongly genetically determined

    DEFF Research Database (Denmark)

    Pinborg, Lars H; Arfan, Haroon; Haugbol, Steven

    2007-01-01

    With the appropriate radiolabeled tracers, positron emission tomography (PET) enables in vivo human brain imaging of markers for neurotransmission, including neurotransmitter synthesis, receptors, and transporters. Whereas structural imaging studies have provided compelling evidence that the human...... brain anatomy is largely genetically determined, it is currently unknown to what degree neuromodulatory markers are subjected to genetic and environmental influence. Changes in serotonin 2A (5-HT(2A)) receptors have been reported to occur in various neuropsychiatric disorders and an association between...

  13. Using soil seed banks to assess temporal patterns of genetic variation in invasive plant populations

    OpenAIRE

    Fennell, Mark; Gallagher, Tommy; Vintro, Luis Leon; Osborne, Bruce

    2014-01-01

    Most research on the genetics of invasive plant species has focused on analyzing spatial differences among existing populations. Using a long-established Gunnera tinctoria population from Ireland, we evaluated the potential of using plants derived from seeds associated with different soil layers to track genetic variation through time. This species and site were chosen because (1) G. tinctoria produces a large and persistent seed bank; (2) it has been present in this locality, Sraheens, for ∼...

  14. Late-Life Drinking Problems: The Predictive Roles of Drinking Level vs. Drinking Pattern.

    Science.gov (United States)

    Holahan, Charles J; Brennan, Penny L; Schutte, Kathleen K; Holahan, Carole K; Hixon, J Gregory; Moos, Rudolf H

    2017-05-01

    Research on late-middle-aged and older adults has focused primarily on average level of alcohol consumption, overlooking variability in underlying drinking patterns. The purpose of the present study was to examine the independent contributions of an episodic heavy pattern of drinking versus a high average level of drinking as prospective predictors of drinking problems. The sample comprised 1,107 adults ages 55-65 years at baseline. Alcohol consumption was assessed at baseline, and drinking problems were indexed across 20 years. We used prospective negative binomial regression analyses controlling for baseline drinking problems, as well as for demographic and health factors, to predict the number of drinking problems at each of four follow-up waves (1, 4, 10, and 20 years). Across waves where the effects were significant, a high average level of drinking (coefficients of 1.56, 95% CI [1.24, 1.95]; 1.48, 95% CI [1.11, 1.98]; and 1.85, 95% CI [1.23, 2.79] at 1, 10, and 20 years) and an episodic heavy pattern of drinking (coefficients of 1.61, 95% CI [1.30, 1.99]; 1.61, 95% CI [1.28, 2.03]; and 1.43, 95% CI [1.08, 1.90] at 1, 4, and 10 years) each independently increased the number of drinking problems by more than 50%. Information based only on average consumption underestimates the risk of drinking problems among older adults. Both a high average level of drinking and an episodic heavy pattern of drinking pose prospective risks of later drinking problems among older adults.

  15. Dermatoglyphics and Cheiloscopy as Key Tools in Resolving the Genetic Correlation of Inheritance Patterns in Cleft Lip and Palate Patients: An Assessment of 160 Patients.

    Science.gov (United States)

    Singh, Priyankar; Nathani, Dipesh B

    2017-09-01

      The objective of this study was to correlate dermatoglyphics and cheiloscopy with genetic inheritance in cleft lip and cleft palate patients.   This was a case-control study to look for asymmetry in finger and lip print patterns. All of the participants were divided into two equal groups (40 mothers and 40 fathers in each group). The data were analyzed by three evaluators who were blind to the study to avoid any chances of error.   A sample of 160 sporadic participants were identified and evaluated. Group A was composed of 80 healthy parents not affected by cleft lip and cleft palate but had at least one child born with nonsyndromic cleft. Group B consisted of 80 healthy parents not affected by cleft lip and cleft palate and had healthy children without cleft lip and cleft palate.   Main outcome measures were marked dermatoglyphic asymmetry and specific lip print pattern in the study group.   We found marked asymmetry in various fingerprints and specific type II and type III lip print in the study group when compared with the control group. It was observed that groove count on the lip was significantly more frequent in study group parents.   Our study determined that there is a significant correlation between increased dermatoglyphic asymmetry and specific type II and type III lip print pattern in parents of children born with cleft. This could act as an important screening marker for the prediction of cleft lip and cleft palate inheritance.

  16. Predictability of rainfall and teleconnections patterns influencing on Southwest Europe from sea surfaces temperatures

    Science.gov (United States)

    Lorenzo, M. N.; Iglesias, I.; Taboada, J. J.; Gómez-Gesteira, M.; Ramos, A. M.

    2009-04-01

    This work assesses the possibility of doing a forecast of rainfall and the main teleconnections patterns that influences climate in Southwest Europe by using sea surface temperature anomalies (SSTA). The area under study is located in the NW Iberian Peninsula. This region has a great oceanic influence on its climate and has an important dependency of the water resources. In this way if the different SST patterns are known, the different rainfall situations can be predicted. On the other hand, the teleconnection patterns, which have strong weight on rainfall, are influenced by the SSTA of different areas. In the light of this, the aim of this study is to explore the relationship between global SSTAs, rainfall and the main teleconnection patterns influencing on Europe. The SST data with a 2.0 degree resolution was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. A monthly averaged data from 1 January 1951 through December 2006 was considered. The monthly precipitation data from 1951-2006 were obtained from the database CLIMA of the University of Santiago de Compostela with data from the Meteorological State Agency (AEMET) and the Regional Government of Galicia. The teleconnection indices were taken of the Climate Prediction Center of the NOAA between 1950 and 2006. A monthly and seasonal study was analysed considering up to three months of delay in the first case and up to four seasons of delay in the second case. The Pearson product-moment correlation coefficient r was considered to quantify linear associations between SSTA and precipitation and/or SSTA and teleconnection indices. A test for field-significance was applied considering the properties of finiteness and interdependence of the spatial grid to avoid spurious correlations. Analysing the results obtained with the global SSTA and the teleconnection indices, a great number of ocean regions with high correlations can be found. The spatial patterns show very high correlations with Indian Ocean waters

  17. Monoamine Oxidase-A Genetic Variants and Childhood Abuse Predict Impulsiveness in Borderline Personality Disorder.

    Science.gov (United States)

    Kolla, Nathan J; Meyer, Jeffrey; Sanches, Marcos; Charbonneau, James

    2017-11-30

    Impulsivity is a core feature of borderline personality disorder (BPD) and antisocial personality disorder (ASPD) that likely arises from combined genetic and environmental influences. The interaction of the low activity variant of the monoamine oxidase-A (MAOA-L) gene and early childhood adversity has been shown to predict aggression in clinical and non-clinical populations. Although impulsivity is a risk factor for aggression in BPD and ASPD, little research has investigated potential gene-environment (G×E) influences impacting its expression in these conditions. Moreover, G×E interactions may differ by diagnosis. Full factorial analysis of variance was employed to investigate the influence of monoamine oxidase-A (MAO-A) genotype, childhood abuse, and diagnosis on Barratt Impulsiveness Scale-11 (BIS-11) scores in 61 individuals: 20 subjects with BPD, 18 subjects with ASPD, and 23 healthy controls. A group×genotype×abuse interaction was present (F(2,49)=4.4, p =0.018), such that the interaction of MAOA-L and childhood abuse predicted greater BIS-11 motor impulsiveness in BPD. Additionally, BPD subjects reported higher BIS-11 attentional impulsiveness versus ASPD participants (t(1,36)=2.3, p =0.025). These preliminary results suggest that MAOA-L may modulate the impact of childhood abuse on impulsivity in BPD. Results additionally indicate that impulsiveness may be expressed differently in BPD and ASPD.

  18. Prediction and optimization of thinning in automotive sealing cover using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Ganesh M. Kakandikar

    2016-01-01

    Full Text Available Deep drawing is a forming process in which a blank of sheet metal is radially drawn into a forming die by the mechanical action of a punch and converted to required shape. Deep drawing involves complex material flow conditions and force distributions. Radial drawing stresses and tangential compressive stresses are induced in flange region due to the material retention property. These compressive stresses result in wrinkling phenomenon in flange region. Normally blank holder is applied for restricting wrinkles. Tensile stresses in radial direction initiate thinning in the wall region of cup. The thinning results into cracking or fracture. The finite element method is widely applied worldwide to simulate the deep drawing process. For real-life simulations of deep drawing process an accurate numerical model, as well as an accurate description of material behavior and contact conditions, is necessary. The finite element method is a powerful tool to predict material thinning deformations before prototypes are made. The proposed innovative methodology combines two techniques for prediction and optimization of thinning in automotive sealing cover. Taguchi design of experiments and analysis of variance has been applied to analyze the influencing process parameters on Thinning. Mathematical relations have been developed to correlate input process parameters and Thinning. Optimization problem has been formulated for thinning and Genetic Algorithm has been applied for optimization. Experimental validation of results proves the applicability of newly proposed approach. The optimized component when manufactured is observed to be safe, no thinning or fracture is observed.

  19. Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

    Science.gov (United States)

    van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

    2014-03-01

    For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

  20. Genetics, recruitment, and migration patterns of Arctic Cisco (Coregonus autumnalis) in the Colville River, Alaska and Mackenzie River, Canada

    Science.gov (United States)

    Zimmerman, Christian E.; Ramey, Andy M.; Turner, S.; Mueter, Franz J.; Murphy, S.; Nielsen, Jennifer L.

    2013-01-01

    Arctic cisco Coregonus autumnalis have a complex anadromous life history, many aspects of which remain poorly understood. Some life history traits of Arctic cisco from the Colville River, Alaska, and Mackenzie River basin, Canada, were investigated using molecular genetics, harvest data, and otolith microchemistry. The Mackenzie hypothesis, which suggests that Arctic cisco found in Alaskan waters originate from the Mackenzie River system, was tested using 11 microsatellite loci and a single mitochondrial DNA gene. No genetic differentiation was found among sample collections from the Colville River and the Mackenzie River system using molecular markers (P > 0.19 in all comparisons). Model-based clustering methods also supported genetic admixture between sample collections from the Colville River and Mackenzie River basin. A reanalysis of recruitment patterns to Alaska, which included data from recent warm periods and suspected changes in atmospheric circulation patterns, still finds that recruitment is correlated to wind conditions. Otolith microchemistry (Sr/Ca ratios) confirmed repeated, annual movements of Arctic cisco between low-salinity habitats in winter and marine waters in summer.

  1. Genetic Pattern and Demographic History of Salminus brasiliensis: Population Expansion in the Pantanal Region during the Pleistocene

    Directory of Open Access Journals (Sweden)

    Lívia A. de Carvalho Mondin

    2018-01-01

    Full Text Available Pleistocene climate changes were major historical events that impacted South American biodiversity. Although the effects of such changes are well-documented for several biomes, it is poorly known how these climate shifts affected the biodiversity of the Pantanal floodplain. Fish are one of the most diverse groups in the Pantanal floodplains and can be taken as a suitable biological model for reconstructing paleoenvironmental scenarios. To identify the effects of Pleistocene climate changes on Pantanal’s ichthyofauna, we used genetic data from multiple populations of a top-predator long-distance migratory fish, Salminus brasiliensis. We specifically investigated whether Pleistocene climate changes affected the demography of this species. If this was the case, we expected to find changes in population size over time. Thus, we assessed the genetic diversity of S. brasiliensis to trace the demographic history of nine populations from the Upper Paraguay basin, which includes the Pantanal floodplain, that form a single genetic group, employing approximate Bayesian computation (ABC to test five scenarios: constant population, old expansion, old decline, old bottleneck following by recent expansion, and old expansion following by recent decline. Based on two mitochondrial DNA markers, our inferences from ABC analysis, the results of Bayesian skyline plot, the implications of star-like networks, and the patterns of genetic diversity (high haplotype diversity and low-to-moderate nucleotide diversity indicated a sudden population expansion. ABC allowed us to make strong quantitative inferences about the demographic history of S. brasiliensis. We estimated a small ancestral population size that underwent a drastic fivefold expansion, probably associated with the colonization of newly formed habitats. The estimated time of this expansion was consistent with a humid and warm phase as inferred by speleothem growth phases and travertine records during

  2. Temporal patterns of genetic variation across a 9-year-old aerial seed bank of the shrub Banksia hookeriana (Proteaceae).

    Science.gov (United States)

    Barrett, Luke G; He, Tianhua; Lamont, Byron B; Krauss, Siegfried L

    2005-11-01

    The pattern of accumulation of genetic variation over time in seed banks is poorly understood. We examined the genetic structure of the aerial seed bank of Banksia hookeriana within a single 15-year-old population in fire-prone southwestern Australia, and compared genetic variation between adults and each year of a 9-year-old seed bank using amplified fragment length polymorphism (AFLP). B. hookeriana is well suited to the study of seed bank dynamics due to the canopy storage of its seeds, and because each annual crop can be identified. A total of 304 seeds from nine crop years and five maternal plants were genotyped, along with 113 plants from the adult population. Genetic variation, as assessed by the proportion of polymorphic markers (P(p)) and Shannon's index (I), increased slightly within the seed bank over time, while gene diversity (H(j)), did not change. P(p), I, and H(j) all indicated that genetic variation within the seed bank quickly approached the maximal level detected. Analysis of molecular variance revealed that less than 4% of variation could be accounted for by variation among seeds produced in different years, whereas there was greater differentiation among maternal plants (12.7%), and among individual seeds produced by different maternal plants (83.4%). With increasing population age, offspring generated each year were slightly more outbred, as indicated by an increase in the mean number of nonmaternal markers per offspring. There were no significant differences for H(j) or I between adults and the seed bank. Viability of seeds decreased with age, such that the viability of 9-year-old seeds was half that of 2-year-old seeds. These results suggest that variable fire frequencies have only limited potential to influence the amount of genetic variation stored within the seed bank of B. hookeriana.

  3. Effectiveness of biological surrogates for predicting patterns of marine biodiversity: a global meta-analysis.

    Directory of Open Access Journals (Sweden)

    Camille Mellin

    Full Text Available The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet, uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales considered. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P and as the predictability of targets using surrogates (R(2. A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and statistical method used all influenced surrogate effectiveness, at least according to either P or R(2. The type of surrogate used (higher-taxa, cross-taxa or subset taxa was the best predictor of P, with the higher-taxa surrogates outperforming all others. The marine habitat was the best predictor of R(2, with particularly low predictability in tropical reefs. Surrogate effectiveness was greatest for higher-taxa surrogates at a <10-km spatial scale, in low-complexity marine habitats such as soft bottoms, and using multivariate-based methods. Comparisons with terrestrial studies in terms of the methods used to study surrogates revealed that marine applications still ignore some problems with several widely used statistical approaches to surrogacy. Our study provides a benchmark for the reliable use of biological surrogates in marine ecosystems, and highlights directions for future development of biological surrogates in predicting biodiversity.

  4. De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

    Science.gov (United States)

    Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N

    2017-11-14

    Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.

  5. Common genetic markers and prediction of recurrent events after ischemic stroke in young adults.

    Science.gov (United States)

    Pezzini, A; Grassi, M; Del Zotto, E; Lodigiani, C; Ferrazzi, P; Spalloni, A; Patella, R; Giossi, A; Volonghi, I; Iacoviello, L; Magoni, M; Rota, L L; Rasura, M; Padovani, A

    2009-09-01

    Scarce information is available on the usefulness of new prediction markers for identifying young ischemic stroke patients at highest risk of recurrence. The predictive effect of traditional risk factors as well as of the 20210A variant of prothrombin gene, the 1691A variant of factor V gene, and the TT677 genotype of the methylenetetrahydrofolate reductase (MTHFR) gene on the risk of recurrence was investigated in a hospital-based cohort study of 511 ischemic stroke patients younger than 45 years followed up for a mean of 43.4 months. Outcome measures were fatal/nonfatal myocardial infarction, ischemic stroke, or TIA. Risk prediction was assessed with the use of the concordance c (c index), and the Net Reclassification Improvement (NRI). The risk of recurrence increased with increasing number of traditional factors (hazard ratio [HR] 2.29, 95% confidence interval [CI] 1.57-3.35 for subjects with 1 factor: HR 5.25, 95% CI 2.45-11.2 for subjects with 2), as well as with that of predisposing genotypes (HR 1.96, 95% CI 1.33-2.89 for subjects carrying 1 at-risk genotype; HR 3.83, 95% CI 1.76-8.34 for those carrying 2). The c statistics increased significantly when the genotypes were included into a model with traditional risk factors (0.696 vs 0.635, test z = 2.41). The NRI was also significant (NRI = 0.172, test z = 2.17). Addition of common genetic variants to traditional risk factors may be an effective method for discriminating young stroke patients at different risk of future ischemic events.

  6. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Science.gov (United States)

    Bertolino, Alessandro; Taurisano, Paolo; Pisciotta, Nicola Marco; Blasi, Giuseppe; Fazio, Leonardo; Romano, Raffaella; Gelao, Barbara; Lo Bianco, Luciana; Lozupone, Madia; Di Giorgio, Annabella; Caforio, Grazia; Sambataro, Fabio; Niccoli-Asabella, Artor; Papp, Audrey; Ursini, Gianluca; Sinibaldi, Lorenzo; Popolizio, Teresa; Sadee, Wolfgang; Rubini, Giuseppe

    2010-02-22

    Variation of the gene coding for D2 receptors (DRD2) has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560) predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic) and D2L (mainly post-synaptic). However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known. Thirty-seven healthy subjects were genotyped for rs1076560 (G>T) and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors) and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors), as well as BOLD fMRI during N-Back working memory. Subjects carrying the T allele (previously associated with reduced D2S expression) had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers) and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT. Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  7. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Directory of Open Access Journals (Sweden)

    Alessandro Bertolino

    2010-02-01

    Full Text Available Variation of the gene coding for D2 receptors (DRD2 has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560 predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic and D2L (mainly post-synaptic. However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known.Thirty-seven healthy subjects were genotyped for rs1076560 (G>T and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors, as well as BOLD fMRI during N-Back working memory.Subjects carrying the T allele (previously associated with reduced D2S expression had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT.Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  8. Predicting recurrent aphthous ulceration using genetic algorithms-optimized neural networks

    Directory of Open Access Journals (Sweden)

    Najla S Dar-Odeh

    2010-05-01

    Full Text Available Najla S Dar-Odeh1, Othman M Alsmadi2, Faris Bakri3, Zaer Abu-Hammour2, Asem A Shehabi3, Mahmoud K Al-Omiri1, Shatha M K Abu-Hammad4, Hamzeh Al-Mashni4, Mohammad B Saeed4, Wael Muqbil4, Osama A Abu-Hammad1 1Faculty of Dentistry, 2Faculty of Engineering and Technology, 3Faculty of Medicine, University of Jordan, Amman, Jordan; 4Dental Department, University of Jordan Hospital, Amman, JordanObjective: To construct and optimize a neural network that is capable of predicting the occurrence of recurrent aphthous ulceration (RAU based on a set of appropriate input data.Participants and methods: Artificial neural networks (ANN software employing genetic algorithms to optimize the architecture neural networks was used. Input and output data of 86 participants (predisposing factors and status of the participants with regards to recurrent aphthous ulceration were used to construct and train the neural networks. The optimized neural networks were then tested using untrained data of a further 10 participants.Results: The optimized neural network, which produced the most accurate predictions for the presence or absence of recurrent aphthous ulceration was found to employ: gender, hematological (with or without ferritin and mycological data of the participants, frequency of tooth brushing, and consumption of vegetables and fruits.Conclusions: Factors appearing to be related to recurrent aphthous ulceration and appropriate for use as input data to construct ANNs that predict recurrent aphthous ulceration were found to include the following: gender, hemoglobin, serum vitamin B12, serum ferritin, red cell folate, salivary candidal colony count, frequency of tooth brushing, and the number of fruits or vegetables consumed daily.Keywords: artifical neural networks, recurrent, aphthous ulceration, ulcer

  9. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

    Science.gov (United States)

    Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M Charlotte

    2016-04-23

    This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features

  10. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

    Directory of Open Access Journals (Sweden)

    Antanas Verikas

    2016-04-01

    Full Text Available This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each. The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG

  11. Georeferenced evaluation of genetic breeding value patterns in Brazilian Holstein cattle.

    Science.gov (United States)

    Costa, N S; Hermuche, P; Cobuci, J A; Paiva, S R; Guimaraes, R F; Carvalho, O A; Gomes, R A T; Costa, C N; McManus, C M

    2014-11-27

    The aim of this study was to analyze the relationship between environmental and genetic values for milk production and type traits in Holstein cattle in Brazil. The genetic value of 65,383 animals for milk production and 53,626 for type classification were available. Socioeconomic and environmental data were obtained from the Brazilian Institute of Geography and Statistics, the Food and Agriculture Organization of the United Nations, the National Aeronautics and Space Administration, and the National Institute of Meteorology. Five to six clusters were generated for each of the groups of type traits and production levels. The relationships between these traits were assessed using the STEPDISC, DISCRIM and CANDISC procedures in SAS(®). Traits within the clusters behaved differently, but, in general, animals with lower genetic values were found in environments that were more stressful for animal production. These differences were mainly associated with temperature, humidity, precipitation and the Normalized Difference Vegetative Index. Genetic values for milk production showed best discrimination between different environments, while type traits showed poor discrimination, possibly because farmers mainly select for milk production. Environmental variations for genetic values in dairy cattle in Brazil should be further examined.

  12. Predictive Pulse Pattern Current Modulation Scheme for Harmonic Reduction in Three-Phase Multidrive Systems

    DEFF Research Database (Denmark)

    Davari, Pooya; Yang, Yongheng; Zare, Firuz

    2016-01-01

    at the rectification stage to synthesize sinusoidal input currents. The input voltage sensing is avoided in order to minimize the number of required sensors, and the grid synchronization also has been implemented based on a common Phase-Locked-Loop (PLL) using the DC-link capacitor voltage ripple. Experimental results......The majority of the industrial motor drive systems are equipped with the conventional line-commutated front-end rectifiers, and being one of the main sources of harmonics in the power line. While a parallel combination of these drive units elevates current quality issues, a proper arrangement...... of them can lead to the cancellation of specific harmonics. This paper proposes a new cost-effective harmonic mitigation solution for multi-drive systems using a predictive pulse pattern current modulation control strategy. The proposed technique applies suitable interaction among parallel drive units...

  13. Model Predictive Control-based gait pattern generation for wearable exoskeletons.

    Science.gov (United States)

    Wang, Letian; van Asseldonk, Edwin H F; van der Kooij, Herman

    2011-01-01

    This paper introduces a new method for controlling wearable exoskeletons that do not need predefined joint trajectories. Instead, it only needs basic gait descriptors such as step length, swing duration, and walking speed. End point Model Predictive Control (MPC) is used to generate the online joint trajectories based on these gait parameters. Real-time ability and control performance of the method during the swing phase of gait cycle is studied in this paper. Experiments are performed by helping a human subject swing his leg with different patterns in the LOPES gait trainer. Results show that the method is able to assist subjects to make steps with different step length and step duration without predefined joint trajectories and is fast enough for real-time implementation. Future study of the method will focus on controlling the exoskeletons in the entire gait cycle. © 2011 IEEE

  14. Prediction of rhythmic and periodic EEG patterns and seizures on continuous EEG with early epileptiform discharges.

    Science.gov (United States)

    Koren, J; Herta, J; Draschtak, S; Pötzl, G; Pirker, S; Fürbass, F; Hartmann, M; Kluge, T; Baumgartner, C

    2015-08-01

    outcome six months after discharge was significantly worse in patients with early epileptiform discharges (p=0.01). Epileptiform discharges within the first 30 min of EEG recording are predictive for the occurrence of ictal EEG patterns and for RPPIIU on subsequent cEEG, for acute convulsive seizures during the ICU stay, and for a worse functional outcome after 6 months of follow-up. This article is part of a Special Issue entitled Status Epilepticus. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Actual building energy use patterns and their implications for predictive modeling

    International Nuclear Information System (INIS)

    Heidarinejad, Mohammad; Cedeño-Laurent, Jose G.; Wentz, Joshua R.; Rekstad, Nicholas M.; Spengler, John D.; Srebric, Jelena

    2017-01-01

    Highlights: • Developed three building categories based on energy use patterns of campus buildings. • Evaluated implication of temporal energy data granularity on predictive modeling. • Demonstrated importance of monitoring daily chilled water consumption. • Identified interval electricity data as an indicator of building operation schedules. • Demonstrated a calibration process for energy modeling of a campus building. - Abstract: The main goal of this study is to understand the patterns in which commercial buildings consume energy, rather than evaluating building energy use based on aggregate utility bills typically linked to building principal tenant activity or occupancy type. The energy consumption patterns define buildings as externally-load, internally-load, or mixed-load dominated buildings. Penn State and Harvard campuses serve as case studies for this particular research project. The buildings in these two campuses use steam, chilled water, and electricity as energy commodities and maintain databases of different resolutions to include minute, hourly, daily, and monthly data instances depending on the commodity and available data acquisition system. The results of this study show monthly steam consumption directly correlates to outdoor environmental conditions for 88% of the studied buildings, while chilled water consumption has negligible correlation to the outdoor environmental conditions. Thus, in terms of monthly chilled water consumption, 86% of buildings are internally-load and mixed-load dominated, respectively. Chilled water consumption is better suited for the daily analyses compared to the monthly and hourly analyses. While the influence of building operation schedules affects the analyses at the hourly level, the monthly chilled water consumptions are not good indicators of the building energy consumption patterns. Electricity consumption at the monthly (or seasonal) level can support the building energy simulation tools for the

  16. Predicting decisions in human social interactions using real-time fMRI and pattern classification.

    Science.gov (United States)

    Hollmann, Maurice; Rieger, Jochem W; Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes

    2011-01-01

    Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

  17. Predicting decisions in human social interactions using real-time fMRI and pattern classification.

    Directory of Open Access Journals (Sweden)

    Maurice Hollmann

    Full Text Available Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

  18. Spatial patterns of diversity and genetic erosion of traditional cassava (Manihot esculenta Crantz) cultivation in the Peruvian Amazon: an evaluation of socio-economic and environmental indicators

    NARCIS (Netherlands)

    Willemen, L.; Scheldeman, X.; Soto Cabellos, V.; Salazar, S.R.; Guarino, L.

    2007-01-01

    This study evaluates quantitatively the suitability of the use of site-specific socio-economic and environmental data as indicators to rapidly assess patterns of diversity and genetic erosion risk in cassava. Socio-economic data as well as farmers¿ estimation of genetic erosion were collected in the

  19. Addition of host genetic variants in a prediction rule for post meningitis hearing loss in childhood: a model updating study.

    Science.gov (United States)

    Sanders, Marieke S; de Jonge, Rogier C J; Terwee, Caroline B; Heymans, Martijn W; Koomen, Irene; Ouburg, Sander; Spanjaard, Lodewijk; Morré, Servaas A; van Furth, A Marceline

    2013-07-23

    Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to severity and outcome of BM. In this study it was determined whether host genetic risk factors improve the predictive abilities of an existing model regarding hearing loss after childhood BM. Four hundred and seventy-one Dutch Caucasian childhood BM were genotyped for 11 single nucleotide polymorphisms (SNPs) in seven different genes involved in pathogen recognition. Genetic data were added to the original clinical prediction model and performance of new models was compared to the original model by likelihood ratio tests and the area under the curve (AUC) of the receiver operating characteristic curves. Addition of TLR9-1237 SNPs and the combination of TLR2 + 2477 and TLR4 + 896 SNPs improved the clinical prediction model, but not significantly (increase of AUC's from 0.856 to 0.861 and from 0.856 to 0.875 (p = 0.570 and 0.335, respectively). Other SNPs analysed were not linked to hearing loss. Although addition of genetic risk factors did not significantly improve the clinical prediction model for post-meningitis hearing loss, AUC's of the pre-existing model remain high after addition of genetic factors. Future studies should evaluate whether more combinations of SNPs in larger cohorts has an additional value to the existing prediction model for post meningitis hearing loss.

  20. Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example

    Directory of Open Access Journals (Sweden)

    Benjamin A Goldstein

    2014-08-01

    Full Text Available Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers. Materials & Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD in the Atherosclerosis Risk in Communities (ARIC cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.Results: The addition of a GRS to a clinical risk score (CRS improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor SNPs are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider. Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

  1. An improved rank based disease prediction using web navigation patterns on bio-medical databases

    Directory of Open Access Journals (Sweden)

    P. Dhanalakshmi

    2017-12-01

    Full Text Available Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the document ranking models on biomedical database are sensitive to sparsity and outliers. In this paper, a novel user recommendation system was implemented to predict the top ranked biomedical documents using the disease type, gene entities and user navigation patterns. In this recommendation system, dynamic session identification, dynamic user identification and document ranking techniques were used to extract the highly relevant disease documents on the online PubMed repository. To verify the performance of the proposed model, the true positive rate and runtime of the model was compared with that of traditional static models such as Bayesian and Fuzzy rank. Experimental results show that the performance of the proposed ranking model is better than the traditional models.

  2. The preoperative manometric pattern predicts the outcome of surgical treatment for esophageal achalasia.

    Science.gov (United States)

    Salvador, Renato; Costantini, Mario; Zaninotto, Giovanni; Morbin, Tiziana; Rizzetto, Christian; Zanatta, Lisa; Ceolin, Martina; Finotti, Elena; Nicoletti, Loredana; Da Dalt, Gianfranco; Cavallin, Francesco; Ancona, Ermanno

    2010-11-01

    A new manometric classification of esophageal achalasia has recently been proposed that also suggests a correlation with the final outcome of treatment. The aim of this study was to investigate this hypothesis in a large group of achalasia patients undergoing laparoscopic Heller-Dor myotomy. We evaluated 246 consecutive achalasia patients who underwent surgery as their first treatment from 2001 to 2009. Patients with sigmoid-shaped esophagus were excluded. Symptoms were scored and barium swallow X-ray, endoscopy, and esophageal manometry were performed before and again at 6 months after surgery. Patients were divided into three groups: (I) no distal esophageal pressurization (contraction wave amplitude 30 mmHg); and (III) rapidly propagating pressurization attributable to spastic contractions. Treatment failure was defined as a postoperative symptom score greater than the 10th percentile of the preoperative score (i.e., >7). Type III achalasia coincided with a longer overall lower esophageal sphincter (LES) length, a lower symptom score, and a smaller esophageal diameter. Treatment failure rates differed significantly in the three groups: I = 14.6% (14/96), II = 4.7% (6/127), and III = 30.4% (7/23; p = 0.0007). At univariate analysis, the manometric pattern, a low LES resting pressure, and a high chest pain score were the only factors predicting treatment failure. At multivariate analysis, the manometric pattern and a LES resting pressure achalasia subtypes: patients with panesophageal pressurization have the best outcome after laparoscopic Heller-Dor myotomy.

  3. PREDICTION OF BLOOD PATTERN IN S-SHAPED MODEL OF ARTERY UNDER NORMAL BLOOD PRESSURE

    Directory of Open Access Journals (Sweden)

    Mohd Azrul Hisham Mohd Adib

    2013-06-01

    Full Text Available Athletes are susceptible to a wide variety of traumatic and non-traumatic vascular injuries to the lower limb. This paper aims to predict the three-dimensional flow pattern of blood through an S-shaped geometrical artery model. This model has created by using Fluid Structure Interaction (FSI software. The modeling of the geometrical S-shaped artery is suitable for understanding the pattern of blood flow under constant normal blood pressure. In this study, a numerical method is used that works on the assumption that the blood is incompressible and Newtonian; thus, a laminar type of flow can be considered. The authors have compared the results with a previous study with FSI validation simulation. The validation and verification of the simulation studies is performed by comparing the maximum velocity at t = 0.4 s, because at this time, the blood accelerates rapidly. In addition, the resulting blood flow at various times, under the same boundary conditions in the S-shaped geometrical artery model, is presented. The graph shows that velocity increases linearly with time. Thus, it can be concluded that the flow of blood increases with respect to the pressure inside the body.

  4. A comparative analysis of primary and secondary Gleason pattern predictive ability for positive surgical margins after radical prostatectomy.

    Science.gov (United States)

    Sfoungaristos, S; Kavouras, A; Kanatas, P; Polimeros, N; Perimenis, P

    2011-01-01

    To compare the predictive ability of primary and secondary Gleason pattern for positive surgical margins in patients with clinically localized prostate cancer and a preoperative Gleason score ≤ 6. A retrospective analysis of the medical records of patients undergone a radical prostatectomy between January 2005 and October 2010 was conducted. Patients' age, prostate volume, preoperative PSA, biopsy Gleason score, the 1st and 2nd Gleason pattern were entered a univariate and multivariate analysis. The 1st and 2nd pattern were tested for their ability to predict positive surgical margins using receiver operating characteristic curves. Positive surgical margins were noticed in 56 cases (38.1%) out of 147 studied patients. The 2nd pattern was significantly greater in those with positive surgical margins while the 1st pattern was not significantly different between the 2 groups of patients. ROC analysis revealed that area under the curve was 0.53 (p=0.538) for the 1st pattern and 0.60 (p=0.048) for the 2nd pattern. Concerning the cases with PSA <10 ng/ml, it was also found that only the 2nd pattern had a predictive ability (p=0.050). When multiple logistic regression analysis was conducted it was found that the 2nd pattern was the only independent predictor. The second Gleason pattern was found to be of higher value than the 1st one for the prediction of positive surgical margins in patients with preoperative Gleason score ≤ 6 and this should be considered especially when a neurovascular bundle sparing radical prostatectomy is planned, in order not to harm the oncological outcome.

  5. The RadGenomics project. Prediction for radio-susceptibility of individuals with genetic predisposition

    International Nuclear Information System (INIS)

    Imai, Takashi

    2003-01-01

    The ultimate goal of our project, named RadGenomics, is to elucidate the heterogeneity of the response to ionizing radiation arising from genetic variation among individuals, for the purpose of developing personalized radiation therapy regimens for cancer patients. Cancer patients exhibit patient-to-patient variability in normal tissue reactions after radiotherapy. Several observations support the hypothesis that the radiosensitivity of normal tissue is influenced by genetic factors. The rapid progression of human genome sequencing and the recent development of new technologies in molecular biology are providing new opportunities for elucidating the genetic basis of individual differences in susceptibility to radiation exposure. The development of a sufficiently robust, predictive assay enabling individual dose adjustment would improve the outcome of radiation therapy in patients. Our strategy for identification of DNA polymorphisms that contribute to the individual radiosensitivity is as follows. First, we have been categorizing DNA samples obtained from cancer patients, who have been kindly introduced to us through many collaborators, according to their clinical characteristics including the method and effect of treatment and side effects as scored by toxicity criteria, and also the result of an in vitro radiosensitivity assay, e.g., the micronuclei assay of their lymphocytes. Second, we have identified candidate genes for genotyping mainly by using our custom-designed oligonucleotide array with RNA samples, in which the probes were obtained from more than 40 cancer and 3 fibroblast cell lines whose radiosensitivity level was quite heterogeneous. We have also been studying the modification of proteins after irradiation of cells which may be caused by mainly phosphorylation or dephosphorylation, using mass spectrometry. Genes encoding the modified proteins and/or other proteins with which they interact such as specific protein kinases and phosphatases are also

  6. A genetic risk score combining ten psoriasis risk loci improves disease prediction.

    Directory of Open Access Journals (Sweden)

    Haoyan Chen

    2011-04-01

    Full Text Available Psoriasis is a chronic, immune-mediated skin disease affecting 2-3% of Caucasians. Recent genetic association studies have identified multiple psoriasis risk loci; however, most of these loci contribute only modestly to disease risk. In this study, we investigated whether a genetic risk score (GRS combining multiple loci could improve psoriasis prediction. Two approaches were used: a simple risk alleles count (cGRS and a weighted (wGRS approach. Ten psoriasis risk SNPs were genotyped in 2815 case-control samples and 858 family samples. We found that the total number of risk alleles in the cases was significantly higher than in controls, mean 13.16 (SD 1.7 versus 12.09 (SD 1.8, p = 4.577×10(-40. The wGRS captured considerably more risk than any SNP considered alone, with a psoriasis OR for high-low wGRS quartiles of 10.55 (95% CI 7.63-14.57, p = 2.010×10(-65. To compare the discriminatory ability of the GRS models, receiver operating characteristic curves were used to calculate the area under the curve (AUC. The AUC for wGRS was significantly greater than for cGRS (72.0% versus 66.5%, p = 2.13×10(-8. Additionally, the AUC for HLA-C alone (rs10484554 was equivalent to the AUC for all nine other risk loci combined (66.2% versus 63.8%, p = 0.18, highlighting the dominance of HLA-C as a risk locus. Logistic regression revealed that the wGRS was significantly associated with two subphenotypes of psoriasis, age of onset (p = 4.91×10(-6 and family history (p = 0.020. Using a liability threshold model, we estimated that the 10 risk loci account for only 11.6% of the genetic variance in psoriasis. In summary, we found that a GRS combining 10 psoriasis risk loci captured significantly more risk than any individual SNP and was associated with early onset of disease and a positive family history. Notably, only a small fraction of psoriasis heritability is captured by the common risk variants identified to date.

  7. Predicting the severity of nuclear power plant transients using nearest neighbors modeling optimized by genetic algorithms on a parallel computer

    International Nuclear Information System (INIS)

    Lin, J.; Bartal, Y.; Uhrig, R.E.

    1995-01-01

    The importance of automatic diagnostic systems for nuclear power plants (NPPs) has been discussed in numerous studies, and various such systems have been proposed. None of those systems were designed to predict the severity of the diagnosed scenario. A classification and severity prediction system for NPP transients is developed. The system is based on nearest neighbors modeling, which is optimized using genetic algorithms. The optimization process is used to determine the most important variables for each of the transient types analyzed. An enhanced version of the genetic algorithms is used in which a local downhill search is performed to further increase the accuracy achieved. The genetic algorithms search was implemented on a massively parallel supercomputer, the KSR1-64, to perform the analysis in a reasonable time. The data for this study were supplied by the high-fidelity simulator of the San Onofre unit 1 pressurized water reactor

  8. Understanding invasion history and predicting invasive niches using genetic sequencing technology in Australia: case studies from Cucurbitaceae and Boraginaceae.

    Science.gov (United States)

    Shaik, Razia S; Zhu, Xiaocheng; Clements, David R; Weston, Leslie A

    2016-01-01

    Part of the challenge in dealing with invasive plant species is that they seldom represent a uniform, static entity. Often, an accurate understanding of the history of plant introduction and knowledge of the real levels of genetic diversity present in species and populations of importance is lacking. Currently, the role of genetic diversity in promoting the successful establishment of invasive plants is not well defined. Genetic profiling of invasive plants should enhance our understanding of the dynamics of colonization in the invaded range. Recent advances in DNA sequencing technology have greatly facilitated the rapid and complete assessment of plant population genetics. Here, we apply our current understanding of the genetics and ecophysiology of plant invasions to recent work on Australian plant invaders from the Cucurbitaceae and Boraginaceae. The Cucurbitaceae study showed that both prickly paddy melon ( Cucumis myriocarpus ) and camel melon ( Citrullus lanatus ) were represented by only a single genotype in Australia, implying that each was probably introduced as a single introduction event. In contrast, a third invasive melon, Citrullus colocynthis , possessed a moderate level of genetic diversity in Australia and was potentially introduced to the continent at least twice. The Boraginaceae study demonstrated the value of comparing two similar congeneric species; one, Echium plantagineum , is highly invasive and genetically diverse, whereas the other, Echium vulgare , exhibits less genetic diversity and occupies a more limited ecological niche. Sequence analysis provided precise identification of invasive plant species, as well as information on genetic diversity and phylogeographic history. Improved sequencing technologies will continue to allow greater resolution of genetic relationships among invasive plant populations, thereby potentially improving our ability to predict the impact of these relationships upon future spread and better manage invaders

  9. Feasibility of an Assessment Tool for Children's Competence to Consent to Predictive Genetic Testing: a Pilot Study

    NARCIS (Netherlands)

    Hein, Irma M.; Troost, Pieter W.; Lindeboom, Robert; Christiaans, Imke; Grisso, Thomas; van Goudoever, Johannes B.; Lindauer, Ramón J. L.

    2015-01-01

    Knowledge on children's capacities to consent to medical treatment is limited. Also, age limits for asking children's consent vary considerably between countries. Decision-making on predictive genetic testing (PGT) is especially complicated, considering the ongoing ethical debate. In order to

  10. Addition of host genetic variants in a prediction rule for post meningitis hearing loss in childhood: a model updating study

    NARCIS (Netherlands)

    Sanders, Marieke S.; de Jonge, Rogier C. J.; Terwee, Caroline B.; Heymans, Martijn W.; Koomen, Irene; Ouburg, Sander; Spanjaard, Lodewijk; Morré, Servaas A.; van Furth, A. Marceline

    2013-01-01

    Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to

  11. The common sense model of self-regulation and psychological adjustment to predictive genetic testing: a prospective study

    NARCIS (Netherlands)

    van Oostrom, Iris; Meijers-Heijboer, Hanne; Duivenvoorden, Hugo J.; Bröcker-Vriends, Annette H. J. T.; van Asperen, Christi J.; Sijmons, Rolf H.; Seynaeve, Caroline; van Gool, Arthur R.; Klijn, Jan G. M.; Tibben, Aad

    2007-01-01

    This prospective study explored the contribution of illness representations and coping to cancer-related distress in unaffected individuals undergoing predictive genetic testing for an identified mutation in BRCA1/2 (BReast CAncer) or an HNPCC (Hereditary Nonpolyposis Colorectal Cancer)-related

  12. The common sense model of self-regulation and psychological adjustment to predictive genetic testing: a prospective study.

    NARCIS (Netherlands)

    Oostrom, I.I.H. van; Meijers-Heijboer, H.; Duivenvoorden, H.J.; Brocker-Vriends, A.H.; Asperen, C.J. van; Sijmons, R.H.; Seynaeve, C.; Gool, A.R. van; Klijn, J.G.M.; Tibben, A.

    2007-01-01

    This prospective study explored the contribution of illness representations and coping to cancer-related distress in unaffected individuals undergoing predictive genetic testing for an identified mutation in BRCA1/2 (BReast CAncer) or an HNPCC (Hereditary Nonpolyposis Colorectal Cancer)-related

  13. The common sense model of self-regulation and psychological adjustment to predictive genetic testing : a prospective study

    NARCIS (Netherlands)

    van Oostrom, Iris; Meijers-Heijboer, Hanne; Duivenvoorden, Hugo J.; Broecker-Vriends, Annette H. J. T.; van Asperen, Christi J.; Sijmons, Rolf H.; Seynaeve, Caroline; Van Gool, Arthur R.; Klijn, Jan G. M.; Tibben, Aad

    2007-01-01

    This prospective study explored the contribution of illness representations and coping to cancer-related distress in unaffected individuals undergoing predictive genetic testing for an identified mutation in BRCA1/2 (BReast CAncer) or an HNPCC (Hereditary Nonpolyposis Colorectal Cancer)-related

  14. HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

    Science.gov (United States)

    Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

    2017-01-15

    Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodologies is that a single imaging pattern can distinguish between healthy and diseased populations, or between two subgroups of patients (e.g., progressors vs. non-progressors). This assumption effectively ignores the ample evidence for the heterogeneous nature of brain diseases. Neurodegenerative, neuropsychiatric and neurodevelopmental disorders are largely characterized by high clinical heterogeneity, which likely stems in part from underlying neuroanatomical heterogeneity of various pathologies. Detecting and characterizing heterogeneity may deepen our understanding of disease mechanisms and lead to patient-specific treatments. However, few approaches tackle disease subtype discovery in a principled machine learning framework. To address this challenge, we present a novel non-linear learning algorithm for simultaneous binary classification and subtype identification, termed HYDRA (Heterogeneity through Discriminative Analysis). Neuroanatomical subtypes are effectively captured by multiple linear hyperplanes, which form a convex polytope that separates two groups (e.g., healthy controls from pathologic samples); each face of this polytope effectively defines a disease subtype. We validated HYDRA on simulated and clinical data. In the latter case, we applied the proposed method independently to the imaging and genetic datasets of the Alzheimer's Disease Neuroimaging Initiative (ADNI 1) study. The imaging dataset consisted of T1-weighted volumetric magnetic resonance images of 123 AD patients and 177 controls. The genetic dataset consisted of single nucleotide polymorphism information of 103 AD patients and 139 controls. We identified 3 reproducible subtypes of atrophy in AD relative to controls: (1) diffuse and extensive

  15. Genetics

    International Nuclear Information System (INIS)

    Hubitschek, H.E.

    1975-01-01

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