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Sample records for histories accurately predict

  1. Highly Accurate Prediction of Jobs Runtime Classes

    OpenAIRE

    Anat Reiner-Benaim; Anna Grabarnick; Edi Shmueli

    2016-01-01

    Separating the short jobs from the long is a known technique to improve scheduling performance. In this paper we describe a method we developed for accurately predicting the runtimes classes of the jobs to enable this separation. Our method uses the fact that the runtimes can be represented as a mixture of overlapping Gaussian distributions, in order to train a CART classifier to provide the prediction. The threshold that separates the short jobs from the long jobs is determined during the ev...

  2. Accurate predictions for the LHC made easy

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    The data recorded by the LHC experiments is of a very high quality. To get the most out of the data, precise theory predictions, including uncertainty estimates, are needed to reduce as much as possible theoretical bias in the experimental analyses. Recently, significant progress has been made in computing Next-to-Leading Order (NLO) computations, including matching to the parton shower, that allow for these accurate, hadron-level predictions. I shall discuss one of these efforts, the MadGraph5_aMC@NLO program, that aims at the complete automation of predictions at the NLO accuracy within the SM as well as New Physics theories. I’ll illustrate some of the theoretical ideas behind this program, show some selected applications to LHC physics, as well as describe the future plans.

  3. Medication errors: the importance of an accurate drug history

    National Research Council Canada - National Science Library

    FitzGerald, Richard J

    2009-01-01

    .... Apart from preventing prescription errors, accurate medication histories are also useful in detecting drug-related pathology or changes in clinical signs that may be the result of drug therapy...

  4. Climate Models have Accurately Predicted Global Warming

    Science.gov (United States)

    Nuccitelli, D. A.

    2016-12-01

    Climate model projections of global temperature changes over the past five decades have proven remarkably accurate, and yet the myth that climate models are inaccurate or unreliable has formed the basis of many arguments denying anthropogenic global warming and the risks it poses to the climate system. Here we compare average global temperature predictions made by both mainstream climate scientists using climate models, and by contrarians using less physically-based methods. We also explore the basis of the myth by examining specific arguments against climate model accuracy and their common characteristics of science denial.

  5. Customised birthweight standards accurately predict perinatal morbidity.

    Science.gov (United States)

    Figueras, Francesc; Figueras, Josep; Meler, Eva; Eixarch, Elisenda; Coll, Oriol; Gratacos, Eduard; Gardosi, Jason; Carbonell, Xavier

    2007-07-01

    Fetal growth restriction is associated with adverse perinatal outcome but is often not recognised antenatally, and low birthweight centiles based on population norms are used as a proxy instead. This study compared the association between neonatal morbidity and fetal growth status at birth as determined by customised birthweight centiles and currently used centiles based on population standards. Retrospective cohort study. Referral hospital, Barcelona, Spain. A cohort of 13 661 non-malformed singleton deliveries. Both population-based and customised standards for birth weight were applied to the study cohort. Customised weight centiles were calculated by adjusting for maternal height, booking weight, parity, ethnic origin, gestational age at delivery and fetal sex. Newborn morbidity and perinatal death. The association between smallness for gestational age (SGA) and perinatal morbidity was stronger when birthweight limits were customised, and resulted in an additional 4.1% (n=565) neonates being classified as SGA. Compared with non-SGA neonates, this newly identified group had an increased risk of perinatal mortality (OR 3.2; 95% CI 1.6 to 6.2), neurological morbidity (OR 3.2; 95% CI 1.7 to 6.1) and non-neurological morbidity (OR 8; 95% CI 4.8 to 13.6). Customised standards improve the prediction of adverse neonatal outcome. The association between SGA and adverse outcome is independent of the gestational age at delivery.

  6. DOMAC: an accurate, hybrid protein domain prediction server

    OpenAIRE

    Cheng, Jianlin

    2007-01-01

    Protein domain prediction is important for protein structure prediction, structure determination, function annotation, mutagenesis analysis and protein engineering. Here we describe an accurate protein domain prediction server (DOMAC) combining both template-based and ab initio methods. The preliminary version of the server was ranked among the top domain prediction servers in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7), 2006. DOMAC server...

  7. Adaptive through-thickness integration for accurate springback prediction

    NARCIS (Netherlands)

    Burchitz, I.A.; Meinders, Vincent T.

    2007-01-01

    Accurate numerical prediction of springback in sheet metal forming is essential for the automotive industry. Numerous factors influence the accuracy of prediction of this complex phenomenon by using the finite element method. One of them is the numerical integration through the thickness of shell

  8. Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.

    Directory of Open Access Journals (Sweden)

    Oscar Westesson

    Full Text Available The Multiple Sequence Alignment (MSA is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history, it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.

  9. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  10. Accurate identification of fear facial expressions predicts prosocial behavior.

    Science.gov (United States)

    Marsh, Abigail A; Kozak, Megan N; Ambady, Nalini

    2007-05-01

    The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants' ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale.

  11. Hybrid Predictive Models for Accurate Forecasting in PV Systems

    Directory of Open Access Journals (Sweden)

    Marco Mussetta

    2013-04-01

    Full Text Available The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced hybrid evolutionary techniques of computational intelligence applied to photovoltaic systems forecasting, analyzing the predictions obtained by comparing different definitions of the forecasting error.

  12. Plant diversity accurately predicts insect diversity in two tropical landscapes.

    Science.gov (United States)

    Zhang, Kai; Lin, Siliang; Ji, Yinqiu; Yang, Chenxue; Wang, Xiaoyang; Yang, Chunyan; Wang, Hesheng; Jiang, Haisheng; Harrison, Rhett D; Yu, Douglas W

    2016-09-01

    Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity. © 2016 John Wiley & Sons Ltd.

  13. Dementia risk prediction in the population: are screening models accurate?

    Science.gov (United States)

    Stephan, Blossom C M; Kurth, Tobias; Matthews, Fiona E; Brayne, Carol; Dufouil, Carole

    2010-06-01

    Early identification of individuals at risk of dementia will become crucial when effective preventative strategies for this condition are developed. Various dementia prediction models have been proposed, including clinic-based criteria for mild cognitive impairment, and more-broadly constructed algorithms, which synthesize information from known dementia risk factors, such as poor cognition and health. Knowledge of the predictive accuracy of such models will be important if they are to be used in daily clinical practice or to screen the entire older population (individuals aged >or=65 years). This article presents an overview of recent progress in the development of dementia prediction models for use in population screening. In total, 25 articles relating to dementia risk screening met our inclusion criteria for review. Our evaluation of the predictive accuracy of each model shows that most are poor at discriminating at-risk individuals from not-at-risk cases. The best models incorporate diverse sources of information across multiple risk factors. Typically, poor accuracy is associated with single-factor models, long follow-up intervals and the outcome measure of all-cause dementia. A parsimonious and cost-effective consensus model needs to be developed that accurately identifies individuals with a high risk of future dementia.

  14. A new, accurate predictive model for incident hypertension.

    Science.gov (United States)

    Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K

    2013-11-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures. The primary study population consisted of 1605 normotensive individuals aged 20-79 years with 5-year follow-up from the population-based study, that is the Study of Health in Pomerania (SHIP). The initial set was randomly split into a training and a testing set. We used a probabilistic graphical model applying a Bayesian network to create a predictive model for incident hypertension and compared the predictive performance with the established Framingham risk score for hypertension. Finally, the model was validated in 2887 participants from INTER99, a Danish community-based intervention study. In the training set of SHIP data, the Bayesian network used a small subset of relevant baseline features including age, mean arterial pressure, rs16998073, serum glucose and urinary albumin concentrations. Furthermore, we detected relevant interactions between age and serum glucose as well as between rs16998073 and urinary albumin concentrations [area under the receiver operating characteristic (AUC 0.76)]. The model was confirmed in the SHIP validation set (AUC 0.78) and externally replicated in INTER99 (AUC 0.77). Compared to the established Framingham risk score for hypertension, the predictive performance of the new model was similar in the SHIP validation set and moderately better in INTER99. Data mining procedures identified a predictive model for incident hypertension, which included innovative and easy-to-measure variables. The findings promise great applicability in screening settings and clinical practice.

  15. Accurate prediction of peptide binding sites on protein surfaces.

    Directory of Open Access Journals (Sweden)

    Evangelia Petsalaki

    2009-03-01

    Full Text Available Many important protein-protein interactions are mediated by the binding of a short peptide stretch in one protein to a large globular segment in another. Recent efforts have provided hundreds of examples of new peptides binding to proteins for which a three-dimensional structure is available (either known experimentally or readily modeled but where no structure of the protein-peptide complex is known. To address this gap, we present an approach that can accurately predict peptide binding sites on protein surfaces. For peptides known to bind a particular protein, the method predicts binding sites with great accuracy, and the specificity of the approach means that it can also be used to predict whether or not a putative or predicted peptide partner will bind. We used known protein-peptide complexes to derive preferences, in the form of spatial position specific scoring matrices, which describe the binding-site environment in globular proteins for each type of amino acid in bound peptides. We then scan the surface of a putative binding protein for sites for each of the amino acids present in a peptide partner and search for combinations of high-scoring amino acid sites that satisfy constraints deduced from the peptide sequence. The method performed well in a benchmark and largely agreed with experimental data mapping binding sites for several recently discovered interactions mediated by peptides, including RG-rich proteins with SMN domains, Epstein-Barr virus LMP1 with TRADD domains, DBC1 with Sir2, and the Ago hook with Argonaute PIWI domain. The method, and associated statistics, is an excellent tool for predicting and studying binding sites for newly discovered peptides mediating critical events in biology.

  16. WGS accurately predicts antimicrobial resistance in Escherichia coli.

    Science.gov (United States)

    Tyson, Gregory H; McDermott, Patrick F; Li, Cong; Chen, Yuansha; Tadesse, Daniel A; Mukherjee, Sampa; Bodeis-Jones, Sonya; Kabera, Claudine; Gaines, Stuart A; Loneragan, Guy H; Edrington, Tom S; Torrence, Mary; Harhay, Dayna M; Zhao, Shaohua

    2015-10-01

    The objective of this study was to determine the effectiveness of WGS in identifying resistance genotypes of MDR Escherichia coli and whether these correlate with observed phenotypes. Seventy-six E. coli strains were isolated from farm cattle and measured for phenotypic resistance to 15 antimicrobials with the Sensititre(®) system. Isolates with resistance to at least four antimicrobials in three classes were selected for WGS using an Illumina MiSeq. Genotypic analysis was conducted with in-house Perl scripts using BLAST analysis to identify known genes and mutations associated with clinical resistance. Over 30 resistance genes and a number of resistance mutations were identified among the E. coli isolates. Resistance genotypes correlated with 97.8% specificity and 99.6% sensitivity to the identified phenotypes. The majority of discordant results were attributable to the aminoglycoside streptomycin, whereas there was a perfect genotype-phenotype correlation for most antibiotic classes such as tetracyclines, quinolones and phenicols. WGS also revealed information about rare resistance mechanisms, such as structural mutations in chromosomal copies of ampC conferring third-generation cephalosporin resistance. WGS can provide comprehensive resistance genotypes and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance. Moreover, the data presented here showing the ability to accurately predict resistance suggest that WGS may be used as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  17. Accurate Holdup Calculations with Predictive Modeling & Data Integration

    Energy Technology Data Exchange (ETDEWEB)

    Azmy, Yousry [North Carolina State Univ., Raleigh, NC (United States). Dept. of Nuclear Engineering; Cacuci, Dan [Univ. of South Carolina, Columbia, SC (United States). Dept. of Mechanical Engineering

    2017-04-03

    In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use

  18. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    Directory of Open Access Journals (Sweden)

    Cecilia Noecker

    2015-03-01

    Full Text Available Upon infection of a new host, human immunodeficiency virus (HIV replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV. First, we found that the mode of virus production by infected cells (budding vs. bursting has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral

  19. Artificial neural network accurately predicts hepatitis B surface antigen seroclearance.

    Directory of Open Access Journals (Sweden)

    Ming-Hua Zheng

    Full Text Available BACKGROUND & AIMS: Hepatitis B surface antigen (HBsAg seroclearance and seroconversion are regarded as favorable outcomes of chronic hepatitis B (CHB. This study aimed to develop artificial neural networks (ANNs that could accurately predict HBsAg seroclearance or seroconversion on the basis of available serum variables. METHODS: Data from 203 untreated, HBeAg-negative CHB patients with spontaneous HBsAg seroclearance (63 with HBsAg seroconversion, and 203 age- and sex-matched HBeAg-negative controls were analyzed. ANNs and logistic regression models (LRMs were built and tested according to HBsAg seroclearance and seroconversion. Predictive accuracy was assessed with area under the receiver operating characteristic curve (AUROC. RESULTS: Serum quantitative HBsAg (qHBsAg and HBV DNA levels, qHBsAg and HBV DNA reduction were related to HBsAg seroclearance (P<0.001 and were used for ANN/LRM-HBsAg seroclearance building, whereas, qHBsAg reduction was not associated with ANN-HBsAg seroconversion (P = 0.197 and LRM-HBsAg seroconversion was solely based on qHBsAg (P = 0.01. For HBsAg seroclearance, AUROCs of ANN were 0.96, 0.93 and 0.95 for the training, testing and genotype B subgroups respectively. They were significantly higher than those of LRM, qHBsAg and HBV DNA (all P<0.05. Although the performance of ANN-HBsAg seroconversion (AUROC 0.757 was inferior to that for HBsAg seroclearance, it tended to be better than those of LRM, qHBsAg and HBV DNA. CONCLUSIONS: ANN identifies spontaneous HBsAg seroclearance in HBeAg-negative CHB patients with better accuracy, on the basis of easily available serum data. More useful predictors for HBsAg seroconversion are still needed to be explored in the future.

  20. Fast and accurate predictions of covalent bonds in chemical space.

    Science.gov (United States)

    Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

    2016-05-07

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  1. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

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    Xin Deng

    2015-07-01

    Full Text Available Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

  2. Towards more accurate and reliable predictions for nuclear applications

    Directory of Open Access Journals (Sweden)

    Goriely Stephane

    2017-01-01

    Full Text Available The need for nuclear data far from the valley of stability, for applications such as nuclear astrophysics or future nuclear facilities, challenges the robustness as well as the predictive power of present nuclear models. Most of the nuclear data evaluation and prediction are still performed on the basis of phenomenological nuclear models. For the last decades, important progress has been achieved in fundamental nuclear physics, making it now feasible to use more reliable, but also more complex microscopic or semi-microscopic models in the evaluation and prediction of nuclear data for practical applications. Nowadays mean-field models can be tuned at the same level of accuracy as the phenomenological models, renormalized on experimental data if needed, and therefore can replace the phenomenological inputs in the evaluation of nuclear data. The latest achievements to determine nuclear masses within the non-relativistic HFB approach, including the related uncertainties in the model predictions, are discussed. Similarly, recent efforts to determine fission observables within the mean-field approach are described and compared with more traditional existing models.

  3. Accurate Theoretical Predictions of the Properties of Energetic Materials

    Science.gov (United States)

    2008-09-18

    and to investigate the relationships between crystal structure/microstructure and sensitivity, compressibility, polymorphism and crystal shape...Additionally, these procedures and potentials can be used to investigate/predict polymorphism and crystal habits. Sensitivity, the ease with...point group symmetries in which the molecule is coincident with appropriate unit cell symmetry. β- HMX , for example, has Ci point group symmetry and

  4. Learning regulatory programs that accurately predict differential expression with MEDUSA.

    Science.gov (United States)

    Kundaje, Anshul; Lianoglou, Steve; Li, Xuejing; Quigley, David; Arias, Marta; Wiggins, Chris H; Zhang, Li; Leslie, Christina

    2007-12-01

    Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology. In this paper, we describe a predictive modeling approach for studying regulatory networks, based on a machine learning algorithm called MEDUSA. MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes. Instead of using clustering or correlation of expression profiles to infer regulatory relationships, MEDUSA determines condition-specific regulators and discovers regulatory motifs that mediate the regulation of target genes. In this way, MEDUSA meaningfully models biological mechanisms of transcriptional regulation. MEDUSA solves the problem of predicting the differential (up/down) expression of target genes by using boosting, a technique from statistical learning, which helps to avoid overfitting as the algorithm searches through the high-dimensional space of potential regulators and sequence motifs. Experimental results demonstrate that MEDUSA achieves high prediction accuracy on held-out experiments (test data), that is, data not seen in training. We also present context-specific analysis of MEDUSA regulatory programs for DNA damage and hypoxia, demonstrating that MEDUSA identifies key regulators and motifs in these processes. A central challenge in the field is the difficulty of validating reverse-engineered networks in the absence of a gold standard. Our approach of learning regulatory programs provides at least a partial solution for the problem: MEDUSA's prediction accuracy on held-out data gives a concrete and statistically sound way to validate how well the algorithm performs. With MEDUSA, statistical validation becomes a prerequisite for hypothesis generation and network building rather than a secondary consideration.

  5. Third trimester ultrasound soft-tissue measurements accurately predicts macrosomia.

    Science.gov (United States)

    Maruotti, Giuseppe Maria; Saccone, Gabriele; Martinelli, Pasquale

    2017-04-01

    To evaluate the accuracy of sonographic measurements of fetal soft tissue in the prediction of macrosomia. Electronic databases were searched from their inception until September 2015 with no limit for language. We included only studies assessing the accuracy of sonographic measurements of fetal soft tissue in the abdomen or thigh in the prediction of macrosomia  ≥34 weeks of gestation. The primary outcome was the accuracy of sonographic measurements of fetal soft tissue in the prediction of macrosomia. We generated the forest plot for the pooled sensitivity and specificity with 95% confidence interval (CI). Additionally, summary receiver-operating characteristics (ROC) curves were plotted and the area under the curve (AUC) was also computed to evaluate the overall performance of the diagnostic test accuracy. Three studies, including 287 singleton gestations, were analyzed. The pooled sensitivity of sonographic measurements of abdominal or thigh fetal soft tissue in the prediction of macrosomia was 80% (95% CI: 66-89%) and the pooled specificity was 95% (95% CI: 91-97%). The AUC for diagnostic accuracy of sonographic measurements of fetal soft tissue in the prediction of macrosomia was 0.92 and suggested high diagnostic accuracy. Third-trimester sonographic measurements of fetal soft tissue after 34 weeks may help to detect macrosomia with a high degree of accuracy. The pooled detection rate was 80%. A standardization of measurements criteria, reproducibility, building reference charts of fetal subcutaneous tissue and large studies to assess the optimal cutoff of fetal adipose thickness are necessary before the introduction of fetal soft-tissue markers in the clinical practice.

  6. Accurate prediction of inducible transcription factor binding intensities in vivo.

    Directory of Open Access Journals (Sweden)

    Michael J Guertin

    Full Text Available DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB-seq, that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF, which inducibly binds a target DNA sequence element (HSE following heat shock stress. PB-seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF-bound and HSF-free DNA, and then detecting HSF-bound DNA by high-throughput sequencing. We compared PB-seq binding profiles with ones observed in vivo by ChIP-seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase-seq data and the ChIP-chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF, tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity.

  7. PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations.

    Directory of Open Access Journals (Sweden)

    Jaroslav Bendl

    2014-01-01

    Full Text Available Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.

  8. Copeptin does not accurately predict disease severity in imported malaria

    Directory of Open Access Journals (Sweden)

    van Wolfswinkel Marlies E

    2012-01-01

    Full Text Available Abstract Background Copeptin has recently been identified to be a stable surrogate marker for the unstable hormone arginine vasopressin (AVP. Copeptin has been shown to correlate with disease severity in leptospirosis and bacterial sepsis. Hyponatraemia is common in severe imported malaria and dysregulation of AVP release has been hypothesized as an underlying pathophysiological mechanism. The aim of the present study was to evaluate the performance of copeptin as a predictor of disease severity in imported malaria. Methods Copeptin was measured in stored serum samples of 204 patients with imported malaria that were admitted to our Institute for Tropical Diseases in Rotterdam in the period 1999-2010. The occurrence of WHO defined severe malaria was the primary end-point. The diagnostic performance of copeptin was compared to that of previously evaluated biomarkers C-reactive protein, procalcitonin, lactate and sodium. Results Of the 204 patients (141 Plasmodium falciparum, 63 non-falciparum infection, 25 had severe malaria. The Area Under the ROC curve of copeptin for severe disease (0.66 [95% confidence interval 0.59-0.72] was comparable to that of lactate, sodium and procalcitonin. C-reactive protein (0.84 [95% CI 0.79-0.89] had a significantly better performance as a biomarker for severe malaria than the other biomarkers. Conclusions C-reactive protein but not copeptin was found to be an accurate predictor for disease severity in imported malaria. The applicability of copeptin as a marker for severe malaria in clinical practice is limited to exclusion of severe malaria.

  9. Predicting life-history adaptations to pollutants

    Energy Technology Data Exchange (ETDEWEB)

    Maltby, L. [Univ. of Sheffield (United Kingdom). Dept. of Animal and Plant Sciences

    1995-12-31

    Animals may adapt to pollutant stress so that individuals from polluted environments are less susceptible than those from unpolluted environments. In addition to such direct adaptations, animals may respond to pollutant stress by life-history modifications; so-called indirect adaptations. This paper will demonstrate how, by combining life-history theory and toxicological data, it is possible to predict stress-induced alterations in reproductive output and offspring size. Pollutant-induced alterations in age-specific survival in favor of adults and reductions in juvenile growth, conditions are predicted to select for reduced investment in reproduction and the allocation of this investment into fewer, larger offspring. Field observations on the freshwater crustaceans, Asellus aquaticus and Gammarus pulex, support these predictions. Females from metal-polluted sites had lower investment in reproduction and produced larger offspring than females of the same species from unpolluted sites. Moreover, interpopulation differences in reproductive biology persisted in laboratory cultures indicating that they had a genetic basis and were therefore due to adaptation rather than acclimation. The general applicability of this approach will be considered.

  10. Predicting accurate absolute binding energies in aqueous solution

    DEFF Research Database (Denmark)

    Jensen, Jan Halborg

    2015-01-01

    Recent predictions of absolute binding free energies of host-guest complexes in aqueous solution using electronic structure theory have been encouraging for some systems, while other systems remain problematic. In this paper I summarize some of the many factors that could easily contribute 1-3 kcal......-represented by continuum models. While I focus on binding free energies in aqueous solution the approach also applies (with minor adjustments) to any free energy difference such as conformational or reaction free energy differences or activation free energies in any solvent....... mol(-1) errors at 298 K: three-body dispersion effects, molecular symmetry, anharmonicity, spurious imaginary frequencies, insufficient conformational sampling, wrong or changing ionization states, errors in the solvation free energy of ions, and explicit solvent (and ion) effects that are not well...

  11. Accurate prediction of secondary metabolite gene clusters in filamentous fungi

    DEFF Research Database (Denmark)

    Andersen, Mikael Rørdam; Nielsen, Jakob Blæsbjerg; Klitgaard, Andreas

    2013-01-01

    -chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have...... used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.......Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify...

  12. Generating highly accurate prediction hypotheses through collaborative ensemble learning

    Science.gov (United States)

    Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

    2017-03-01

    Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.

  13. Robust High-Resolution Cloth Using Parallelism, History-Based Collisions and Accurate Friction

    Science.gov (United States)

    Selle, Andrew; Su, Jonathan; Irving, Geoffrey; Fedkiw, Ronald

    2015-01-01

    In this paper we simulate high resolution cloth consisting of up to 2 million triangles which allows us to achieve highly detailed folds and wrinkles. Since the level of detail is also influenced by object collision and self collision, we propose a more accurate model for cloth-object friction. We also propose a robust history-based repulsion/collision framework where repulsions are treated accurately and efficiently on a per time step basis. Distributed memory parallelism is used for both time evolution and collisions and we specifically address Gauss-Seidel ordering of repulsion/collision response. This algorithm is demonstrated by several high-resolution and high-fidelity simulations. PMID:19147895

  14. Change in BMI accurately predicted by social exposure to acquaintances.

    Science.gov (United States)

    Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (pchange in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.

  15. Change in BMI accurately predicted by social exposure to acquaintances.

    Directory of Open Access Journals (Sweden)

    Rahman O Oloritun

    Full Text Available Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC and R(2. This study found a model that explains 68% (p<0.0001 of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as

  16. Biomarker Surrogates Do Not Accurately Predict Sputum Eosinophils and Neutrophils in Asthma

    Science.gov (United States)

    Hastie, Annette T.; Moore, Wendy C.; Li, Huashi; Rector, Brian M.; Ortega, Victor E.; Pascual, Rodolfo M.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

    2013-01-01

    Background Sputum eosinophils (Eos) are a strong predictor of airway inflammation, exacerbations, and aid asthma management, whereas sputum neutrophils (Neu) indicate a different severe asthma phenotype, potentially less responsive to TH2-targeted therapy. Variables such as blood Eos, total IgE, fractional exhaled nitric oxide (FeNO) or FEV1% predicted, may predict airway Eos, while age, FEV1%predicted, or blood Neu may predict sputum Neu. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway Eos and Neu, individually or combined, is not established. Objectives To determine whether blood Eos, FeNO, and IgE accurately predict sputum eosinophils, and age, FEV1% predicted, and blood Neu accurately predict sputum neutrophils (Neu). Methods Subjects in the Wake Forest Severe Asthma Research Program (N=328) were characterized by blood and sputum cells, healthcare utilization, lung function, FeNO, and IgE. Multiple analytical techniques were utilized. Results Despite significant association with sputum Eos, blood Eos, FeNO and total IgE did not accurately predict sputum Eos, and combinations of these variables failed to improve prediction. Age, FEV1%predicted and blood Neu were similarly unsatisfactory for prediction of sputum Neu. Factor analysis and stepwise selection found FeNO, IgE and FEV1% predicted, but not blood Eos, correctly predicted 69% of sputum Eospredicted 64% of sputum Neupredict both sputum Eos and Neu accurately assigned only 41% of samples. Conclusion Despite statistically significant associations FeNO, IgE, blood Eos and Neu, FEV1%predicted, and age are poor surrogates, separately and combined, for accurately predicting sputum eosinophils and neutrophils. PMID:23706399

  17. Accurate Prediction of Motor Failures by Application of Multi CBM Tools: A Case Study

    Science.gov (United States)

    Dutta, Rana; Singh, Veerendra Pratap; Dwivedi, Jai Prakash

    2018-02-01

    Motor failures are very difficult to predict accurately with a single condition-monitoring tool as both electrical and the mechanical systems are closely related. Electrical problem, like phase unbalance, stator winding insulation failures can, at times, lead to vibration problem and at the same time mechanical failures like bearing failure, leads to rotor eccentricity. In this case study of a 550 kW blower motor it has been shown that a rotor bar crack was detected by current signature analysis and vibration monitoring confirmed the same. In later months in a similar motor vibration monitoring predicted bearing failure and current signature analysis confirmed the same. In both the cases, after dismantling the motor, the predictions were found to be accurate. In this paper we will be discussing the accurate predictions of motor failures through use of multi condition monitoring tools with two case studies.

  18. Heart rate during basketball game play and volleyball drills accurately predicts oxygen uptake and energy expenditure.

    Science.gov (United States)

    Scribbans, T D; Berg, K; Narazaki, K; Janssen, I; Gurd, B J

    2015-09-01

    There is currently little information regarding the ability of metabolic prediction equations to accurately predict oxygen uptake and exercise intensity from heart rate (HR) during intermittent sport. The purpose of the present study was to develop and, cross-validate equations appropriate for accurately predicting oxygen cost (VO2) and energy expenditure from HR during intermittent sport participation. Eleven healthy adult males (19.9±1.1yrs) were recruited to establish the relationship between %VO2peak and %HRmax during low-intensity steady state endurance (END), moderate-intensity interval (MOD) and high intensity-interval exercise (HI), as performed on a cycle ergometer. Three equations (END, MOD, and HI) for predicting %VO2peak based on %HRmax were developed. HR and VO2 were directly measured during basketball games (6 male, 20.8±1.0 yrs; 6 female, 20.0±1.3yrs) and volleyball drills (12 female; 20.8±1.0yrs). Comparisons were made between measured and predicted VO2 and energy expenditure using the 3 equations developed and 2 previously published equations. The END and MOD equations accurately predicted VO2 and energy expenditure, while the HI equation underestimated, and the previously published equations systematically overestimated VO2 and energy expenditure. Intermittent sport VO2 and energy expenditure can be accurately predicted from heart rate data using either the END (%VO2peak=%HRmax x 1.008-17.17) or MOD (%VO2peak=%HRmax x 1.2-32) equations. These 2 simple equations provide an accessible and cost-effective method for accurate estimation of exercise intensity and energy expenditure during intermittent sport.

  19. Accurate and dynamic predictive model for better prediction in medicine and healthcare.

    Science.gov (United States)

    Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

    2017-07-29

    Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

  20. Accurate Prediction of Contact Numbers for Multi-Spanning Helical Membrane Proteins

    Science.gov (United States)

    Li, Bian; Mendenhall, Jeffrey; Nguyen, Elizabeth Dong; Weiner, Brian E.; Fischer, Axel W.; Meiler, Jens

    2017-01-01

    Prediction of the three-dimensional (3D) structures of proteins by computational methods is acknowledged as an unsolved problem. Accurate prediction of important structural characteristics such as contact number is expected to accelerate the otherwise slow progress being made in the prediction of 3D structure of proteins. Here, we present a dropout neural network-based method, TMH-Expo, for predicting the contact number of transmembrane helix (TMH) residues from sequence. Neuronal dropout is a strategy where certain neurons of the network are excluded from back-propagation to prevent co-adaptation of hidden-layer neurons. By using neuronal dropout, overfitting was significantly reduced and performance was noticeably improved. For multi-spanning helical membrane proteins, TMH-Expo achieved a remarkable Pearson correlation coefficient of 0.69 between predicted and experimental values and a mean absolute error of only 1.68. In addition, among those membrane protein–membrane protein interface residues, 76.8% were correctly predicted. Mapping of predicted contact numbers onto structures indicates that contact numbers predicted by TMH-Expo reflect the exposure patterns of TMHs and reveal membrane protein–membrane protein interfaces, reinforcing the potential of predicted contact numbers to be used as restraints for 3D structure prediction and protein–protein docking. TMH-Expo can be accessed via a Web server at www.meilerlab.org. PMID:26804342

  1. Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins.

    Science.gov (United States)

    Yang, Jing; He, Bao-Ji; Jang, Richard; Zhang, Yang; Shen, Hong-Bin

    2015-12-01

    Cysteine-rich proteins cover many important families in nature but there are currently no methods specifically designed for modeling the structure of these proteins. The accuracy of disulfide connectivity pattern prediction, particularly for the proteins of higher-order connections, e.g., >3 bonds, is too low to effectively assist structure assembly simulations. We propose a new hierarchical order reduction protocol called Cyscon for disulfide-bonding prediction. The most confident disulfide bonds are first identified and bonding prediction is then focused on the remaining cysteine residues based on SVR training. Compared with purely machine learning-based approaches, Cyscon improved the average accuracy of connectivity pattern prediction by 21.9%. For proteins with more than 5 disulfide bonds, Cyscon improved the accuracy by 585% on the benchmark set of PDBCYS. When applied to 158 non-redundant cysteine-rich proteins, Cyscon predictions helped increase (or decrease) the TM-score (or RMSD) of the ab initio QUARK modeling by 12.1% (or 14.4%). This result demonstrates a new avenue to improve the ab initio structure modeling for cysteine-rich proteins. http://www.csbio.sjtu.edu.cn/bioinf/Cyscon/ zhng@umich.edu or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. An effective method for accurate prediction of the first hyperpolarizability of alkalides.

    Science.gov (United States)

    Wang, Jia-Nan; Xu, Hong-Liang; Sun, Shi-Ling; Gao, Ting; Li, Hong-Zhi; Li, Hui; Su, Zhong-Min

    2012-01-15

    The proper theoretical calculation method for nonlinear optical (NLO) properties is a key factor to design the excellent NLO materials. Yet it is a difficult task to obatin the accurate NLO property of large scale molecule. In present work, an effective intelligent computing method, as called extreme learning machine-neural network (ELM-NN), is proposed to predict accurately the first hyperpolarizability (β(0)) of alkalides from low-accuracy first hyperpolarizability. Compared with neural network (NN) and genetic algorithm neural network (GANN), the root-mean-square deviations of the predicted values obtained by ELM-NN, GANN, and NN with their MP2 counterpart are 0.02, 0.08, and 0.17 a.u., respectively. It suggests that the predicted values obtained by ELM-NN are more accurate than those calculated by NN and GANN methods. Another excellent point of ELM-NN is the ability to obtain the high accuracy level calculated values with less computing cost. Experimental results show that the computing time of MP2 is 2.4-4 times of the computing time of ELM-NN. Thus, the proposed method is a potentially powerful tool in computational chemistry, and it may predict β(0) of the large scale molecules, which is difficult to obtain by high-accuracy theoretical method due to dramatic increasing computational cost. Copyright © 2011 Wiley Periodicals, Inc.

  3. ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

    Science.gov (United States)

    Ntaios, G; Gioulekas, F; Papavasileiou, V; Strbian, D; Michel, P

    2016-11-01

    ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P DRAGON score estimates (P DRAGON score estimates (P DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. © 2016 EAN.

  4. An accurate model for predicting high frequency noise of nanoscale NMOS SOI transistors

    Science.gov (United States)

    Shen, Yanfei; Cui, Jie; Mohammadi, Saeed

    2017-05-01

    A nonlinear and scalable model suitable for predicting high frequency noise of N-type Metal Oxide Semiconductor (NMOS) transistors is presented. The model is developed for a commercial 45 nm CMOS SOI technology and its accuracy is validated through comparison with measured performance of a microwave low noise amplifier. The model employs the virtual source nonlinear core and adds parasitic elements to accurately simulate the RF behavior of multi-finger NMOS transistors up to 40 GHz. For the first time, the traditional long-channel thermal noise model is supplemented with an injection noise model to accurately represent the noise behavior of these short-channel transistors up to 26 GHz. The developed model is simple and easy to extract, yet very accurate.

  5. PlantLoc: an accurate web server for predicting plant protein subcellular localization by substantiality motif

    OpenAIRE

    Tang, Shengnan; Li, Tonghua; Cong, Peisheng; Xiong, Wenwei; Wang, Zhiheng; Sun, Jiangming

    2013-01-01

    Knowledge of subcellular localizations (SCLs) of plant proteins relates to their functions and aids in understanding the regulation of biological processes at the cellular level. We present PlantLoc, a highly accurate and fast webserver for predicting the multi-label SCLs of plant proteins. The PlantLoc server has two innovative characters: building localization motif libraries by a recursive method without alignment and Gene Ontology information; and establishing simple architecture for rapi...

  6. LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

    DEFF Research Database (Denmark)

    Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.

    2012-01-01

    Current genomic screens for noncoding RNAs (ncRNAs) predict a large number of genomic regions containing potential structural ncRNAs. The analysis of these data requires highly accurate prediction of ncRNA boundaries and discrimination of promising candidate ncRNAs from weak predictions. Existing...... methods struggle with these goals because they rely on sequence-based multiple sequence alignments, which regularly misalign RNA structure and therefore do not support identification of structural similarities. To overcome this limitation, we compute columnwise and global reliabilities of alignments based...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely used nc...

  7. Rapid yet accurate first principle based predictions of alkali halide crystal phases using alchemical perturbation

    CERN Document Server

    Solovyeva, Alisa

    2016-01-01

    We assess the predictive power of alchemical perturbations for estimating fundamental properties in ionic crystals. Using density functional theory we have calculated formation energies, lattice constants, and bulk moduli for all sixteen iso-valence-electronic combinations of pure pristine alkali halides involving elements $A \\in \\{$Na, K, Rb, Cs$\\}$ and $X \\in \\{$F, Cl, Br, I$\\}$. For rock salt, zincblende and cesium chloride symmetry, alchemical Hellmann-Feynman derivatives, evaluated along lattice scans of sixteen reference crystals, have been obtained for all respective 16$\\times$15 combinations of reference and predicted target crystals. Mean absolute errors (MAE) are on par with density functional theory level of accuracy for energies and bulk modulus. Predicted lattice constants are less accurate. NaCl is the best reference salt for alchemical estimates of relative energies (MAE $<$ 40 meV/atom) while alkali fluorides are the worst. By contrast, lattice constants are predicted best using NaF as a re...

  8. Predicting life history parameters for all fishes worldwide.

    Science.gov (United States)

    Thorson, James T; Munch, Stephan B; Cope, Jason M; Gao, Jin

    2017-12-01

    Scientists and resource managers need to know life history parameters (e.g., average mortality rate, individual growth rate, maximum length or mass, and timing of maturity) to understand and respond to risks to natural populations and ecosystems. For over 100 years, scientists have identified "life history invariants" (LHI) representing pairs of parameters whose ratio is theorized to be constant across species. LHI then promise to allow prediction of many parameters from field measurements of a few important traits. Using LHI in this way, however, neglects any residual patterns in parameters when making predictions. We therefore apply a multivariate model for eight variables (seven parameters and temperature) in over 32,000 fishes, and include taxonomic structure for residuals (with levels for class, order, family, genus, and species). We illustrate that this approach predicts variables probabilistically for taxa with many or few data. We then use this model to resolve three questions regarding life history parameters in fishes. Specifically we show that (1) on average there is a 1.24% decrease in the Brody growth coefficient for every 1% increase in maximum size; (2) the ratio of natural mortality rate and growth coefficient is not an LHI but instead varies systematically based on the timing of maturation, where movement along this life history axis is predictably correlated with species taxonomy; and (3) three variables must be known per species to precisely predict remaining life history variables. We distribute our predictive model as an R package, FishLife, to allow future life history predictions for fishes to be conditioned on taxonomy and life history data for fishes worldwide. This package also contains predictions (and predictive intervals) for mortality, maturity, size, and growth parameters for all described fishes. © 2017 by the Ecological Society of America.

  9. Can phenological models predict tree phenology accurately under climate change conditions?

    Science.gov (United States)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  10. Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

    Science.gov (United States)

    Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

    2017-04-01

    Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

  11. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Directory of Open Access Journals (Sweden)

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  12. The HOMR-Now! Model Accurately Predicts 1-Year Death Risk for Hospitalized Patients on Admission.

    Science.gov (United States)

    van Walraven, Carl; Forster, Alan J

    2017-08-01

    The Hospital-patient One-year Mortality Risk (HOMR) score is an externally validated index using health administrative data to accurately predict the risk of death within 1 year of admission to the hospital. This study derived and internally validated a HOMR modification using data that are available when the patient is admitted to the hospital. From all adult hospitalizations at our tertiary-care teaching hospital between 2004 and 2015, we randomly selected one per patient. We added to all HOMR variables that could be determined from our hospital's data systems on admission other factors that might prognosticate. Vital statistics registries determined vital status at 1 year from admission. Of 2,06,396 patients, 32,112 (15.6%) died within 1 year of admission to the hospital. The HOMR-now! model included patient (sex, comorbidities, living and cancer clinic status, and 1-year death risk from population-based life tables) and hospitalization factors (admission year, urgency, service and laboratory-based acuity score). The model explained that more than half of the total variability (Regenkirke's R(2) value of 0.53) was very discriminative (C-statistic 0.92), and accurately predicted death risk (calibration slope 0.98). One-year risk of death can be accurately predicted using routinely collected data available when patients are admitted to the hospital. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

    Directory of Open Access Journals (Sweden)

    Chen Ke

    2008-05-01

    Full Text Available Abstract Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is

  14. Adult Spinal Deformity Surgeons Are Unable to Accurately Predict Postoperative Spinal Alignment Using Clinical Judgment Alone.

    Science.gov (United States)

    Ailon, Tamir; Scheer, Justin K; Lafage, Virginie; Schwab, Frank J; Klineberg, Eric; Sciubba, Daniel M; Protopsaltis, Themistocles S; Zebala, Lukas; Hostin, Richard; Obeid, Ibrahim; Koski, Tyler; Kelly, Michael P; Bess, Shay; Shaffrey, Christopher I; Smith, Justin S; Ames, Christopher P

    2016-07-01

    Adult spinal deformity (ASD) surgery seeks to reduce disability and improve quality of life through restoration of spinal alignment. In particular, correction of sagittal malalignment is correlated with patient outcome. Inadequate correction of sagittal deformity is not infrequent. The present study assessed surgeons' ability to accurately predict postoperative alignment. Seventeen cases were presented with preoperative radiographic measurements, and a summary of the operation as performed by the treating physician. Surgeon training, practice characteristics, and use of surgical planning software was assessed. Participants predicted if the surgical plan would lead to adequate deformity correction and attempted to predict postoperative radiographic parameters including sagittal vertical axis (SVA), pelvic tilt (PT), pelvic incidence to lumbar lordosis mismatch (PI-LL), thoracic kyphosis (TK). Seventeen surgeons participated: 71% within 0 to 10 years of practice; 88% devote >25% of their practice to deformity surgery. Surgeons accurately judged adequacy of the surgical plan to achieve correction to specific thresholds of SVA 69% ± 8%, PT 68% ± 9%, and PI-LL 68% ± 11% of the time. However, surgeons correctly predicted the actual postoperative radiographic parameters only 42% ± 6% of the time. They were more successful at predicting PT (61% ± 10%) than SVA (45% ± 8%), PI-LL (26% ± 11%), or TK change (35% ± 21%; p deformity but not number of years in practice or number of three-column osteotomies performed per year. Surgeons failed to correctly predict the adequacy of the proposed surgical plan in approximately one third of presented cases. They were better at determining whether a surgical plan would achieve adequate correction than predicting specific postoperative alignment parameters. Pelvic tilt and SVA were predicted with the greatest accuracy. Copyright © 2016 Scoliosis Research Society. Published by Elsevier Inc. All rights reserved.

  15. Can Triage Nurses Accurately Predict Patient Dispositions in the Emergency Department?

    Science.gov (United States)

    Alexander, Danette; Abbott, Lincoln; Zhou, Qiuping; Staff, Ilene

    2016-11-01

    Contemporary emergency departments experience crowded conditions with poor patient outcomes. If triage nurses could accurately predict admission, one theoretical intervention to reduce crowding is to place patients in the admission cue on arrival to the emergency department. The purpose of this study was to determine if triage nurses could accurately predict patient dispositions. This prospective study was conducted in a tertiary academic hospital's emergency department using a data collection tool embedded in the ED electronic information system. Study variables included the predicted and actual disposition, as well as level of care, gender, age, and Emergency Severity Index level. Data were collected for 28 consecutive days from September 17 through October 9, 2013. Sensitivity and specificity, positive and negative predictive values, and accuracy of prediction, as well as the associations between patient characteristics and nurse prediction, were calculated. A total of 5,135 cases were included in the analysis. The triage nurses predicted admissions with a sensitivity of 71.5% and discharges with a specificity of 88.0%. Accuracy was significantly higher for younger patients and for patients at very low or very high severity levels. Although the ability to predict admissions at triage by nurses was not adequate to support a change in the bed procurement process, a specificity of 88.0% could have implications for rapid ED discharges or other low-acuity processes designed within the emergency department. Further studies in additional settings and on alternative interventions are needed. Copyright © 2016 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.

  16. Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

    Science.gov (United States)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2016-10-01

    The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.

  17. Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation

    Science.gov (United States)

    Vašát, Radim; Kodešová, Radka; Borůvka, Luboš

    2017-07-01

    A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.

  18. Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb.

    Directory of Open Access Journals (Sweden)

    Remo Monti

    2017-08-01

    Full Text Available Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb-Enhancer Genie (LEG, a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface. We predict limb enhancers using a combination of >50 published limb-specific datasets and clusters of evolutionarily conserved transcription factor binding sites, taking advantage of the patterns observed at previously in vivo validated elements. By combining different statistical models, our approach outperforms current state-of-the-art methods and provides interpretable measures of feature importance. Our results indicate that including a previously unappreciated score that quantifies tissue-specific nuclease accessibility significantly improves prediction performance. We demonstrate the utility of our approach through in vivo validation of newly predicted elements. Moreover, we describe general features that can guide the type of datasets to include when predicting tissue-specific enhancers genome-wide, while providing an accessible resource to the general biological community and facilitating the functional interpretation of genetic studies of limb malformations.

  19. Psychometric assessment of human life history predicts health related behaviors

    Directory of Open Access Journals (Sweden)

    Daniel J. Kruger

    2016-04-01

    Full Text Available Life History Theory is a powerful framework that can help promote understanding of variation in health-related behavioral patterns and why they vary consistent with environmental conditions. An organism's life history reflects tradeoffs made in the allocation of effort towards specific aspects of survival and reproduction across the lifespan. This study examines the relationship between psychological indicators of life history strategy and health related behaviors in a demographically representative sample in the Midwestern USA. Slower life histories predicted higher levels of health promoting behaviors and lower levels of health adverse behaviors, even when controlling for relevant socio-demographic factors. The analyses provide a strong test of the hypothesized relationship between life history and health behavior indicators, as life history variation co-varies with these socio-demographic factors. Traditional public health efforts may be reaching their limits of effectiveness in encouraging health-promoting behaviors. Integrating an evolutionary framework may revitalize behavioral health promotion efforts.

  20. More accurate recombination prediction in HIV-1 using a robust decoding algorithm for HMMs

    Directory of Open Access Journals (Sweden)

    Brown Daniel G

    2011-05-01

    Full Text Available Abstract Background Identifying recombinations in HIV is important for studying the epidemiology of the virus and aids in the design of potential vaccines and treatments. The previous widely-used tool for this task uses the Viterbi algorithm in a hidden Markov model to model recombinant sequences. Results We apply a new decoding algorithm for this HMM that improves prediction accuracy. Exactly locating breakpoints is usually impossible, since different subtypes are highly conserved in some sequence regions. Our algorithm identifies these sites up to a certain error tolerance. Our new algorithm is more accurate in predicting the location of recombination breakpoints. Our implementation of the algorithm is available at http://www.cs.uwaterloo.ca/~jmtruszk/jphmm_balls.tar.gz. Conclusions By explicitly accounting for uncertainty in breakpoint positions, our algorithm offers more reliable predictions of recombination breakpoints in HIV-1. We also document a new domain of use for our new decoding approach in HMMs.

  1. DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning.

    Science.gov (United States)

    Angermueller, Christof; Lee, Heather J; Reik, Wolf; Stegle, Oliver

    2017-04-11

    Recent technological advances have enabled DNA methylation to be assayed at single-cell resolution. However, current protocols are limited by incomplete CpG coverage and hence methods to predict missing methylation states are critical to enable genome-wide analyses. We report DeepCpG, a computational approach based on deep neural networks to predict methylation states in single cells. We evaluate DeepCpG on single-cell methylation data from five cell types generated using alternative sequencing protocols. DeepCpG yields substantially more accurate predictions than previous methods. Additionally, we show that the model parameters can be interpreted, thereby providing insights into how sequence composition affects methylation variability.

  2. Prediction of Accurate Thermochemistry of Medium and Large Sized Radicals Using Connectivity-Based Hierarchy (CBH).

    Science.gov (United States)

    Sengupta, Arkajyoti; Raghavachari, Krishnan

    2014-10-14

    Accurate modeling of the chemical reactions in many diverse areas such as combustion, photochemistry, or atmospheric chemistry strongly depends on the availability of thermochemical information of the radicals involved. However, accurate thermochemical investigations of radical systems using state of the art composite methods have mostly been restricted to the study of hydrocarbon radicals of modest size. In an alternative approach, systematic error-canceling thermochemical hierarchy of reaction schemes can be applied to yield accurate results for such systems. In this work, we have extended our connectivity-based hierarchy (CBH) method to the investigation of radical systems. We have calibrated our method using a test set of 30 medium sized radicals to evaluate their heats of formation. The CBH-rad30 test set contains radicals containing diverse functional groups as well as cyclic systems. We demonstrate that the sophisticated error-canceling isoatomic scheme (CBH-2) with modest levels of theory is adequate to provide heats of formation accurate to ∼1.5 kcal/mol. Finally, we predict heats of formation of 19 other large and medium sized radicals for which the accuracy of available heats of formation are less well-known.

  3. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space.

    Science.gov (United States)

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O Anatole; Müller, Klaus-Robert; Tkatchenko, Alexandre

    2015-06-18

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  4. A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

    Energy Technology Data Exchange (ETDEWEB)

    Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.; Arkin, Adam P.

    2004-12-01

    We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

  5. Accurate prediction of emission energies with TD-DFT methods for platinum and iridium OLED materials.

    Science.gov (United States)

    Morello, Glenn R

    2017-06-01

    Accurate prediction of triplet excitation energies for transition metal complexes has proven to be a difficult task when confronted with a variety of metal centers and ligand types. Specifically, phosphorescent transition metal light emitters, typically based on iridium or platinum, often give calculated results of varying accuracy when compared to experimentally determined T1 emission values. Developing a computational protocol for reliably calculating OLED emission energies will allow for the prediction of a complex's color prior to synthesis, saving time and resources in the laboratory. A comprehensive investigation into the dependence of the DFT functional, basis set, and solvent model is presented here, with the aim of identifying an accurate method while remaining computationally cost-effective. A protocol that uses TD-DFT excitation energies on ground-state geometries was used to predict triplet emission values of 34 experimentally characterized complexes, using a combination of gas phase B3LYP/LANL2dz for optimization and B3LYP/CEP-31G/PCM(THF) for excitation energies. Results show excellent correlation with experimental emission values of iridium and platinum complexes for a wide range of emission energies. The set of complexes tested includes neutral and charged complexes, as well as a variety of different ligand types.

  6. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    Science.gov (United States)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  7. The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum

    Energy Technology Data Exchange (ETDEWEB)

    Jorgensen, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-02

    Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

  8. Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

    Science.gov (United States)

    Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

  9. SIFTER search: a web server for accurate phylogeny-based protein function prediction.

    Science.gov (United States)

    Sahraeian, Sayed M; Luo, Kevin R; Brenner, Steven E

    2015-07-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

    Science.gov (United States)

    Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

    2015-05-01

    Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

  11. Partin Tables cannot accurately predict the pathological stage at radical prostatectomy.

    Science.gov (United States)

    Bhojani, N; Ahyai, S; Graefen, M; Capitanio, U; Suardi, N; Shariat, S F; Jeldres, C; Erbersdobler, A; Schlomm, T; Haese, A; Steuber, T; Heinzer, H; Montorsi, F; Huland, H; Karakiewicz, P I

    2009-02-01

    The Partin Tables represent the most commonly used staging tool for radical prostatectomy (RP) candidates. The Partin Tables' predictions are used to guide the type (nerve preserving RP) and/or the extent (RP with wide resection) of RP. We examined the ability of the Partin Tables' predictions incorrectly assigning the stage at RP. The testing of the Partin Tables (external validation) was based on 3105 patients treated with RP at a single European institution. Standard validation metrics were used (area under the receiver operating characteristics curve, AUC) to test the three endpoints predicted by the Partin Tables, namely the presence of extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph node invasion (LNI). Ideal predictions are denoted with 100% accuracy vs. 50% for entirely random predictions. For the 2001 version of the Tables the accuracy defined by the AUC was 79.7, 77.8, and 73.0 for ECE, SVI, and LNI, respectively. For the 2007 version of the Tables the corresponding accuracy estimates were 79.8, 80.5, and 76.2. The relationship between predicted probabilities and observed rates was poor. The Partin Tables are meant to guide clinicians about the safety of nerve bundle preservation at RP, about the need for seminal vesicle resection or for lymphadenectomy. Therefore, the use of the Partin Tables predictions may significantly affect the type and/or the extent of RP. In their present format the Partin Tables are not accurate enough to influence the pre-operative decision making regarding the type or extent of RP.

  12. Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer.

    Science.gov (United States)

    Turnbull, Arran K; Arthur, Laura M; Renshaw, Lorna; Larionov, Alexey A; Kay, Charlene; Dunbier, Anita K; Thomas, Jeremy S; Dowsett, Mitch; Sims, Andrew H; Dixon, J Michael

    2015-07-10

    Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor-alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer -specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs. © 2015 by American Society of Clinical Oncology.

  13. Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models

    Directory of Open Access Journals (Sweden)

    Aeriel Belk

    2018-02-01

    Full Text Available Death investigations often include an effort to establish the postmortem interval (PMI in cases in which the time of death is uncertain. The postmortem interval can lead to the identification of the deceased and the validation of witness statements and suspect alibis. Recent research has demonstrated that microbes provide an accurate clock that starts at death and relies on ecological change in the microbial communities that normally inhabit a body and its surrounding environment. Here, we explore how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head, gene markers (16S ribosomal RNA (rRNA, 18S rRNA, internal transcribed spacer regions (ITS, and taxonomic levels (sequence variants, species, genus, etc.. We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using gravesoil and skin data using the 16S rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.

  14. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

    Science.gov (United States)

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

    2017-01-09

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

    Science.gov (United States)

    Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2016-05-01

    At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

  16. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

    Science.gov (United States)

    Li, Zhen; Zhang, Renyu

    2017-01-01

    Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact

  17. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

    Science.gov (United States)

    Wang, Sheng; Sun, Siqi; Li, Zhen; Zhang, Renyu; Xu, Jinbo

    2017-01-01

    Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have

  18. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

    Directory of Open Access Journals (Sweden)

    Sheng Wang

    2017-01-01

    Full Text Available Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction.This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question.Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6 for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact

  19. Prediction of blunt traumatic injuries and hospital admission based on history and physical exam.

    Science.gov (United States)

    Beal, Alan L; Ahrendt, Mark N; Irwin, Eric D; Lyng, John W; Turner, Steven V; Beal, Christopher A; Byrnes, Matthew T; Beilman, Greg A

    2016-01-01

    We evaluated the ability of experienced trauma surgeons to accurately predict specific blunt injuries, as well as patient disposition from the emergency department (ED), based only on the initial clinical evaluation and prior to any imaging studies. It would be hypothesized that experienced trauma surgeons' initial clinical evaluation is accurate for excluding life-threatening blunt injuries and for appropriate admission triage decisions. Using only their history and physical exam, and prior to any imaging studies, three (3) experienced trauma surgeons, with a combined Level 1 trauma experience of over 50 years, predicted injuries in patients with an initial GCS (Glasgow Coma Score) of 14-15. Additionally, ED disposition (ICU, floor, discharge to home) was also predicted. These predictions were compared to actual patient dispositions and to blunt injuries documented at discharge. A total of 101 patients with 92 blunt injuries were studied. 43/92 (46.7 %) injuries would have been missed by only performing an initial history and physical exam ("Missed injury"). A change in treatment, though often minor, was required in 19/43 (44.2 %) of the missed injuries. Only 1/43 (2.3 %) of these "missed injuries" (blunt aortic injury) required surgery. Sensitivity, specificity, and accuracy for injury prediction were 53.2, 95.9, and 92.3 % respectively. Positive and negative predictive values were 53.8 and 95.8 % respectively. Prediction of disposition from the ED was 77.8 % accurate. In 7/34 (20.6 %) patients, missed injuries led to changes in disposition. "Undertriage" occurred in 9/99 (9.1 %) patients (Predicted for floor but admitted to ICU). Additionally, 8/84 (9.5 %) patients predicted for floor admission were sent home from the ED; and 5/13 (38.5 %) patients predicted for ICU admission were actually sent to the floor after complete evaluations, giving an "overtriage" rate of 13/99 (13.1 %) patients. In a neurologically-intact group of trauma patients

  20. OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement.

    Science.gov (United States)

    Battenberg, Kai; Lee, Ernest K; Chiu, Joanna C; Berry, Alison M; Potter, Daniel

    2017-06-21

    Identifying orthologous genes is an initial step required for phylogenetics, and it is also a common strategy employed in functional genetics to find candidates for functionally equivalent genes across multiple species. At the same time, in silico orthology prediction tools often require large computational resources only available on computing clusters. Here we present OrthoReD, an open-source orthology prediction tool with accuracy comparable to published tools that requires only a desktop computer. The low computational resource requirement of OrthoReD is achieved by repeating orthology searches on one gene of interest at a time, thereby generating a reduced dataset to limit the scope of orthology search for each gene of interest. The output of OrthoReD was highly similar to the outputs of two other published orthology prediction tools, OrthologID and/or OrthoDB, for the three dataset tested, which represented three phyla with different ranges of species diversity and different number of genomes included. Median CPU time for ortholog prediction per gene by OrthoReD executed on a desktop computer was <15 min even for the largest dataset tested, which included all coding sequences of 100 bacterial species. With high-throughput sequencing, unprecedented numbers of genes from non-model organisms are available with increasing need for clear information about their orthologies and/or functional equivalents in model organisms. OrthoReD is not only fast and accurate as an orthology prediction tool, but also gives researchers flexibility in the number of genes analyzed at a time, without requiring a high-performance computing cluster.

  1. APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.

    Science.gov (United States)

    Xia, Jun-Feng; Zhao, Xing-Ming; Song, Jiangning; Huang, De-Shuang

    2010-04-08

    It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying their interactions. Experimental hot spots detection methods such as alanine scanning mutagenesis are not applicable on a large scale since they are time consuming and expensive. Therefore, reliable and efficient computational methods for identifying hot spots are greatly desired and urgently required. In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces. We systematically investigate a wide variety of 62 features from a combination of protein sequence and structure information. Then, to remove redundant and irrelevant features and improve the prediction performance, feature selection is employed using the F-score method. Based on the selected features, nine individual-feature based predictors are developed to identify hot spots using SVMs. Furthermore, a new ensemble classifier, namely APIS (A combined model based on Protrusion Index and Solvent accessibility), is developed to further improve the prediction accuracy. The results on two benchmark datasets, ASEdb and BID, show that this proposed method yields significantly better prediction accuracy than those previously published in the literature. In addition, we also demonstrate the predictive power of our proposed method by modelling two protein complexes: the calmodulin/myosin light chain kinase complex and the heat shock locus gene products U and V complex, which indicate that our method can identify more hot spots in these two complexes compared with other state-of-the-art methods. We have developed an accurate prediction model for hot spot residues, given the structure of a protein complex. A major contribution of this study is to propose several new features based on the protrusion index of amino acid residues, which

  2. Accurate prediction of vaccine stability under real storage conditions and during temperature excursions.

    Science.gov (United States)

    Clénet, Didier

    2018-01-13

    Due to their thermosensitivity, most vaccines must be kept refrigerated from production to use. To successfully carry out global immunization programs, ensuring the stability of vaccines is crucial. In this context, two important issues are critical, namely: (i) predicting vaccine stability and (ii) preventing product damage due to excessive temperature excursions outside of the recommended storage conditions (cold chain break). We applied a combination of advanced kinetics and statistical analyses on vaccine forced degradation data to accurately describe the loss of antigenicity for a multivalent freeze-dried inactivated virus vaccine containing three variants. The screening of large amounts of kinetic models combined with a statistical model selection approach resulted in the identification of two-step kinetic models. Predictions based on kinetic analysis and experimental stability data were in agreement, with approximately five percentage points difference from real values for long-term stability storage conditions, after excursions of temperature and during experimental shipments of freeze-dried products. Results showed that modeling a few months of forced degradation can be used to predict various time and temperature profiles endured by vaccines, i.e. long-term stability, short time excursions outside the labeled storage conditions or shipments at ambient temperature, with high accuracy. Pharmaceutical applications of the presented kinetics-based approach are discussed. Copyright © 2018. Published by Elsevier B.V.

  3. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    Energy Technology Data Exchange (ETDEWEB)

    Shvab, I.; Sadus, Richard J., E-mail: rsadus@swin.edu.au [Centre for Molecular Simulation, Swinburne University of Technology, PO Box 218, Hawthorn, Victoria 3122 (Australia)

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  4. Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

    Science.gov (United States)

    Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

    2016-03-01

    The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

  5. Accurate Prediction of Complex Structure and Affinity for a Flexible Protein Receptor and Its Inhibitor.

    Science.gov (United States)

    Bekker, Gert-Jan; Kamiya, Narutoshi; Araki, Mitsugu; Fukuda, Ikuo; Okuno, Yasushi; Nakamura, Haruki

    2017-06-13

    In order to predict the accurate binding configuration as well as the binding affinity for a flexible protein receptor and its inhibitor drug, enhanced sampling with multicanonical molecular dynamics (McMD) simulation and thermodynamic integration (TI) were combined as a general drug docking method. CDK2, cyclin-dependent kinase 2, is involved in the cell cycle regulation. Malfunctions in CDK2 can cause tumorigenesis, and thus it is a potential drug target. Here, we performed a long McMD simulation for docking the inhibitor CS3 to CDK2 starting from the unbound structure. Subsequently, a potential binding/unbinding pathway was given from the multicanonical ensemble, and the binding free energy was readily computed by TI along the pathway. Using this combination, the correct binding configuration of CS3 to CDK2 was obtained, and its affinity coincided well with the experimental value.

  6. Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models

    CERN Document Server

    Blackman, Jonathan; Galley, Chad R; Szilagyi, Bela; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-01-01

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second dependin...

  7. Can physicians accurately predict which patients will lose weight, improve nutrition and increase physical activity?

    Science.gov (United States)

    Pollak, Kathryn I; Coffman, Cynthia J; Alexander, Stewart C; Tulsky, James A; Lyna, Pauline; Dolor, Rowena J; Cox, Mary E; Brouwer, Rebecca J Namenek; Bodner, Michael E; Østbye, Truls

    2012-10-01

    Physician counselling may help patients increase physical activity, improve nutrition and lose weight. However, physicians have low outcome expectations that patients will change. The aims are to describe the accuracy of physicians' outcome expectations about whether patients will follow weight loss, nutrition and physical activity recommendations. The relationships between physician outcome expectations and patient motivation and confidence also are assessed. This was an observational study that audio recorded encounters between 40 primary care physicians and 461 of their overweight or obese patients. We surveyed physicians to assess outcome expectations that patients will lose weight, improve nutrition and increase physical activity after counselling. We assessed actual patient change in behaviours from baseline to 3 months after the encounter and changes in motivation and confidence from baseline to immediately post-encounter. Right after the visit, ~55% of the time physicians were optimistic that their individual patients would improve. Physicians were not very accurate about which patients actually would improve weight, nutrition and physical activity. More patients had higher confidence to lose weight when physicians thought that patients would be likely to follow their weight loss recommendations. Physicians are moderately optimistic that patients will follow their weight loss, nutrition and physical activity recommendations. Patients might perceive physicians' confidence in them and thus feel more confident themselves. Physicians, however, are not very accurate in predicting which patients will or will not change behaviours. Their optimism, although helpful for patient confidence, might make physicians less receptive to learning effective counselling techniques.

  8. In vitro transcription accurately predicts lac repressor phenotype in vivo in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Matthew Almond Sochor

    2014-07-01

    Full Text Available A multitude of studies have looked at the in vivo and in vitro behavior of the lac repressor binding to DNA and effector molecules in order to study transcriptional repression, however these studies are not always reconcilable. Here we use in vitro transcription to directly mimic the in vivo system in order to build a self consistent set of experiments to directly compare in vivo and in vitro genetic repression. A thermodynamic model of the lac repressor binding to operator DNA and effector is used to link DNA occupancy to either normalized in vitro mRNA product or normalized in vivo fluorescence of a regulated gene, YFP. An accurate measurement of repressor, DNA and effector concentrations were made both in vivo and in vitro allowing for direct modeling of the entire thermodynamic equilibrium. In vivo repression profiles are accurately predicted from the given in vitro parameters when molecular crowding is considered. Interestingly, our measured repressor–operator DNA affinity differs significantly from previous in vitro measurements. The literature values are unable to replicate in vivo binding data. We therefore conclude that the repressor-DNA affinity is much weaker than previously thought. This finding would suggest that in vitro techniques that are specifically designed to mimic the in vivo process may be necessary to replicate the native system.

  9. A machine learned classifier that uses gene expression data to accurately predict estrogen receptor status.

    Directory of Open Access Journals (Sweden)

    Meysam Bastani

    Full Text Available BACKGROUND: Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. METHODS: To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. RESULTS: This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. CONCLUSIONS: Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions.

  10. Measuring solar reflectance Part I: Defining a metric that accurately predicts solar heat gain

    Energy Technology Data Exchange (ETDEWEB)

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-05-14

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.

  11. A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

    Science.gov (United States)

    Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

    2013-01-01

    Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

  12. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    Directory of Open Access Journals (Sweden)

    Zheng-Wei Li

    2016-08-01

    Full Text Available Protein-protein interactions (PPIs occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research.

  13. Improved CYP3A4 Molecular Models Accurately Predict Phe215 Requirement for Raloxifene Dehydrogenation Selectivity

    Science.gov (United States)

    Moore, Chad D.; Shahrokh, Kiumars; Sontum, Stephen F.; Cheatham, Thomas E.; Yost, Garold S.

    2010-01-01

    The use of molecular modeling in conjunction with site-directed mutagenesis has extensively been used to study substrate orientation within cytochrome P450 active sites, and to identify potential residues involved in positioning and catalytic mechanisms of these substrates. However, because docking studies utilize static models to simulate dynamic P450 enzymes, the effectiveness of these studies are highly dependent on accurate enzyme models. This study employed a cytochrome P450 3A4 (CYP3A4) crystal structure (PDB code:1W0E) to predict the sites of metabolism of the known CYP3A4 substrate raloxifene. In addition, partial charges were incorporated into the P450 heme moiety to investigate the effect of the modified CYP3A4 model on metabolite prediction with the ligand-docking program Autodock. Dehydrogenation of raloxifene to an electrophilic di-quinone methide intermediate has been linked to the potent inactivation of CYP3A4. Active site residues involved in the positioning and/or catalysis of raloxifene supporting dehydrogenation were identified with the two models, and site-directed mutagenesis studies were conducted to validate the models. The addition of partial charges to the heme moiety increased accuracy of the docking studies, increasing the number of conformations predicting dehydrogenation, and facilitating the identification of substrate/active site residue interactions. Based on the improved model, the Phe215 residue was hypothesized to play an important role in orienting raloxifene for dehydrogenation through a combination of electrostatic and steric interactions. Substitution of this residue with glycine or glutamine significantly decreased dehydrogenation rates without concurrent changes in the rates of raloxifene oxygenation. Thus, the improved structural model predicted novel enzyme/substrate interactions that control the selective dehydrogenation of raloxifene to its protein-binding intermediate. PMID:20812728

  14. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

    Science.gov (United States)

    Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

    2017-04-01

    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

  15. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    Science.gov (United States)

    Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish

    2016-04-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.

  16. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    Directory of Open Access Journals (Sweden)

    Matias I Maturana

    2016-04-01

    Full Text Available Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants. Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF, i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.

  17. Accurate load prediction by BEM with airfoil data from 3D RANS simulations

    Science.gov (United States)

    Schneider, Marc S.; Nitzsche, Jens; Hennings, Holger

    2016-09-01

    In this paper, two methods for the extraction of airfoil coefficients from 3D CFD simulations of a wind turbine rotor are investigated, and these coefficients are used to improve the load prediction of a BEM code. The coefficients are extracted from a number of steady RANS simulations, using either averaging of velocities in annular sections, or an inverse BEM approach for determination of the induction factors in the rotor plane. It is shown that these 3D rotor polars are able to capture the rotational augmentation at the inner part of the blade as well as the load reduction by 3D effects close to the blade tip. They are used as input to a simple BEM code and the results of this BEM with 3D rotor polars are compared to the predictions of BEM with 2D airfoil coefficients plus common empirical corrections for stall delay and tip loss. While BEM with 2D airfoil coefficients produces a very different radial distribution of loads than the RANS simulation, the BEM with 3D rotor polars manages to reproduce the loads from RANS very accurately for a variety of load cases, as long as the blade pitch angle is not too different from the cases from which the polars were extracted.

  18. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    Energy Technology Data Exchange (ETDEWEB)

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  19. Accurate First-Principles Spectra Predictions for Planetological and Astrophysical Applications at Various T-Conditions

    Science.gov (United States)

    Rey, M.; Nikitin, A. V.; Tyuterev, V.

    2014-06-01

    Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

  20. Accurate and robust genomic prediction of celiac disease using statistical learning.

    Directory of Open Access Journals (Sweden)

    Gad Abraham

    2014-02-01

    Full Text Available Practical application of genomic-based risk stratification to clinical diagnosis is appealing yet performance varies widely depending on the disease and genomic risk score (GRS method. Celiac disease (CD, a common immune-mediated illness, is strongly genetically determined and requires specific HLA haplotypes. HLA testing can exclude diagnosis but has low specificity, providing little information suitable for clinical risk stratification. Using six European cohorts, we provide a proof-of-concept that statistical learning approaches which simultaneously model all SNPs can generate robust and highly accurate predictive models of CD based on genome-wide SNP profiles. The high predictive capacity replicated both in cross-validation within each cohort (AUC of 0.87-0.89 and in independent replication across cohorts (AUC of 0.86-0.9, despite differences in ethnicity. The models explained 30-35% of disease variance and up to ∼43% of heritability. The GRS's utility was assessed in different clinically relevant settings. Comparable to HLA typing, the GRS can be used to identify individuals without CD with ≥99.6% negative predictive value however, unlike HLA typing, fine-scale stratification of individuals into categories of higher-risk for CD can identify those that would benefit from more invasive and costly definitive testing. The GRS is flexible and its performance can be adapted to the clinical situation by adjusting the threshold cut-off. Despite explaining a minority of disease heritability, our findings indicate a genomic risk score provides clinically relevant information to improve upon current diagnostic pathways for CD and support further studies evaluating the clinical utility of this approach in CD and other complex diseases.

  1. Can radiation therapy treatment planning system accurately predict surface doses in postmastectomy radiation therapy patients?

    Science.gov (United States)

    Wong, Sharon; Back, Michael; Tan, Poh Wee; Lee, Khai Mun; Baggarley, Shaun; Lu, Jaide Jay

    2012-01-01

    Skin doses have been an important factor in the dose prescription for breast radiotherapy. Recent advances in radiotherapy treatment techniques, such as intensity-modulated radiation therapy (IMRT) and new treatment schemes such as hypofractionated breast therapy have made the precise determination of the surface dose necessary. Detailed information of the dose at various depths of the skin is also critical in designing new treatment strategies. The purpose of this work was to assess the accuracy of surface dose calculation by a clinically used treatment planning system and those measured by thermoluminescence dosimeters (TLDs) in a customized chest wall phantom. This study involved the construction of a chest wall phantom for skin dose assessment. Seven TLDs were distributed throughout each right chest wall phantom to give adequate representation of measured radiation doses. Point doses from the CMS Xio® treatment planning system (TPS) were calculated for each relevant TLD positions and results correlated. There were no significant difference between measured absorbed dose by TLD and calculated doses by the TPS (p > 0.05 (1-tailed). Dose accuracy of up to 2.21% was found. The deviations from the calculated absorbed doses were overall larger (3.4%) when wedges and bolus were used. 3D radiotherapy TPS is a useful and accurate tool to assess the accuracy of surface dose. Our studies have shown that radiation treatment accuracy expressed as a comparison between calculated doses (by TPS) and measured doses (by TLD dosimetry) can be accurately predicted for tangential treatment of the chest wall after mastectomy. Copyright © 2012 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

  2. Accurate prediction of spectral phonon relaxation time and thermal conductivity of intrinsic and perturbed materials

    Science.gov (United States)

    Feng, Tianli

    The prediction of spectral phonon relaxation time, mean-free-path, and thermal conductivity can provide significant insights into the thermal conductivity of bulk and nanomaterials, which are important for thermal management and thermoelectric applications. We perform frequency-domain normal mode analysis (NMA) on pure bulk argon and pure bulk germanium. Spectral phonon properties, including the phonon dispersion, relaxation time, mean free path, and thermal conductivity of argon and germanium at different temperatures have been calculated. We find the dependence of phonon relaxation time tau on frequency o and temperature T vary from ~o-1.3 to ~o -1.8 and ~T-0.8 to ~T-1.8 for argon, and from ~o-0.6 to ~o-2.8 and ~T -0.4 to ~T-2.5 for germanium. The predicted thermal conductivities are in reasonable agreement with those obtained from the Green-Kubo method. We show, using both analytical derivations and numerical simulations, that the eigenvectors are necessary in time-domain NMA but unnecessary in frequency-domain NMA. The function of eigenvectors in frequency-domain NMA is to distinguish each phonon branch. Furthermore, it is found in solids not only the phonon frequency but also the phonon eigenvector can shift from harmonic lattice profile at finite temperature, due to thermal expansion and anharmonicity of interatomic potential. The anharmonicity of phonon eigenvector, different with that of frequency, only exists in the materials which contain at least two types of atoms and two different interatomic forces. Introducing anharmonic eigenvectors makes it easier to distinguish phonon branches in frequency-domain NMA although does not influence the results. For time-domain NMA, anharmonic eigenvectors make the results more accurate than harmonic eigenvectors. In addition, the phonon spectral relaxation time of defective silicon is calculated from frequency-domain NMA based on molecular dynamics. We show that the thermal conductivity k predicted from this approach

  3. Life history traits to predict biogeographic species distributions in bivalves

    Science.gov (United States)

    Montalto, V.; Rinaldi, A.; Sarà, G.

    2015-10-01

    Organismal fecundity ( F) and its relationship with body size (BS) are key factors in predicting species distribution under current and future scenarios of global change. A functional trait-based dynamic energy budget (FT-DEB) is proposed as a mechanistic approach to predict the variation of F and BS as function of environmental correlates using two marine bivalves as model species ( Mytilus galloprovincialis and Brachidontes pharaonis). Validation proof of model skill (i.e., degree of correspondence between model predictions and field observations) and stationarity (i.e., ability of a model generated from data collected at one place/time to predict processes at another place/time) was provided to test model performance in predicting the bivalve distribution throughout the 22 sites in the Central Mediterranean Sea under local conditions of food density and body temperature. Model skill and stationarity were tested through the estimate of commission (i.e., proportion of species' absences predicted present) and omission (i.e., proportion of presences predicted absent) errors of predictions by comparing mechanistic predicted vs. observed F and BS values throughout the study area extrapolated by lab experiments and literature search. The resulting relationship was reliable for both species, and body size and fecundity were highly correlated in M. galloprovincialis compared to B. pharaonis; FT-DEB showed correct predictions of presence in more than 75 % of sites, and the regression between BS predicted vs. observed was highly significant in both species. Whilst recognising the importance of biotic interactions in shaping the distribution of species, our FT-DEB approach provided reliable quantitative estimates of where our species had sufficient F to support local populations or suggesting reproductive failure. Mechanistically, estimating F and BS as key traits of species life history can also be addressed within a broader, scale-dependent context that surpasses the

  4. Artificial neural networks accurately predict mortality in patients with nonvariceal upper GI bleeding.

    Science.gov (United States)

    Rotondano, Gianluca; Cipolletta, Livio; Grossi, Enzo; Koch, Maurizio; Intraligi, Marco; Buscema, Massimo; Marmo, Riccardo

    2011-02-01

    Risk stratification systems that accurately identify patients with a high risk for bleeding through the use of clinical predictors of mortality before endoscopic examination are needed. Computerized (artificial) neural networks (ANNs) are adaptive tools that may improve prognostication. To assess the capability of an ANN to predict mortality in patients with nonvariceal upper GI bleeding and compare the predictive performance of the ANN with that of the Rockall score. Prospective, multicenter study. Academic and community hospitals. This study involved 2380 patients with nonvariceal upper GI bleeding. Upper GI endoscopy. The primary outcome variable was 30-day mortality, defined as any death occurring within 30 days of the index bleeding episode. Other outcome variables were recurrent bleeding and need for surgery. We performed analysis of certified outcomes of 2380 patients with nonvariceal upper GI bleeding. The Rockall score was compared with a supervised ANN (TWIST system, Semeion), adopting the same result validation protocol with random allocation of the sample in training and testing subsets and subsequent crossover. Overall, death occurred in 112 cases (4.70%). Of 68 pre-endoscopic input variables, 17 were selected and used by the ANN versus 16 included in the Rockall score. The sensitivity of the ANN-based model was 83.8% (76.7-90.8) versus 71.4% (62.8-80.0) for the Rockall score. Specificity was 97.5 (96.8-98.2) and 52.0 (49.8 4.2), respectively. Accuracy was 96.8% (96.0-97.5) versus 52.9% (50.8-55.0) (Pperformance of the ANN-based model for prediction of mortality was significantly superior to that of the complete Rockall score (area under the curve 0.95 [0.92-0.98] vs 0.67 [0.65-0.69]; P<.001). External validation on a subsequent independent population is needed, patients with variceal bleeding and obscure GI hemorrhage are excluded. In patients with nonvariceal upper GI bleeding, ANNs are significantly superior to the Rockall score in predicting the

  5. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    Science.gov (United States)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  6. Accurate secondary structure prediction and fold recognition for circular dichroism spectroscopy.

    Science.gov (United States)

    Micsonai, András; Wien, Frank; Kernya, Linda; Lee, Young-Ho; Goto, Yuji; Réfrégiers, Matthieu; Kardos, József

    2015-06-16

    Circular dichroism (CD) spectroscopy is a widely used technique for the study of protein structure. Numerous algorithms have been developed for the estimation of the secondary structure composition from the CD spectra. These methods often fail to provide acceptable results on α/β-mixed or β-structure-rich proteins. The problem arises from the spectral diversity of β-structures, which has hitherto been considered as an intrinsic limitation of the technique. The predictions are less reliable for proteins of unusual β-structures such as membrane proteins, protein aggregates, and amyloid fibrils. Here, we show that the parallel/antiparallel orientation and the twisting of the β-sheets account for the observed spectral diversity. We have developed a method called β-structure selection (BeStSel) for the secondary structure estimation that takes into account the twist of β-structures. This method can reliably distinguish parallel and antiparallel β-sheets and accurately estimates the secondary structure for a broad range of proteins. Moreover, the secondary structure components applied by the method are characteristic to the protein fold, and thus the fold can be predicted to the level of topology in the CATH classification from a single CD spectrum. By constructing a web server, we offer a general tool for a quick and reliable structure analysis using conventional CD or synchrotron radiation CD (SRCD) spectroscopy for the protein science research community. The method is especially useful when X-ray or NMR techniques fail. Using BeStSel on data collected by SRCD spectroscopy, we investigated the structure of amyloid fibrils of various disease-related proteins and peptides.

  7. The presence of prostate cancer on saturation biopsy can be accurately predicted.

    Science.gov (United States)

    Ahyai, Sascha A; Isbarn, Hendrik; Karakiewicz, Pierre I; Chun, Felix K H; Reichert, Mathias; Walz, Jochen; Steuber, Thomas; Jeldres, Claudio; Schlomm, Thorsten; Heinzer, Hans; Salomon, Georg; Budäus, Lars; Perrotte, Paul; Huland, Hartwig; Graefen, Markus; Haese, Alexander

    2010-03-01

    To improve the ability of our previously reported saturation biopsy nomogram quantifying the risk of prostate cancer, as the use of office-based saturation biopsy has increased. Saturation biopsies of 540 men with one or more previously negative 6-12 core biopsies were used to develop a multivariable logistic regression model-based nomogram, predicting the probability of prostate cancer. Candidate predictors were used in their original or stratified format, and consisted of age, total prostate-specific antigen (PSA) level, percentage free PSA (%fPSA), gland volume, findings on a digital rectal examination, cumulative number of previous biopsy sessions, presence of high-grade prostatic intraepithelial neoplasia on any previous biopsy, and presence of atypical small acinar proliferation (ASAP) on any previous biopsy. Two hundred bootstraps re-samples were used to adjust for overfit bias. Prostate cancer was diagnosed in 39.4% of saturation biopsies. Age, total PSA, %fPSA, gland volume, number of previous biopsies, and presence of ASAP at any previous biopsy were independent predictors for prostate cancer (all P < 0.05). The nomogram was 77.2% accurate and had a virtually perfect correlation between predicted and observed rates of prostate cancer. We improved the accuracy of the saturation biopsy nomogram from 72% to 77%; it relies on three previously included variables, i.e. age, %fPSA and prostate volume, and on three previously excluded variables, i.e. PSA, the number of previous biopsy sessions, and evidence of ASAP on previous biopsy. Our study represents the largest series of saturation biopsies to date.

  8. ROCK I Has More Accurate Prognostic Value than MET in Predicting Patient Survival in Colorectal Cancer.

    Science.gov (United States)

    Li, Jian; Bharadwaj, Shruthi S; Guzman, Grace; Vishnubhotla, Ramana; Glover, Sarah C

    2015-06-01

    Colorectal cancer remains the second leading cause of death in the United States despite improvements in incidence rates and advancements in screening. The present study evaluated the prognostic value of two tumor markers, MET and ROCK I, which have been noted in other cancers to provide more accurate prognoses of patient outcomes than tumor staging alone. We constructed a tissue microarray from surgical specimens of adenocarcinomas from 108 colorectal cancer patients. Using immunohistochemistry, we examined the expression levels of tumor markers MET and ROCK I, with a pathologist blinded to patient identities and clinical outcomes providing the scoring of MET and ROCK I expression. We then used retrospective analysis of patients' survival data to provide correlations with expression levels of MET and ROCK I. Both MET and ROCK I were significantly over-expressed in colorectal cancer tissues, relative to the unaffected adjacent mucosa. Kaplan-Meier survival analysis revealed that patients' 5-year survival was inversely correlated with levels of expression of ROCK I. In contrast, MET was less strongly correlated with five-year survival. ROCK I provides better efficacy in predicting patient outcomes, compared to either tumor staging or MET expression. As a result, ROCK I may provide a less invasive method of assessing patient prognoses and directing therapeutic interventions. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  9. Cluster abundance in chameleon f(R) gravity I: toward an accurate halo mass function prediction

    Science.gov (United States)

    Cataneo, Matteo; Rapetti, David; Lombriser, Lucas; Li, Baojiu

    2016-12-01

    We refine the mass and environment dependent spherical collapse model of chameleon f(R) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f(R) halo abundance with respect to that of General Relativity (GR) within a precision of lesssim 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f(R) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.

  10. Accurate prediction of DnaK-peptide binding via homology modelling and experimental data.

    Directory of Open Access Journals (Sweden)

    Joost Van Durme

    2009-08-01

    Full Text Available Molecular chaperones are essential elements of the protein quality control machinery that governs translocation and folding of nascent polypeptides, refolding and degradation of misfolded proteins, and activation of a wide range of client proteins. The prokaryotic heat-shock protein DnaK is the E. coli representative of the ubiquitous Hsp70 family, which specializes in the binding of exposed hydrophobic regions in unfolded polypeptides. Accurate prediction of DnaK binding sites in E. coli proteins is an essential prerequisite to understand the precise function of this chaperone and the properties of its substrate proteins. In order to map DnaK binding sites in protein sequences, we have developed an algorithm that combines sequence information from peptide binding experiments and structural parameters from homology modelling. We show that this combination significantly outperforms either single approach. The final predictor had a Matthews correlation coefficient (MCC of 0.819 when assessed over the 144 tested peptide sequences to detect true positives and true negatives. To test the robustness of the learning set, we have conducted a simulated cross-validation, where we omit sequences from the learning sets and calculate the rate of repredicting them. This resulted in a surprisingly good MCC of 0.703. The algorithm was also able to perform equally well on a blind test set of binders and non-binders, of which there was no prior knowledge in the learning sets. The algorithm is freely available at http://limbo.vib.be.

  11. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models.

    Science.gov (United States)

    Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  12. Accurate prediction of pregnancy viability by means of a simple scoring system.

    Science.gov (United States)

    Bottomley, Cecilia; Van Belle, Vanya; Kirk, Emma; Van Huffel, Sabine; Timmerman, Dirk; Bourne, Tom

    2013-01-01

    What is the performance of a simple scoring system to predict whether women will have an ongoing viable intrauterine pregnancy beyond the first trimester? A simple scoring system using demographic and initial ultrasound variables accurately predicts pregnancy viability beyond the first trimester with an area under the curve (AUC) in a receiver operating characteristic curve of 0.924 [95% confidence interval (CI) 0.900-0.947] on an independent test set. Individual demographic and ultrasound factors, such as maternal age, vaginal bleeding and gestational sac size, are strong predictors of miscarriage. Previous mathematical models have combined individual risk factors with reasonable performance. A simple scoring system derived from a mathematical model that can be easily implemented in clinical practice has not previously been described for the prediction of ongoing viability. This was a prospective observational study in a single early pregnancy assessment centre during a 9-month period. A cohort of 1881 consecutive women undergoing transvaginal ultrasound scan at a gestational age system was derived from this. This scoring system was tested on an independent test data set. The final outcome based on a total of 1435 participants was an ongoing viable pregnancy in 885 (61.7%) and early pregnancy loss in 550 (38.3%) women. The scoring system using significant demographic variables alone (maternal age and amount of bleeding) to predict ongoing viability gave an AUC of 0.724 (95% CI = 0.692-0.756) in the training set and 0.729 (95% CI = 0.684-0.774) in the test set. The scoring system using significant ultrasound variables alone (mean gestation sac diameter, mean yolk sac diameter and the presence of fetal heart beat) gave an AUC of 0.873 (95% CI = 0.850-0.897) and 0.900 (95% CI = 0.871-0.928) in the training and the test sets, respectively. The final scoring system using demographic and ultrasound variables together gave an AUC of 0.901 (95% CI = 0.881-0.920) and 0

  13. Unilateral prostate cancer cannot be accurately predicted in low-risk patients.

    Science.gov (United States)

    Isbarn, Hendrik; Karakiewicz, Pierre I; Vogel, Susanne; Jeldres, Claudio; Lughezzani, Giovanni; Briganti, Alberto; Montorsi, Francesco; Perrotte, Paul; Ahyai, Sascha A; Budäus, Lars; Eichelberg, Christian; Heuer, Roman; Köllermann, Jens; Sauter, Guido; Schlomm, Thorsten; Steuber, Thomas; Haese, Alexander; Zacharias, Mario; Fisch, Margit; Heinzer, Hans; Huland, Hartwig; Chun, Felix K H; Graefen, Markus

    2010-07-01

    Hemiablative therapy (HAT) is increasing in popularity for treatment of patients with low-risk prostate cancer (PCa). The validity of this therapeutic modality, which exclusively treats PCa within a single prostate lobe, rests on accurate staging. We tested the accuracy of unilaterally unremarkable biopsy findings in cases of low-risk PCa patients who are potential candidates for HAT. The study population consisted of 243 men with clinical stage predict the presence of unilateral PCa. This was reflected in an overall accuracy of 58% (95% confidence interval, 50.6-65.8%). Two-thirds of patients with unilateral low-risk PCa, confirmed by clinical stage and biopsy findings, have bilateral or non-organ-confined PCa at radical prostatectomy. This alarming finding questions the safety and validity of HAT. (c) 2010 Elsevier Inc. All rights reserved.

  14. Raoult's law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments.

    Science.gov (United States)

    Bowler, Michael G; Bowler, David R; Bowler, Matthew W

    2017-04-01

    The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111-114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult's law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult's law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult's law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample.

  15. A new somatic cell count index to more accurately predict milk yield losses

    Directory of Open Access Journals (Sweden)

    J. Jeretina

    2017-10-01

    Full Text Available Intramammary infection and clinical mastitis in dairy cows leads to considerable economic losses for farmers. The somatic cell concentration in cow's milk has been shown to be an excellent indicator for the prevalence of subclinical mastitis. In this study, a new somatic cell count index (SCCI was proposed for the accurate prediction of milk yield losses caused by elevated somatic cell count (SCC. In all, 97 238 lactations (55 207 Holstein cows from 2328 herds were recorded between 2010 and 2014 under different scenarios (high and low levels of SCC, four lactation stages, different milk yield intensities, and parities (1, 2, and  ≥  3. The standard shape of the curve for SCC was determined using completed standard lactations of healthy cows. The SCCI was defined as the sum of the differences between the measured interpolated values of the natural logarithm of SCC (ln(SCC and the values for the standard shape of the curve for SCC for a particular period, divided by the total area enclosed by the standard curve and upper limit of ln(SCC  =  10 for SCC. The phenotypic potential of milk yield (305-day milk yield – MY305 was calculated using regression coefficients estimated from the linear regression model for parity and breeding values of cows for milk yield. The extent of daily milk yield loss caused by increased SCC was found to be mainly related to the early stage of lactation. Depending on the possible scenarios, the estimated milk yield loss from MY305 for primiparous cows was at least 0.8 to 0.9 kg day−1 and for multiparous cows it ranged from 1.3 to 4.3 kg day−1. Thus, the SCCI was a suitable indicator for estimating daily milk yield losses associated with increased SCC and might provide farmers reliable information to take appropriate measures for ensuring good health of cows and reducing milk yield losses at the herd level.

  16. Towards Accurate Prediction of Unbalance Response, Oil Whirl and Oil Whip of Flexible Rotors Supported by Hydrodynamic Bearings

    Directory of Open Access Journals (Sweden)

    Rob Eling

    2016-09-01

    Full Text Available Journal bearings are used to support rotors in a wide range of applications. In order to ensure reliable operation, accurate analyses of these rotor-bearing systems are crucial. Coupled analysis of the rotor and the journal bearing is essential in the case that the rotor is flexible. The accuracy of prediction of the model at hand depends on its comprehensiveness. In this study, we construct three bearing models of increasing modeling comprehensiveness and use these to predict the response of two different rotor-bearing systems. The main goal is to evaluate the correlation with measurement data as a function of modeling comprehensiveness: 1D versus 2D pressure prediction, distributed versus lumped thermal model, Newtonian versus non-Newtonian fluid description and non-mass-conservative versus mass-conservative cavitation description. We conclude that all three models predict the existence of critical speeds and whirl for both rotor-bearing systems. However, the two more comprehensive models in general show better correlation with measurement data in terms of frequency and amplitude. Furthermore, we conclude that a thermal network model comprising temperature predictions of the bearing surroundings is essential to obtain accurate predictions. The results of this study aid in developing accurate and computationally-efficient models of flexible rotors supported by plain journal bearings.

  17. Paley's multiplier method does not accurately predict adult height in children with bone sarcoma

    National Research Council Canada - National Science Library

    Gilg, Magdalena Maria; Wibmer, Christine; Andreou, Dimosthenis; Avian, Alexander; Sovinz, Petra; Maurer-Ertl, Werner; Tunn, Per-Ulf; Leithner, Andreas

    2014-01-01

    .... Paley's multiplier is used for height prediction in healthy children, and has been suggested as a method to make growth predictions for children with osteosarcoma and Ewing's sarcoma when considering...

  18. Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

    Directory of Open Access Journals (Sweden)

    Yong-Bi Fu

    2017-07-01

    Full Text Available Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

  19. Towards more accurate wind and solar power prediction by improving NWP model physics

    Science.gov (United States)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  20. Accurate wavelength prediction of photonic crystal resonant reflection and applications in refractive index measurement

    DEFF Research Database (Denmark)

    Hermannsson, Pétur Gordon; Vannahme, Christoph; Smith, Cameron L. C.

    2014-01-01

    In the past decade, photonic crystal resonant reflectors have been increasingly used as the basis for label-free biochemical assays in lab-on-a-chip applications. In both designing and interpreting experimental results, an accurate model describing the optical behavior of such structures is essen...

  1. Resting metabolic rate prediction equations in teenagers: history and validity

    Directory of Open Access Journals (Sweden)

    Paulo Henrique Santos da Fonseca

    2008-01-01

    Full Text Available http://dx.doi.org/10.5007/1980-0037.2008v10n4p405 The resting metabolic rate (RMR has been utilized routinely by clinics to predict the energy necessary for patients. Additionally, governmental agencies and health organizations define the energy necessary for the population and the energy orientation for athletes who play sports. Many recognize the value of the RMR, but it is not always possible to measure it by using calorimetry, so it is suggested to use equations of prediction for this variable. However, RMR prediction equations must be used in such a way that allows its frequent reexamination to guarantee efficiency. This article has three purposes: 1 to analyze the development history of the traditional equations by Harris and Benedict (1919, Schofield (1985, WHO/FAO/UNU (1985, and Henry and Rees (1991 (these authors routinely used the traditional equations to measure the RMR in teenagers; 2 to analyze the studies that tested the validity of these equations in the population of teenagers; 3 to argue and point out possible intervening factors on the RMR results of teenagers, thus guiding to election of independent variables when developing equations for Brazilian’s population. After analyzing the equations, it is possible to conclude that: 1 the equations had been developed by having a given base of compiled evaluations from the beginning of the Twentieth Century; 2 the studies that tested the validity of these equations demonstrated great variability in the results, confirming the impossibility to have a unique/universal equation. This study also showed that new RMR prediction equations must be developed for specific populations taking into consideration the race and where the individual resides.

  2. Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations.

    Science.gov (United States)

    Martin, Alicia R; Gignoux, Christopher R; Walters, Raymond K; Wojcik, Genevieve L; Neale, Benjamin M; Gravel, Simon; Daly, Mark J; Bustamante, Carlos D; Kenny, Eimear E

    2017-04-06

    The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  3. LOCUSTRA: accurate prediction of local protein structure using a two-layer support vector machine approach.

    Science.gov (United States)

    Zimmermann, Olav; Hansmann, Ulrich H E

    2008-09-01

    Constraint generation for 3d structure prediction and structure-based database searches benefit from fine-grained prediction of local structure. In this work, we present LOCUSTRA, a novel scheme for the multiclass prediction of local structure that uses two layers of support vector machines (SVM). Using a 16-letter structural alphabet from de Brevern et al. (Proteins: Struct., Funct., Bioinf. 2000, 41, 271-287), we assess its prediction ability for an independent test set of 222 proteins and compare our method to three-class secondary structure prediction and direct prediction of dihedral angles. The prediction accuracy is Q16=61.0% for the 16 classes of the structural alphabet and Q3=79.2% for a simple mapping to the three secondary classes helix, sheet, and coil. We achieve a mean phi(psi) error of 24.74 degrees (38.35 degrees) and a median RMSDA (root-mean-square deviation of the (dihedral) angles) per protein chain of 52.1 degrees. These results compare favorably with related approaches. The LOCUSTRA web server is freely available to researchers at http://www.fz-juelich.de/nic/cbb/service/service.php.

  4. An accurate and efficient method to predict the electronic excitation energies of BODIPY fluorescent dyes.

    Science.gov (United States)

    Wang, Jia-Nan; Jin, Jun-Ling; Geng, Yun; Sun, Shi-Ling; Xu, Hong-Liang; Lu, Ying-Hua; Su, Zhong-Min

    2013-03-15

    Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research. Copyright © 2012 Wiley Periodicals, Inc.

  5. Resting metabolic rate prediction equations in teenagers: history and validity

    Directory of Open Access Journals (Sweden)

    Paulo Henrique Santos da Fonseca

    2008-12-01

    Full Text Available The resting metabolic rate (RMR has been utilized routinely by clinics to predict the energy necessary forpatients. Additionally, governmental agencies and health organizations define the energy necessary for the population andthe energy orientation for athletes who play sports. Many recognize the value of the RMR, but it is not always possible tomeasure it by using calorimetry, so it is suggested to use equations of prediction for this variable. However, RMR predictionequations must be used in such a way that allows its frequent reexamination to guarantee efficiency. This article has threepurposes: 1 to analyze the development history of the traditional equations by Harris and Benedict (1919, Schofield (1985,WHO/FAO/UNU (1985, and Henry and Rees (1991 (these authors routinely used the traditional equations to measure theRMR in teenagers; 2 to analyze the studies that tested the validity of these equations in the population of teenagers; 3 toargue and point out possible intervening factors on the RMR results of teenagers, thus guiding to election of independentvariables when developing equations for Brazilian’s population. After analyzing the equations, it is possible to conclude that:1 the equations had been developed by having a given base of compiled evaluations from the beginning of the TwentiethCentury; 2 the studies that tested the validity of these equations demonstrated great variability in the results, confirmingthe impossibility to have a unique/universal equation. This study also showed that new RMR prediction equations must bedeveloped for specific populations taking into consideration the race and where the individual resides.

  6. Accurate predictions of iron redox state in silicate glasses: A multivariate approach using X-ray absorption spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Dyar, M. Darby; McCanta, Molly; Breves, Elly; Carey, C. J.; Lanzirotti, Antonio

    2016-03-01

    Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yield accurate results from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.

  7. Accurate predictions of iron redox state in silicate glasses: A multivariate approach using X-ray absorption spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Dyar, M. Darby; McCanta, Molly; Breves, Elly; Carey, C. J.; Lanzirotti, Antonio

    2016-03-01

    Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yield accurate results from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.

  8. Accurate microRNA target prediction correlates with protein repression levels

    Directory of Open Access Journals (Sweden)

    Simossis Victor A

    2009-09-01

    Full Text Available Abstract Background MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

  9. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

    Directory of Open Access Journals (Sweden)

    Jesse S. Jin

    2010-10-01

    Full Text Available Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

  10. How accurate and statistically robust are catalytic site predictions based on closeness centrality?

    Directory of Open Access Journals (Sweden)

    Livesay Dennis R

    2007-05-01

    Full Text Available Abstract Background We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex i and all other vertices. Results We benchmark the approach against 283 structurally unique proteins within the Catalytic Site Atlas. Our results, which are inline with previous investigations of smaller datasets, indicate closeness centrality predictions are statistically significant. However, unlike previous approaches, we specifically focus on residues with the very best scores. Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the first time that filtering the predictions by residue identity improves the results even more than accessibility filtering. Here, we simply eliminate residues with physiochemical properties unlikely to be compatible with catalytic requirements from consideration. Residue identity filtering improves the average true to false positive rate ratio to 26.3 to 1. Combining the two filters together has little affect on the results. Calculated p-values for the three prediction schemes range from 2.7E-9 to less than 8.8E-134. Finally, the sensitivity of the predictions to structure choice and slight perturbations is examined. Conclusion Our results resolutely confirm that closeness centrality is a viable prediction scheme whose predictions are statistically

  11. Towards more accurate prediction of ubiquitination sites: a comprehensive review of current methods, tools and features.

    Science.gov (United States)

    Chen, Zhen; Zhou, Yuan; Zhang, Ziding; Song, Jiangning

    2015-07-01

    Protein ubiquitination is one of the most important reversible post-translational modifications (PTMs). In many biochemical, pathological and pharmaceutical studies on understanding the function of proteins in biological processes, identification of ubiquitination sites is an important first step. However, experimental approaches for identifying ubiquitination sites are often expensive, labor-intensive and time-consuming, partly due to the dynamics and reversibility of ubiquitination. In silico prediction of ubiquitination sites is potentially a useful strategy for whole proteome annotation. A number of bioinformatics approaches and tools have recently been developed for predicting protein ubiquitination sites. However, these tools have different methodologies, prediction algorithms, functionality and features, which complicate their utility and application. The purpose of this review is to aid users in selecting appropriate tools for specific analyses and circumstances. We first compared five popular webservers and standalone software options, assessing their performance on four up-to-date ubiquitination benchmark datasets from Saccharomyces cerevisiae, Homo sapiens, Mus musculus and Arabidopsis thaliana. We then discussed and summarized these tools to guide users in choosing among the tools efficiently and rapidly. Finally, we assessed the importance of features of existing tools for ubiquitination site prediction, ranking them by performance. We also discussed the features that make noticeable contributions to species-specific ubiquitination site prediction. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  12. Nurses and physicians in a medical admission unit can accurately predict mortality of acutely admitted patients

    DEFF Research Database (Denmark)

    Brabrand, Mikkel; Hallas, Jesper; Knudsen, Torben

    2014-01-01

    BACKGROUND: There exist several risk stratification systems for predicting mortality of emergency patients. However, some are complex in clinical use and others have been developed using suboptimal methodology. The objective was to evaluate the capability of the staff at a medical admission unit......-hospital mortality upon the patients' arrival. We calculated discriminatory power as the area under the receiver-operating-characteristic curve (AUROC) and accuracy of prediction (calibration) by Hosmer-Lemeshow goodness-of-fit test. RESULTS: We had a total of 2,848 admissions (2,463 patients). 89 (3.1%) died while......: Using only clinical intuition, staff in a medical admission unit has a good ability to identify patients at increased risk of dying while admitted. When nursing staff and physicians agreed on their prediction, discriminatory power and calibration were excellent....

  13. A random protein-creatinine ratio accurately predicts baseline proteinuria in early pregnancy.

    Science.gov (United States)

    Hirshberg, Adi; Draper, Jennifer; Curley, Cara; Sammel, Mary D; Schwartz, Nadav

    2014-12-01

    Data surrounding the use of a random urine protein:creatinine ratio (PCR) in the diagnosis of preeclampsia is conflicting. We sought to determine whether PCR in early pregnancy can replace the 24-hour urine collection as the primary screening test in patients at risk for baseline proteinuria. Women requiring a baseline evaluation for proteinuria supplied a urine sample the morning after their 24-hour collection. The PCR was analyzed as a predictor of significant proteinuria (≥150 mg). A regression equation to estimate the 24-hour protein value from the PCR was then developed. Sixty of 135 subjects enrolled completed the study. The median 24-hour urine protein and PCR were 90 mg (IQR: 50-145) and 0.063 (IQR: 0.039-0.083), respectively. Fifteen patients (25%) had significant proteinuria. PCR was strongly correlated with the 24-hour protein value (r = 0.99, p protein = 46.5 + 904.2*PCR] accurately estimates the actual 24-hour protein (95% CI: ±88 mg). A random urine PCR accurately estimates the 24-hour protein excretion in the first half of pregnancy and can be used as the primary screening test for baseline proteinuria in at-risk patients.

  14. Predictive value of history taking and physical examination in diagnosing arrhythmias in general practice.

    Science.gov (United States)

    Hoefman, Emmy; Boer, Kimberly R; van Weert, Henk C P M; Reitsma, Johannes B; Koster, Rudolph W; Bindels, Patrick J E

    2007-12-01

    Palpitations and light-headedness are common symptoms that may be indicative of cardiac arrhythmias. Effective triage by the GP might prevent delayed treatment or inappropriate referrals. The aim of this study was to determine the capability of GPs to assess the presence of cardiac arrhythmias and which signs and symptoms are used in predicting the presence of arrhythmias and which actually are related to the presence of arrhythmias. A consecutive cohort of 127 patients presenting with palpitations and/or light-headedness to 41 GPs in the Netherlands underwent physical examination, patient history and standard electrocardiogram. The GPs' estimation of the probability of patients having an arrhythmia was compared with the diagnostic result of 30 days of continuous event recording (CER). We assessed discriminating factors that can assist a GP in diagnosing an arrhythmia. No correlation was found between the GPs' assessment of risk and actual diagnoses. GPs were more likely to predict an arrhythmia in patients who suffer from hypertension (P=0.049) or patients with a history of cardiovascular disease (P=0.006). Vasovagal symptoms [odds ratio (OR)=2.91, 95% confidence interval (CI) 1.1-7.6] and bradycardia (OR=4.2, 95% CI 1.3-14.0) were significantly more common in patients with a CER diagnosis of arrhythmia. Prediction of arrhythmias by GPs based on history taking and physical examination alone is not accurate. These parameters are insufficient to decide which patients need further diagnostic evaluation. A diagnostic facility with low threshold for GPs is essential for an adequate diagnostic process in patients with palpitations and light-headedness.

  15. Habitat history improves prediction of biodiversity in rainforest fauna.

    Science.gov (United States)

    Graham, Catherine H; Moritz, Craig; Williams, Stephen E

    2006-01-17

    Patterns of biological diversity should be interpreted in light of both contemporary and historical influences; however, to date, most attempts to explain diversity patterns have largely ignored history or have been unable to quantify the influence of historical processes. The historical effects on patterns of diversity have been hypothesized to be most important for taxonomic groups with poor dispersal abilities. We quantified the relative stability of rainforests over the late Quaternary period by modeling rainforest expansion and contraction in 21 biogeographic subregions in northeast Australia across four time periods. We demonstrate that historical habitat stability can be as important, and in endemic low-dispersal taxa even more important, than current habitat area in explaining spatial patterns of species richness. In contrast, patterns of endemic species richness for taxa with high dispersal capacity are best predicted by using current environmental parameters. We also show that contemporary patterns of species turnover across the region are best explained by historical patterns of habitat connectivity. These results clearly demonstrate that spatially explicit analyses of the historical processes of persistence and colonization are both effective and necessary for understanding observed patterns of biodiversity.

  16. Safe surgery: how accurate are we at predicting intra-operative blood loss?

    LENUS (Irish Health Repository)

    2012-02-01

    Introduction Preoperative estimation of intra-operative blood loss by both anaesthetist and operating surgeon is a criterion of the World Health Organization\\'s surgical safety checklist. The checklist requires specific preoperative planning when anticipated blood loss is greater than 500 mL. The aim of this study was to assess the accuracy of surgeons and anaesthetists at predicting intra-operative blood loss. Methods A 6-week prospective study of intermediate and major operations in an academic medical centre was performed. An independent observer interviewed surgical and anaesthetic consultants and registrars, preoperatively asking each to predict expected blood loss in millilitre. Intra-operative blood loss was measured and compared with these predictions. Parameters including the use of anticoagulation and anti-platelet therapy as well as intra-operative hypothermia and hypotension were recorded. Results One hundred sixty-eight operations were included in the study, including 142 elective and 26 emergency operations. Blood loss was predicted to within 500 mL of measured blood loss in 89% of cases. Consultant surgeons tended to underestimate blood loss, doing so in 43% of all cases, while consultant anaesthetists were more likely to overestimate (60% of all operations). Twelve patients (7%) had underestimation of blood loss of more than 500 mL by both surgeon and anaesthetist. Thirty per cent (n = 6\\/20) of patients requiring transfusion of a blood product within 24 hours of surgery had blood loss underestimated by more than 500 mL by both surgeon and anaesthetist. There was no significant difference in prediction between patients on anti-platelet or anticoagulation therapy preoperatively and those not on the said therapies. Conclusion Predicted intra-operative blood loss was within 500 mL of measured blood loss in 89% of operations. In 30% of patients who ultimately receive a blood transfusion, both the surgeon and anaesthetist significantly underestimate

  17. Are predictive equations for estimating resting energy expenditure accurate in Asian Indian male weightlifters?

    Directory of Open Access Journals (Sweden)

    Mini Joseph

    2017-01-01

    Full Text Available Background: The accuracy of existing predictive equations to determine the resting energy expenditure (REE of professional weightlifters remains scarcely studied. Our study aimed at assessing the REE of male Asian Indian weightlifters with indirect calorimetry and to compare the measured REE (mREE with published equations. A new equation using potential anthropometric variables to predict REE was also evaluated. Materials and Methods: REE was measured on 30 male professional weightlifters aged between 17 and 28 years using indirect calorimetry and compared with the eight formulas predicted by Harris–Benedicts, Mifflin-St. Jeor, FAO/WHO/UNU, ICMR, Cunninghams, Owen, Katch-McArdle, and Nelson. Pearson correlation coefficient, intraclass correlation coefficient, and multiple linear regression analysis were carried out to study the agreement between the different methods, association with anthropometric variables, and to formulate a new prediction equation for this population. Results: Pearson correlation coefficients between mREE and the anthropometric variables showed positive significance with suprailiac skinfold thickness, lean body mass (LBM, waist circumference, hip circumference, bone mineral mass, and body mass. All eight predictive equations underestimated the REE of the weightlifters when compared with the mREE. The highest mean difference was 636 kcal/day (Owen, 1986 and the lowest difference was 375 kcal/day (Cunninghams, 1980. Multiple linear regression done stepwise showed that LBM was the only significant determinant of REE in this group of sportspersons. A new equation using LBM as the independent variable for calculating REE was computed. REE for weightlifters = −164.065 + 0.039 (LBM (confidence interval −1122.984, 794.854]. This new equation reduced the mean difference with mREE by 2.36 + 369.15 kcal/day (standard error = 67.40. Conclusion: The significant finding of this study was that all the prediction equations

  18. FATHMM-XF: accurate prediction of pathogenic point mutations via extended features.

    Science.gov (United States)

    Rogers, Mark F; Shihab, Hashem A; Mort, Matthew; Cooper, David N; Gaunt, Tom R; Campbell, Colin

    2018-02-01

    We present FATHMM-XF, a method for predicting pathogenic point mutations in the human genome. Drawing on an extensive feature set, FATHMM-XF outperforms competitors on benchmark tests, particularly in non-coding regions where the majority of pathogenic mutations are likely to be found. The FATHMM-XF web server is available at http://fathmm.biocompute.org.uk/fathmm-xf/, and as tracks on the Genome Tolerance Browser: http://gtb.biocompute.org.uk. Predictions are provided for human genome version GRCh37/hg19. The data used for this project can be downloaded from: http://fathmm.biocompute.org.uk/fathmm-xf/. mark.rogers@bristol.ac.uk or c.campbell@bristol.ac.uk. Supplementary data are available at Bioinformatics online.

  19. Using an Allometric Equation to Accurately Predict the Energy Expenditure of Children and Adolescents With Nonalcoholic Fatty Liver Disease.

    Science.gov (United States)

    Martincevic, Inez; Mouzaki, Marialena

    2017-03-01

    Pediatric patients with nonalcoholic fatty liver disease (NAFLD) require targeted nutrition therapy that relies on calculating energy needs. Common energy equations are inaccurate in predicting resting energy expenditure (REE), influencing total energy expenditure (TEE) estimates. Equations based on allometric scaling are simple, accurate, void of subjective activity and/or stress factor bias, and they estimate TEE. To investigate the predictive accuracy of an allometric energy equation (AEE) in predicting TEE of children and adolescents with NAFLD. Retrospective study performed in a single institution. The allometric equation was used to calculate AEE, and the results were compared with TEE calculated using indirect calorimetry data (measured REE) multiplied by an activity factor (AF) of 1.5 or 1.7. Fifty-six patients with a mean age of 13 years were included in this study. The agreement between TEE (using an AF of 1.5) and AEE was -96 kcal/d (confidence interval, -29 to 221). The predictive accuracy of the allometric equation was not different between obese and nonobese patients. Allometric equations allow for accurate estimation of TEE in children with NAFLD.

  20. Ability to predict repetitions to momentary failure is not perfectly accurate, though improves with resistance training experience

    Directory of Open Access Journals (Sweden)

    James Steele

    2017-11-01

    Full Text Available ‘Repetitions in Reserve’ (RIR scales in resistance training (RT are used to control effort but assume people accurately predict performance a priori (i.e. the number of possible repetitions to momentary failure (MF. This study examined the ability of trainees with different experience levels to predict number of repetitions to MF. One hundred and forty-one participants underwent a full body RT session involving single sets to MF and were asked to predict the number of repetitions they could complete before reaching MF on each exercise. Participants underpredicted the number of repetitions they could perform to MF (Standard error of measurements [95% confidence intervals] for combined sample ranged between 2.64 [2.36–2.99] and 3.38 [3.02–3.83]. There was a tendency towards improved accuracy with greater experience. Ability to predict repetitions to MF is not perfectly accurate among most trainees though may improve with experience. Thus, RIR should be used cautiously in prescription of RT. Trainers and trainees should be aware of this as it may have implications for the attainment of training goals, particularly muscular hypertrophy.

  1. Ability to predict repetitions to momentary failure is not perfectly accurate, though improves with resistance training experience

    Science.gov (United States)

    Endres, Andreas; Fisher, James; Gentil, Paulo; Giessing, Jürgen

    2017-01-01

    ‘Repetitions in Reserve’ (RIR) scales in resistance training (RT) are used to control effort but assume people accurately predict performance a priori (i.e. the number of possible repetitions to momentary failure (MF)). This study examined the ability of trainees with different experience levels to predict number of repetitions to MF. One hundred and forty-one participants underwent a full body RT session involving single sets to MF and were asked to predict the number of repetitions they could complete before reaching MF on each exercise. Participants underpredicted the number of repetitions they could perform to MF (Standard error of measurements [95% confidence intervals] for combined sample ranged between 2.64 [2.36–2.99] and 3.38 [3.02–3.83]). There was a tendency towards improved accuracy with greater experience. Ability to predict repetitions to MF is not perfectly accurate among most trainees though may improve with experience. Thus, RIR should be used cautiously in prescription of RT. Trainers and trainees should be aware of this as it may have implications for the attainment of training goals, particularly muscular hypertrophy. PMID:29204323

  2. FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

    Directory of Open Access Journals (Sweden)

    Yasser El-Manzalawy

    Full Text Available A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles. Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein

  3. Accurate Stabilities of Laccase Mutants Predicted with a Modified FoldX Protocol

    DEFF Research Database (Denmark)

    Christensen, Niels Johan; Kepp, Kasper Planeta

    2012-01-01

    Fungal laccases are multi-copper enzymes of industrial importance due to their high stability, multi-functionality, and oxidizing power. This paper reports computational protocols that quantify the relative stability (∆∆G of folding) of mutants of high-redox-potential laccases (TvLIIIb and PM1L) ...... forces governing the high stability of fungal laccases, most notably the hydrophobic and Van der Waal's interactions in the folded state, which provide most of the predictive power....

  4. Geriatric nutritional risk index accurately predicts cardiovascular mortality in incident hemodialysis patients.

    Science.gov (United States)

    Takahashi, Hiroshi; Ito, Yasuhiko; Ishii, Hideki; Aoyama, Toru; Kamoi, Daisuke; Kasuga, Hirotake; Yasuda, Kaoru; Maruyama, Shoichi; Matsuo, Seiichi; Murohara, Toyoaki; Yuzawa, Yukio

    2014-07-01

    Cardiovascular disease (CVD) is a leading cause of death in end-stage renal disease (ESRD) patients. Protein-energy wasting (PEW) or malnutrition is common in this population, and is associated with increasing risk of mortality. The geriatric nutritional risk index (GNRI) has been developed as a tool to assess the nutritional risk, and is associated with mortality not only in elderly patients but also in ESRD patients. However, whether the GNRI could predict the mortality due to CVD remains unclear in this population. We investigated the prognostic value of GNRI at initiation of hemodialysis (HD) therapy for CVD mortality in a large cohort of ESRD patients. Serum albumin, body weight, and height for calculating GNRI were measured in 1568 ESRD patients. Thereafter, the patients were divided into quartiles according to GNRI levels [quartile 1 (Q1): 97.3], and were followed up for up to 10 years. GNRI levels independently correlated with serum C-reactive-protein levels (β = -0.126, p index was also greater in an established CVD risk model with GNRI (0.749) compared to that with albumin (0.730), body mass index (0.732), and alone (0.710). Similar results were observed for all-cause mortality. GNRI at initiation of HD therapy could predict CVD mortality with incremental value of the predictability compared to serum albumin and body mass index in ESRD patients. Copyright © 2013 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

  5. How accurate is Density Functional Theory in Predicting Reaction Energies Relevant to Phase Stability?

    Science.gov (United States)

    Hautier, Geoffroy; Ong, Shyue Ping; Jain, Anubhav; Moore, Charles J.; Ceder, Gerbrand

    2012-02-01

    Density Functional Theory (DFT) computations can be used to build computational phase diagrams that are used to understand the stability of known phases but also to assess the stability of novel, predicted compounds. The quality and predictive power of those phase diagrams rely on the accuracy of DFT in modeling reaction energies and we will present in this talk the results of a large scale comparison between experimentally measured and DFT computed reaction energies. For starters, we will show that only certain reaction energies are directly relevant to phase stability of multicomponent systems and that very often those reaction energies are not the commonly studied reactions from the elements. Using data from different experimental thermochemical tables and DFT high-throughput computing, we will present the results of a statistical study based on more than 130 reaction energies relevant to phase stability and from binary oxides to ternary oxides. We will show that the typical error are around 30 meV/at and therefore an order of magnitude lower than the errors in reaction energies from the elements. Finally, we will discuss the broad implications of our results on the evaluation of ab initio phase diagrams and on the computational prediction of new solid phases.

  6. Deconstructing environmental predictability: seasonality, environmental colour and the biogeography of marine life histories.

    Science.gov (United States)

    Marshall, Dustin J; Burgess, Scott C

    2015-02-01

    Environmental predictability is predicted to shape the evolution of life histories. Two key types of environmental predictability, seasonality and environmental colour, may influence life-history evolution independently but formal considerations of both and how they relate to life history are exceedingly rare. Here, in a global biogeographical analysis of over 800 marine invertebrates, we explore the relationships between both forms of environmental predictability and three fundamental life-history traits: location of larval development (aplanktonic vs. planktonic), larval developmental mode (feeding vs. non-feeding) and offspring size. We found that both dispersal potential and offspring size related to environmental predictability, but the relationships depended on both the environmental factor as well as the type of predictability. Environments that were more seasonal in food availability had a higher prevalence of species with a planktonic larval stage. Future studies should consider both types of environmental predictability as each can strongly affect life-history evolution. © 2014 John Wiley & Sons Ltd/CNRS.

  7. Mini-Mental Status Examination: a short form of MMSE was as accurate as the original MMSE in predicting dementia

    DEFF Research Database (Denmark)

    Schultz-Larsen, Kirsten; Lomholt, Rikke Kirstine; Kreiner, Svend

    2006-01-01

    as the original MMSE in predicting dementia. STUDY DESIGN AND SETTING: A population-based post hoc examination of the performance characteristics of the MMSE for detecting dementia in an existing data set of 243 elderly persons. RESULTS: Sensitivity, specificity, and predictive values were computed.......4%), and positive predictive value (71.0%) but equal area under the receiver operating characteristic curve. Cross-validation on follow-up data confirmed the results. CONCLUSION: A short, valid MMSE, which is as sensitive and specific as the original MMSE for the screening of cognitive impairments and dementia......OBJECTIVES: This study assesses the properties of the Mini-Mental State Examination (MMSE) with the purpose of improving the efficiencies of the methods of screening for cognitive impairment and dementia. A specific purpose was to determine whether an abbreviated version would be as accurate...

  8. Accurate cut-offs for predicting endoscopic activity and mucosal healing in Crohn's disease with fecal calprotectin

    Directory of Open Access Journals (Sweden)

    Juan María Vázquez-Morón

    Full Text Available Background: Fecal biomarkers, especially fecal calprotectin, are useful for predicting endoscopic activity in Crohn's disease; however, the cut-off point remains unclear. The aim of this paper was to analyze whether faecal calprotectin and M2 pyruvate kinase are good tools for generating highly accurate scores for the prediction of the state of endoscopic activity and mucosal healing. Methods: The simple endoscopic score for Crohn's disease and the Crohn's disease activity index was calculated for 71 patients diagnosed with Crohn's. Fecal calprotectin and M2-PK were measured by the enzyme-linked immunosorbent assay test. Results: A fecal calprotectin cut-off concentration of ≥ 170 µg/g (sensitivity 77.6%, specificity 95.5% and likelihood ratio +17.06 predicts a high probability of endoscopic activity, and a fecal calprotectin cut-off of ≤ 71 µg/g (sensitivity 95.9%, specificity 52.3% and likelihood ratio -0.08 predicts a high probability of mucosal healing. Three clinical groups were identified according to the data obtained: endoscopic activity (calprotectin ≥ 170, mucosal healing (calprotectin ≤ 71 and uncertainty (71 > calprotectin < 170, with significant differences in endoscopic values (F = 26.407, p < 0.01. Clinical activity or remission modified the probabilities of presenting endoscopic activity (100% vs 89% or mucosal healing (75% vs 87% in the diagnostic scores generated. M2-PK was insufficiently accurate to determine scores. Conclusions: The highly accurate scores for fecal calprotectin provide a useful tool for interpreting the probabilities of presenting endoscopic activity or mucosal healing, and are valuable in the specific clinical context.

  9. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons.

    Science.gov (United States)

    Oyeyemi, Victor B; Krisiloff, David B; Keith, John A; Libisch, Florian; Pavone, Michele; Carter, Emily A

    2014-01-28

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  10. Can magnetic resonance imaging accurately predict concordant pain provocation during provocative disc injection?

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Chang Ho; Kim, Yun Hwan; Kim, Jung Hyuk; Chung, Kyoo Byung; Sung, Deuk Jae [Korea University Anam Hospital, Korea University College of Medicine, Department of Radiology, Seoul (Korea); Lee, Sang-Heon [Korea University Anam Hospital, Korea University College of Medicine, Department of Physical Medicine and Rehabilitation, Seoul (Korea); Derby, Richard [Spinal Diagnostics and Treatment Center, Daly City, CA (United States); Stanford University Medical Center, Division of Physical Medicine and Rehabilitation, Stanford, CA (United States)

    2009-09-15

    To correlate magnetic resonance (MR) image findings with pain response by provocation discography in patients with discogenic low back pain, with an emphasis on the combination analysis of a high intensity zone (HIZ) and disc contour abnormalities. Sixty-two patients (aged 17-68 years) with axial low back pain that was likely to be disc related underwent lumbar discography (178 discs tested). The MR images were evaluated for disc degeneration, disc contour abnormalities, HIZ, and endplate abnormalities. Based on the combination of an HIZ and disc contour abnormalities, four classes were determined: (1) normal or bulging disc without HIZ; (2) normal or bulging disc with HIZ; (3) disc protrusion without HIZ; (4) disc protrusion with HIZ. These MR image findings and a new combined MR classification were analyzed in the base of concordant pain determined by discography. Disc protrusion with HIZ [sensitivity 45.5%; specificity 97.8%; positive predictive value (PPV), 87.0%] correlated significantly with concordant pain provocation (P < 0.01). A normal or bulging disc with HIZ was not associated with reproduction of pain. Disc degeneration (sensitivity 95.4%; specificity 38.8%; PPV 33.9%), disc protrusion (sensitivity 68.2%; specificity 80.6%; PPV 53.6%), and HIZ (sensitivity 56.8%; specificity 83.6%; PPV 53.2%) were not helpful in the identification of a disc with concordant pain. The proposed MR classification is useful to predict a disc with concordant pain. Disc protrusion with HIZ on MR imaging predicted positive discography in patients with discogenic low back pain. (orig.)

  11. Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer.

    Science.gov (United States)

    Ghandehari, Masoud; Emig, Thorsten; Aghamohamadnia, Milad

    2018-02-02

    Despite decades of research seeking to derive the urban energy budget, the dynamics of thermal exchange in the densely constructed environment is not yet well understood. Using New York City as a study site, we present a novel hybrid experimental-computational approach for a better understanding of the radiative heat transfer in complex urban environments. The aim of this work is to contribute to the calculation of the urban energy budget, particularly the stored energy. We will focus our attention on surface thermal radiation. Improved understanding of urban thermodynamics incorporating the interaction of various bodies, particularly in high rise cities, will have implications on energy conservation at the building scale, and for human health and comfort at the urban scale. The platform presented is based on longwave hyperspectral imaging of nearly 100 blocks of Manhattan, in addition to a geospatial radiosity model that describes the collective radiative heat exchange between multiple buildings. Despite assumptions in surface emissivity and thermal conductivity of buildings walls, the close comparison of temperatures derived from measurements and computations is promising. Results imply that the presented geospatial thermodynamic model of urban structures can enable accurate and high resolution analysis of instantaneous urban surface temperatures.

  12. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach.

    Directory of Open Access Journals (Sweden)

    Zhiheng Wang

    Full Text Available The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database.The DisoMCS is available at http://cal.tongji.edu.cn/disorder/.

  13. Heat capacities of xenotime-type ceramics: An accurate ab initio prediction

    Science.gov (United States)

    Ji, Yaqi; Beridze, George; Bosbach, Dirk; Kowalski, Piotr M.

    2017-10-01

    Because of ability to incorporate actinides into their structure, the lanthanide phosphate ceramics (LnPO4) are considered as potential matrices for the disposal of nuclear waste. Here we present highly reliable ab initio prediction of the variation of heat capacities and the standard entropies of these compounds in zircon structure along lanthanide series (Ln = Dy, …,Lu) and validate them against the existing experimental data. These data are helpful for assessment of thermodynamic parameters of these materials in the context of using them as matrices for immobilization of radionuclides for the purpose of nuclear waste management.

  14. Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

    Science.gov (United States)

    Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

    2018-01-05

    Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

  15. PSI: a comprehensive and integrative approach for accurate plant subcellular localization prediction.

    Directory of Open Access Journals (Sweden)

    Lili Liu

    Full Text Available Predicting the subcellular localization of proteins conquers the major drawbacks of high-throughput localization experiments that are costly and time-consuming. However, current subcellular localization predictors are limited in scope and accuracy. In particular, most predictors perform well on certain locations or with certain data sets while poorly on others. Here, we present PSI, a novel high accuracy web server for plant subcellular localization prediction. PSI derives the wisdom of multiple specialized predictors via a joint-approach of group decision making strategy and machine learning methods to give an integrated best result. The overall accuracy obtained (up to 93.4% was higher than best individual (CELLO by ~10.7%. The precision of each predicable subcellular location (more than 80% far exceeds that of the individual predictors. It can also deal with multi-localization proteins. PSI is expected to be a powerful tool in protein location engineering as well as in plant sciences, while the strategy employed could be applied to other integrative problems. A user-friendly web server, PSI, has been developed for free access at http://bis.zju.edu.cn/psi/.

  16. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences.

    Science.gov (United States)

    Chen, Peng; Li, Jinyan; Wong, Limsoon; Kuwahara, Hiroyuki; Huang, Jianhua Z; Gao, Xin

    2013-08-01

    Hot spot residues of proteins are fundamental interface residues that help proteins perform their functions. Detecting hot spots by experimental methods is costly and time-consuming. Sequential and structural information has been widely used in the computational prediction of hot spots. However, structural information is not always available. In this article, we investigated the problem of identifying hot spots using only physicochemical characteristics extracted from amino acid sequences. We first extracted 132 relatively independent physicochemical features from a set of the 544 properties in AAindex1, an amino acid index database. Each feature was utilized to train a classification model with a novel encoding schema for hot spot prediction by the IBk algorithm, an extension of the K-nearest neighbor algorithm. The combinations of the individual classifiers were explored and the classifiers that appeared frequently in the top performing combinations were selected. The hot spot predictor was built based on an ensemble of these classifiers and to work in a voting manner. Experimental results demonstrated that our method effectively exploited the feature space and allowed flexible weights of features for different queries. On the commonly used hot spot benchmark sets, our method significantly outperformed other machine learning algorithms and state-of-the-art hot spot predictors. The program is available at http://sfb.kaust.edu.sa/pages/software.aspx. Copyright © 2013 Wiley Periodicals, Inc.

  17. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences

    KAUST Repository

    Chen, Peng

    2013-07-23

    Hot spot residues of proteins are fundamental interface residues that help proteins perform their functions. Detecting hot spots by experimental methods is costly and time-consuming. Sequential and structural information has been widely used in the computational prediction of hot spots. However, structural information is not always available. In this article, we investigated the problem of identifying hot spots using only physicochemical characteristics extracted from amino acid sequences. We first extracted 132 relatively independent physicochemical features from a set of the 544 properties in AAindex1, an amino acid index database. Each feature was utilized to train a classification model with a novel encoding schema for hot spot prediction by the IBk algorithm, an extension of the K-nearest neighbor algorithm. The combinations of the individual classifiers were explored and the classifiers that appeared frequently in the top performing combinations were selected. The hot spot predictor was built based on an ensemble of these classifiers and to work in a voting manner. Experimental results demonstrated that our method effectively exploited the feature space and allowed flexible weights of features for different queries. On the commonly used hot spot benchmark sets, our method significantly outperformed other machine learning algorithms and state-of-the-art hot spot predictors. The program is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013 Wiley Periodicals, Inc.

  18. Size matters. The width and location of a ureteral stone accurately predict the chance of spontaneous passage

    Energy Technology Data Exchange (ETDEWEB)

    Jendeberg, Johan; Geijer, Haakan; Alshamari, Muhammed; Liden, Mats [Oerebro University Hospital, Department of Radiology, Faculty of Medicine and Health, Oerebro (Sweden); Cierzniak, Bartosz [Oerebro University, Department of Surgery, Faculty of Medicine and Health, Oerebro (Sweden)

    2017-11-15

    To determine how to most accurately predict the chance of spontaneous passage of a ureteral stone using information in the diagnostic non-enhanced computed tomography (NECT) and to create predictive models with smaller stone size intervals than previously possible. Retrospectively 392 consecutive patients with ureteric stone on NECT were included. Three radiologists independently measured the stone size. Stone location, side, hydronephrosis, CRP, medical expulsion therapy (MET) and all follow-up radiology until stone expulsion or 26 weeks were recorded. Logistic regressions were performed with spontaneous stone passage in 4 weeks and 20 weeks as the dependent variable. The spontaneous passage rate in 20 weeks was 312 out of 392 stones, 98% in 0-2 mm, 98% in 3 mm, 81% in 4 mm, 65% in 5 mm, 33% in 6 mm and 9% in ≥6.5 mm wide stones. The stone size and location predicted spontaneous ureteric stone passage. The side and the grade of hydronephrosis only predicted stone passage in specific subgroups. Spontaneous passage of a ureteral stone can be predicted with high accuracy with the information available in the NECT. We present a prediction method based on stone size and location. (orig.)

  19. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  20. Accurate prediction of thermodynamic properties of alkyl peroxides by combining density functional theory calculation with least-square calibration.

    Science.gov (United States)

    Liu, Cun-Xi; Li, Ze-Rong; Zhou, Chong-Wen; Li, Xiang-Yuan

    2009-05-01

    Owing to the significance in kinetic modeling of the oxidation and combustion mechanisms of hydrocarbons, a fast and relatively accurate method was developed for the prediction of Delta(f)H(298)(o) of alkyl peroxides. By this method, a raw Delta(f)H(298)(o) value was calculated from the optimized geometry and vibration frequencies at B3LYP/6-31G(d,p) level and then an accurate Delta(f)H(298)(o) value was obtained by a least-square procedure. The least-square procedure is a six-parameter linear equation and is validated by a leave-one out technique, giving a cross-validation squared correlation coefficient q(2) of 0.97 and a squared correlation coefficient of 0.98 for the final model. Calculated results demonstrated that the least-square calibration leads to a remarkable reduction of error and to the accurate Delta(f)H(298)(o) values within the chemical accuracy of 8 kJ mol(-1) except (CH(3))(2)CHCH(2)CH(2)CH(2)OOH which has an error of 8.69 kJ mol(-1). Comparison of the results by CBS-Q, CBS-QB3, G2, and G3 revealed that B3LYP/6-31G(d,p) in combination with a least-square calibration is reliable in the accurate prediction of the standard enthalpies of formation for alkyl peroxides. Standard entropies at 298 K and heat capacities in the temperature range of 300-1500 K for alkyl peroxides were also calculated using the rigid rotor-harmonic oscillator approximation. 2008 Wiley Periodicals, Inc.

  1. Predicting accurate absolute binding energies in aqueous solution: thermodynamic considerations for electronic structure methods.

    Science.gov (United States)

    Jensen, Jan H

    2015-05-21

    Recent predictions of absolute binding free energies of host-guest complexes in aqueous solution using electronic structure theory have been encouraging for some systems, while other systems remain problematic. In this paper I summarize some of the many factors that could easily contribute 1-3 kcal mol(-1) errors at 298 K: three-body dispersion effects, molecular symmetry, anharmonicity, spurious imaginary frequencies, insufficient conformational sampling, wrong or changing ionization states, errors in the solvation free energy of ions, and explicit solvent (and ion) effects that are not well-represented by continuum models. While I focus on binding free energies in aqueous solution the approach also applies (with minor adjustments) to any free energy difference such as conformational or reaction free energy differences or activation free energies in any solvent.

  2. Method for accurate shape prediction of 3D structure fabricated by x-ray lithography

    Science.gov (United States)

    Horade, Mitsuhiro; Khumpuang, Sommawan; Sugiyama, Susumu

    2005-02-01

    The paper describes about a useful study on the deformed shapes of microstructures fabricated by PCT (Plane-pattern to Cross-section Transfer) Technique. Previously, we have introduced the PCT technique as an additional process to conventional X-ray lithography for an extension of 2.5-dimensional structure to 3-dimensional structure. The PMMA (poly-methylmethacrylate) has been used as the X-ray resist. So far, microneedle and microlens arrays have been successfully fabricated in various shapes and dimensions. The production cost of X-ray mask has been known as the most expensive process for LIGA step, therefore, to predict the resulting shapes of structure precisely before fabricating the mask is relatively important. Although, the 2-D pattern on the X-ray mask can form a similar shape resulting in 3-D structure, the distorted shapes of microstructures have been observed. A linear-edged pattern on the X-ray mask resulted as an exponential-edged structure and an exponential-edged pattern resulted as an exceeding curvature, for example. This problem causes a change in the functional property of the array. In the case of our microneedle array, the linear-edge is highly required since it increases the strength of microneedle. We have investigated and suggested a calculation method fir a shape-prediction of microstructure fabricated by PCT technique in this work. The compensation calculation by our theories for an X-ray mask design can solve the undesired shape resulting after X-ray exposure. Moreover, the dosage control and suitable developing time are given in order to see through the current condition of the currently used synchrotron radiation light-source.

  3. Polarizable charge equilibration model for predicting accurate electrostatic interactions in molecules and solids

    Science.gov (United States)

    Naserifar, Saber; Brooks, Daniel J.; Goddard, William A.; Cvicek, Vaclav

    2017-03-01

    Electrostatic interactions play a critical role in determining the properties, structures, and dynamics of chemical, biochemical, and material systems. These interactions are described well at the level of quantum mechanics (QM) but not so well for the various models used in force field simulations of these systems. We propose and validate a new general methodology, denoted PQEq, to predict rapidly and dynamically the atomic charges and polarization underlying the electrostatic interactions. Here the polarization is described using an atomic sized Gaussian shaped electron density that can polarize away from the core in response to internal and external electric fields, while at the same time adjusting the charge on each core (described as a Gaussian function) so as to achieve a constant chemical potential across all atoms of the system. The parameters for PQEq are derived from experimental atomic properties of all elements up to Nobelium (atomic no. = 102). We validate PQEq by comparing to QM interaction energy as probe dipoles are brought along various directions up to 30 molecules containing H, C, N, O, F, Si, P, S, and Cl atoms. We find that PQEq predicts interaction energies in excellent agreement with QM, much better than other common charge models such as obtained from QM using Mulliken or ESP charges and those from standard force fields (OPLS and AMBER). Since PQEq increases the accuracy of electrostatic interactions and the response to external electric fields, we expect that PQEq will be useful for a large range of applications including ligand docking to proteins, catalytic reactions, electrocatalysis, ferroelectrics, and growth of ceramics and films, where it could be incorporated into standard force fields as OPLS, AMBER, CHARMM, Dreiding, ReaxFF, and UFF.

  4. The antenatal urinary tract dilation classification system accurately predicts severity of kidney and urinary tract abnormalities.

    Science.gov (United States)

    Kaspar, C D W; Lo, M; Bunchman, T E; Xiao, N

    2017-10-01

    Urinary tract dilation (UTD) is a commonly diagnosed prenatal condition; however, it is currently unknown which features lead to benign and resolving or pathologic abnormalities. A consensus UTD classification system (antenatal UTD classification, UTD-A) was created by Nguyen et al. in 2014 [1], but has not yet been validated. To evaluate the ability of the UTD-A system to identify kidney and urinary tract (KUT) abnormalities, assess whether UTD-A can predict severity of KUT conditions, and perform a cost analysis of screening ultrasound (US). A retrospective single-center study was conducted at an academic medical center. Inclusion criteria were: neonates in the well or sick nursery who had a complete abdominal or limited renal US performed in the first 30 days of life between January 01, 2011 and December 31, 2013. Data were collected on prenatal US characteristics from which UTD-A classification was retrospectively applied, and postnatal data were collected up to 2 years following birth. A total of 203 patients were identified. Of the 36 abnormal postnatal KUT diagnoses, 90% were identified prenatally as UTD A1 or UTD A2-3. The remaining 10% developed postnatal KUT abnormalities due to myelomeningocele, such as VUR or UTD, which were not evident prenatally. Overall sensitivity and specificity of the UTD-A system was 0.767 (95% CI 0.577, 0.901) and 0.836 (95% CI 0.758, 0.897), respectively, when resolved UTD was counted as a normal diagnosis. Postnatal diagnoses differed by UTD-A classification as shown in the Summary fig. Of all the obstructive uropathies, 90.9% occurred in the UTD A2-3 class and none occurred in UTD-A Normal. Rate of postnatally resolved UTD was significantly higher in the UTD A1 group (78%) compared with UTD A2-3 (31%) or UTD-A Normal (12%, all P system revealed important differences in the severity of UTD abnormalities. With repeated validation in larger cohorts, the UTD-A classification may be used to offer a prognosis for parents

  5. DrugECs: An Ensemble System with Feature Subspaces for Accurate Drug-Target Interaction Prediction

    Directory of Open Access Journals (Sweden)

    Jinjian Jiang

    2017-01-01

    Full Text Available Background. Drug-target interaction is key in drug discovery, especially in the design of new lead compound. However, the work to find a new lead compound for a specific target is complicated and hard, and it always leads to many mistakes. Therefore computational techniques are commonly adopted in drug design, which can save time and costs to a significant extent. Results. To address the issue, a new prediction system is proposed in this work to identify drug-target interaction. First, drug-target pairs are encoded with a fragment technique and the software “PaDEL-Descriptor.” The fragment technique is for encoding target proteins, which divides each protein sequence into several fragments in order and encodes each fragment with several physiochemical properties of amino acids. The software “PaDEL-Descriptor” creates encoding vectors for drug molecules. Second, the dataset of drug-target pairs is resampled and several overlapped subsets are obtained, which are then input into kNN (k-Nearest Neighbor classifier to build an ensemble system. Conclusion. Experimental results on the drug-target dataset showed that our method performs better and runs faster than the state-of-the-art predictors.

  6. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke, E-mail: ksheng@mednet.ucla.edu [Department of Radiation Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90024 (United States)

    2015-11-15

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.

  7. How Accurate Are the Anthropometry Equations in in Iranian Military Men in Predicting Body Composition?

    Science.gov (United States)

    Shakibaee, Abolfazl; Faghihzadeh, Soghrat; Alishiri, Gholam Hossein; Ebrahimpour, Zeynab; Faradjzadeh, Shahram; Sobhani, Vahid; Asgari, Alireza

    2015-12-01

    The body composition varies according to different life styles (i.e. intake calories and caloric expenditure). Therefore, it is wise to record military personnel's body composition periodically and encourage those who abide to the regulations. Different methods have been introduced for body composition assessment: invasive and non-invasive. Amongst them, the Jackson and Pollock equation is most popular. The recommended anthropometric prediction equations for assessing men's body composition were compared with dual-energy X-ray absorptiometry (DEXA) gold standard to develop a modified equation to assess body composition and obesity quantitatively among Iranian military men. A total of 101 military men aged 23 - 52 years old with a mean age of 35.5 years were recruited and evaluated in the present study (average height, 173.9 cm and weight, 81.5 kg). The body-fat percentages of subjects were assessed both with anthropometric assessment and DEXA scan. The data obtained from these two methods were then compared using multiple regression analysis. The mean and standard deviation of body fat percentage of the DEXA assessment was 21.2 ± 4.3 and body fat percentage obtained from three Jackson and Pollock 3-, 4- and 7-site equations were 21.1 ± 5.8, 22.2 ± 6.0 and 20.9 ± 5.7, respectively. There was a strong correlation between these three equations and DEXA (R² = 0.98). The mean percentage of body fat obtained from the three equations of Jackson and Pollock was very close to that of body fat obtained from DEXA; however, we suggest using a modified Jackson-Pollock 3-site equation for volunteer military men because the 3-site equation analysis method is simpler and faster than other methods.

  8. A Novel Fibrosis Index Comprising a Non-Cholesterol Sterol Accurately Predicts HCV-Related Liver Cirrhosis

    DEFF Research Database (Denmark)

    Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin

    2014-01-01

    Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim...... of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive...... significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred...

  9. Influence of ensemble geostatistics on production history matching and prediction at new wells

    NARCIS (Netherlands)

    Peters, E.; Leeuwenburgh, O.; Hanea, R.G.

    2008-01-01

    Automatic history matching techniques such as the Ensemble Kalman Filter (EnKF) have been shown to provide reliable results for matching and prediction at existing wells. It is much less clear if the prediction outside of existing wells improves as a result of history matching. The amount of

  10. Industrial Compositional Streamline Simulation for Efficient and Accurate Prediction of Gas Injection and WAG Processes

    Energy Technology Data Exchange (ETDEWEB)

    Margot Gerritsen

    2008-10-31

    Gas-injection processes are widely and increasingly used for enhanced oil recovery (EOR). In the United States, for example, EOR production by gas injection accounts for approximately 45% of total EOR production and has tripled since 1986. The understanding of the multiphase, multicomponent flow taking place in any displacement process is essential for successful design of gas-injection projects. Due to complex reservoir geometry, reservoir fluid properties and phase behavior, the design of accurate and efficient numerical simulations for the multiphase, multicomponent flow governing these processes is nontrivial. In this work, we developed, implemented and tested a streamline based solver for gas injection processes that is computationally very attractive: as compared to traditional Eulerian solvers in use by industry it computes solutions with a computational speed orders of magnitude higher and a comparable accuracy provided that cross-flow effects do not dominate. We contributed to the development of compositional streamline solvers in three significant ways: improvement of the overall framework allowing improved streamline coverage and partial streamline tracing, amongst others; parallelization of the streamline code, which significantly improves wall clock time; and development of new compositional solvers that can be implemented along streamlines as well as in existing Eulerian codes used by industry. We designed several novel ideas in the streamline framework. First, we developed an adaptive streamline coverage algorithm. Adding streamlines locally can reduce computational costs by concentrating computational efforts where needed, and reduce mapping errors. Adapting streamline coverage effectively controls mass balance errors that mostly result from the mapping from streamlines to pressure grid. We also introduced the concept of partial streamlines: streamlines that do not necessarily start and/or end at wells. This allows more efficient coverage and avoids

  11. Easy-to-use, general, and accurate multi-Kinect calibration and its application to gait monitoring for fall prediction.

    Science.gov (United States)

    Staranowicz, Aaron N; Ray, Christopher; Mariottini, Gian-Luca

    2015-01-01

    Falls are the most-common causes of unintentional injury and death in older adults. Many clinics, hospitals, and health-care providers are urgently seeking accurate, low-cost, and easy-to-use technology to predict falls before they happen, e.g., by monitoring the human walking pattern (or "gait"). Despite the wide popularity of Microsoft's Kinect and the plethora of solutions for gait monitoring, no strategy has been proposed to date to allow non-expert users to calibrate the cameras, which is essential to accurately fuse the body motion observed by each camera in a single frame of reference. In this paper, we present a novel multi-Kinect calibration algorithm that has advanced features when compared to existing methods: 1) is easy to use, 2) it can be used in any generic Kinect arrangement, and 3) it provides accurate calibration. Extensive real-world experiments have been conducted to validate our algorithm and to compare its performance against other multi-Kinect calibration approaches, especially to show the improved estimate of gait parameters. Finally, a MATLAB Toolbox has been made publicly available for the entire research community.

  12. Predictive value of clinical history compared with urodynamic study in 1,179 women

    Directory of Open Access Journals (Sweden)

    Jorge Milhem Haddad

    2016-02-01

    Full Text Available SUMMARY Objective: to determine the positive predictive value of clinical history in comparison with urodynamic study for the diagnosis of urinary incontinence. Methods: retrospective analysis comparing clinical history and urodynamic evaluation of 1,179 women with urinary incontinence. The urodynamic study was considered the gold standard, whereas the clinical history was the new test to be assessed. This was established after analyzing each method as the gold standard through the difference between their positive predictive values. Results: the positive predictive values of clinical history compared with urodynamic study for diagnosis of stress urinary incontinence, overactive bladder and mixed urinary incontinence were, respectively, 37% (95% CI 31-44, 40% (95% CI 33-47 and 16% (95% CI 14-19. Conclusion: we concluded that the positive predictive value of clinical history was low compared with urodynamic study for urinary incontinence diagnosis. The positive predictive value was low even among women with pure stress urinary incontinence.

  13. Predictive powertrain control using powertrain history and GPS data

    Science.gov (United States)

    Weslati, Feisel; Krupadanam, Ashish A

    2015-03-03

    A method and powertrain apparatus that predicts a route of travel for a vehicle and uses historical powertrain loads and speeds for the predicted route of travel to optimize at least one powertrain operation for the vehicle.

  14. New and Accurate Predictive Model for the Efficacy of Extracorporeal Shock Wave Therapy in Managing Patients With Chronic Plantar Fasciitis.

    Science.gov (United States)

    Yin, Mengchen; Chen, Ni; Huang, Quan; Marla, Anastasia Sulindro; Ma, Junming; Ye, Jie; Mo, Wen

    2017-12-01

    index was .4243, .3003, and .7189, respectively. The Hosmer-Lemeshow test showed a good fitting of the predictive model, with an overall accuracy of 89.6%. This study establishes a new and accurate predictive model for the efficacy of ESWT in managing patients with chronic plantar fasciitis. The use of these parameters, in the form of a predictive model for ESWT efficacy, has the potential to improve decision-making in the application of ESWT. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  15. Non-isothermal kinetics model to predict accurate phase transformation and hardness of 22MnB5 boron steel

    Energy Technology Data Exchange (ETDEWEB)

    Bok, H.-H.; Kim, S.N.; Suh, D.W. [Graduate Institute of Ferrous Technology, POSTECH, San 31, Hyoja-dong, Nam-gu, Pohang, Gyeongsangbuk-do (Korea, Republic of); Barlat, F., E-mail: f.barlat@postech.ac.kr [Graduate Institute of Ferrous Technology, POSTECH, San 31, Hyoja-dong, Nam-gu, Pohang, Gyeongsangbuk-do (Korea, Republic of); Lee, M.-G., E-mail: myounglee@korea.ac.kr [Department of Materials Science and Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul (Korea, Republic of)

    2015-02-25

    A non-isothermal phase transformation kinetics model obtained by modifying the well-known JMAK approach is proposed for application to a low carbon boron steel (22MnB5) sheet. In the modified kinetics model, the parameters are functions of both temperature and cooling rate, and can be identified by a numerical optimization method. Moreover, in this approach the transformation start and finish temperatures are variable instead of the constants that depend on chemical composition. These variable reference temperatures are determined from the measured CCT diagram using dilatation experiments. The kinetics model developed in this work captures the complex transformation behavior of the boron steel sheet sample accurately. In particular, the predicted hardness and phase fractions in the specimens subjected to a wide range of cooling rates were validated by experiments.

  16. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael

    2015-01-01

    by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding...... with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped...... to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1....

  17. Effect of computational grid on accurate prediction of a wind turbine rotor using delayed detached-eddy simulations

    Energy Technology Data Exchange (ETDEWEB)

    Bangga, Galih; Weihing, Pascal; Lutz, Thorsten; Krämer, Ewald [University of Stuttgart, Stuttgart (Germany)

    2017-05-15

    The present study focuses on the impact of grid for accurate prediction of the MEXICO rotor under stalled conditions. Two different blade mesh topologies, O and C-H meshes, and two different grid resolutions are tested for several time step sizes. The simulations are carried out using Delayed detached-eddy simulation (DDES) with two eddy viscosity RANS turbulence models, namely Spalart- Allmaras (SA) and Menter Shear stress transport (SST) k-ω. A high order spatial discretization, WENO (Weighted essentially non- oscillatory) scheme, is used in these computations. The results are validated against measurement data with regards to the sectional loads and the chordwise pressure distributions. The C-H mesh topology is observed to give the best results employing the SST k-ω turbulence model, but the computational cost is more expensive as the grid contains a wake block that increases the number of cells.

  18. Total reference air kerma can accurately predict isodose surface volumes in cervix cancer brachytherapy. A multicenter study.

    Science.gov (United States)

    Nkiwane, Karen S; Andersen, Else; Champoudry, Jerome; de Leeuw, Astrid; Swamidas, Jamema; Lindegaard, Jacob; Pötter, Richard; Kirisits, Christian; Tanderup, Kari

    To demonstrate that V 60  Gy, V 75  Gy, and V 85  Gy isodose surface volumes can be accurately estimated from total reference air kerma (TRAK) in cervix cancer MRI-guided brachytherapy (BT). 60 Gy, 75 Gy, and 85 Gy isodose surface volumes levels were obtained from treatment planning systems (V TPS ) for 239 EMBRACE study patients from five institutions treated with various dose rates, fractionation schedules and applicators. An equation for estimating V TPS from TRAK was derived. Furthermore, a surrogate Point A dose (Point A*) was proposed and tested for correlation with V 75  Gy. Predicted volumes V pred  = 4965 (TRAK/dref) 3/2 + 170 (TRAK/dref) - 1.5 gave the best fit to V TPS . The difference between V TPS and predicted volumes was 0.0% ± 2.3%. All volumes were predicted within 10%. The prediction was valid for (1) high-dose rate and pulsed dose rate, (2) intracavitary vs. intracavitary/interstitial applicators, and (3) tandem-ring, tandem-ovoid, and mold. Point A* = 14 TRAK was converted to total EQD 2 and showed high correlation with V 75  Gy. TRAK derived Isodose surface volumes may become a tool for assessment of treatment intensity. Furthermore, surrogate Point A ∗ doses can be applied for both intracavitary and intracavitary/interstitial BT and can be used to compare treatments across fractionation schedules. Copyright © 2017 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

  19. A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

    Directory of Open Access Journals (Sweden)

    Magdalena Ydreborg

    Full Text Available Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI in the paper, was based on the model: Log-odds (predicting cirrhosis = -12.17+ (age × 0.11 + (BMI (kg/m(2 × 0.23 + (D7-lathosterol (μg/100 mg cholesterol×(-0.013 + (Platelet count (x10(9/L × (-0.018 + (Prothrombin-INR × 3.69. The area under the ROC curve (AUROC for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96. The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98. In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

  20. Analytical prediction of sub-surface thermal history in translucent tissue phantoms during plasmonic photo-thermotherapy (PPTT).

    Science.gov (United States)

    Dhar, Purbarun; Paul, Anup; Narasimhan, Arunn; Das, Sarit K

    2016-12-01

    Knowledge of thermal history and/or distribution in biological tissues during laser based hyperthermia is essential to achieve necrosis of tumour/carcinoma cells. A semi-analytical model to predict sub-surface thermal distribution in translucent, soft, tissue mimics has been proposed. The model can accurately predict the spatio-temporal temperature variations along depth and the anomalous thermal behaviour in such media, viz. occurrence of sub-surface temperature peaks. Based on optical and thermal properties, the augmented temperature and shift of the peak positions in case of gold nanostructure mediated tissue phantom hyperthermia can be predicted. Employing inverse approach, the absorption coefficient of nano-graphene infused tissue mimics is determined from the peak temperature and found to provide appreciably accurate predictions along depth. Furthermore, a simplistic, dimensionally consistent correlation to theoretically determine the position of the peak in such media is proposed and found to be consistent with experiments and computations. The model shows promise in predicting thermal distribution induced by lasers in tissues and deduction of therapeutic hyperthermia parameters, thereby assisting clinical procedures by providing a priori estimates. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Predicting suitable optoelectronic properties of monoclinic VON semiconductor crystals for photovoltaics using accurate first-principles computations

    KAUST Repository

    Harb, Moussab

    2015-08-26

    Using accurate first-principles quantum calculations based on DFT (including the perturbation theory DFPT) with the range-separated hybrid HSE06 exchange-correlation functional, we predict essential fundamental properties (such as bandgap, optical absorption coefficient, dielectric constant, charge carrier effective masses and exciton binding energy) of two stable monoclinic vanadium oxynitride (VON) semiconductor crystals for solar energy conversion applications. In addition to the predicted band gaps in the optimal range for making single-junction solar cells, both polymorphs exhibit relatively high absorption efficiencies in the visible range, high dielectric constants, high charge carrier mobilities and much lower exciton binding energies than the thermal energy at room temperature. Moreover, their optical absorption, dielectric and exciton dissociation properties are found to be better than those obtained for semiconductors frequently utilized in photovoltaic devices like Si, CdTe and GaAs. These novel results offer a great opportunity for this stoichiometric VON material to be properly synthesized and considered as a new good candidate for photovoltaic applications.

  2. Predicting suitable optoelectronic properties of monoclinic VON semiconductor crystals for photovoltaics using accurate first-principles computations.

    Science.gov (United States)

    Harb, Moussab

    2015-10-14

    Using accurate first-principles quantum calculations based on DFT (including the DFPT) with the range-separated hybrid HSE06 exchange-correlation functional, we can predict the essential fundamental properties (such as bandgap, optical absorption co-efficient, dielectric constant, charge carrier effective masses and exciton binding energy) of two stable monoclinic vanadium oxynitride (VON) semiconductor crystals for solar energy conversion applications. In addition to the predicted band gaps in the optimal range for making single-junction solar cells, both polymorphs exhibit a relatively high absorption efficiency in the visible range, high dielectric constant, high charge carrier mobility and much lower exciton binding energy than the thermal energy at room temperature. Moreover, their optical absorption, dielectric and exciton dissociation properties were found to be better than those obtained for semiconductors frequently utilized in photovoltaic devices such as Si, CdTe and GaAs. These novel results offer a great opportunity for this stoichiometric VON material to be properly synthesized and considered as a new good candidate for photovoltaic applications.

  3. Accurate prediction of complex free surface flow around a high speed craft using a single-phase level set method

    Science.gov (United States)

    Broglia, Riccardo; Durante, Danilo

    2017-11-01

    This paper focuses on the analysis of a challenging free surface flow problem involving a surface vessel moving at high speeds, or planing. The investigation is performed using a general purpose high Reynolds free surface solver developed at CNR-INSEAN. The methodology is based on a second order finite volume discretization of the unsteady Reynolds-averaged Navier-Stokes equations (Di Mascio et al. in A second order Godunov—type scheme for naval hydrodynamics, Kluwer Academic/Plenum Publishers, Dordrecht, pp 253-261, 2001; Proceedings of 16th international offshore and polar engineering conference, San Francisco, CA, USA, 2006; J Mar Sci Technol 14:19-29, 2009); air/water interface dynamics is accurately modeled by a non standard level set approach (Di Mascio et al. in Comput Fluids 36(5):868-886, 2007a), known as the single-phase level set method. In this algorithm the governing equations are solved only in the water phase, whereas the numerical domain in the air phase is used for a suitable extension of the fluid dynamic variables. The level set function is used to track the free surface evolution; dynamic boundary conditions are enforced directly on the interface. This approach allows to accurately predict the evolution of the free surface even in the presence of violent breaking waves phenomena, maintaining the interface sharp, without any need to smear out the fluid properties across the two phases. This paper is aimed at the prediction of the complex free-surface flow field generated by a deep-V planing boat at medium and high Froude numbers (from 0.6 up to 1.2). In the present work, the planing hull is treated as a two-degree-of-freedom rigid object. Flow field is characterized by the presence of thin water sheets, several energetic breaking waves and plungings. The computational results include convergence of the trim angle, sinkage and resistance under grid refinement; high-quality experimental data are used for the purposes of validation, allowing to

  4. History and physical examination findings predictive of testicular torsion: an attempt to promote clinical diagnosis by house staff.

    Science.gov (United States)

    Srinivasan, Arun; Cinman, Nadya; Feber, Kevin M; Gitlin, Jordan; Palmer, Lane S

    2011-08-01

    To standardize the history and physical examination of boys who present with acute scrotum and identify parameters that best predict testicular torsion. Over a 5-month period, a standardized history and physical examination form with 22 items was used for all boys presenting with scrotal pain. Management decisions for radiological evaluation and surgical intervention were based on the results. Data were statistically analyzed in correlation with the eventual diagnosis. Of the 79 boys evaluated, 8 (10.1%) had testicular torsion. On univariate analysis, age, worsening pain, nausea/vomiting, severe pain at rest, absence of ipsilateral cremaster reflex, abnormal testicular position and scrotal skin changes were statistically predictive of torsion. After multivariate analysis and adjusting for confounding effect of other co-existing variables, absence of ipsilateral cremaster reflex (P predictive factors of testicular torsion. An accurate history and physical examination of boys with acute scrotum should be primary in deciding upon further radiographic or surgical evaluation. While several forces have led to less consistent overnight resident staffing, consistent and reliable clinical evaluation of the acute scrotum using a standardized approach should reduce error, improve patient care and potentially reduce health care costs. Copyright © 2011 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

  5. Predicting breast cancer risk: implications of a "weak" family history.

    Science.gov (United States)

    Anderson, Elaine; Berg, Jonathan; Black, Roger; Bradshaw, Nicola; Campbell, Joyce; Cetnarskyj, Roseanne; Drummond, Sarah; Davidson, Rosemarie; Dunlop, Jacqueline; Fordyce, Alison; Gibbons, Barbara; Goudie, David; Gregory, Helen; Hanning, Kirstie; Holloway, Susan; Longmuir, Mark; McLeish, Lorna; Murday, Vicky; Miedzybrodska, Zosia; Nicholson, Donna; Pearson, Pauline; Porteous, Mary; Reis, Marta; Slater, Sheila; Smith, Karen; Smyth, Elizabeth; Snadden, Lesley; Steel, Michael; Stirling, Diane; Watt, Cathy; Whyte, Catriona; Young, Dorothy

    2008-01-01

    Published guidelines adopted in many countries recommend that women whose family history of breast cancer places them at a risk>or=1.7 times that of the age-matched general population, should be considered for inclusion in special surveillance programmes. However validation of risk assessment models has been called for as a matter of urgency. The databases of the four Scottish Familial Breast Cancer clinics and the Scottish Cancer Registry have been searched to identify breast cancers occurring among 1,125 women aged 40-56, with family histories placing them below the "moderate" level of genetic risk. The observed incidence over 6 years was compared with age-specific data for the Scottish population. Our findings confirm that when there are two affected relatives (one first degree) the relative risk (RR) exceeds 1.7 regardless of their ages at diagnosis. When only one (first degree) relative was affected at any age from 40 to 55, the RR does not reach 1.7 if that relative was a mother but exceeds it if the relative was a sister. The probable explanation is that sisters are more likely than mother/daughter pairs to share homozygosity for a risk allele. Surveillance programmes might therefore accommodate sisters of women affected before age 55. Evidence that "low penetrance" alleles contributing to breast cancer risk may be recessive should be taken into account in strategies for identifying them.

  6. History of drug use predicts opioid treatment agreement violation.

    Science.gov (United States)

    Summers, Pamela; Alemu, Brook; Quidgley-Nevares, Antonio

    2015-01-01

    To determine reasons and describe characteristics of patients who violate their opioid treatment agreement. Cross-sectional retrospective study. New patients aged 18 years or above attending a multidisciplinary comprehensive pain management clinic from January 2012 to June 2012. Reason for discharge from the clinic. Of the 234 subjects in the study, 38.5 percent were discharged due to treatment agreement violation. A majority had a self-reported history of tobacco use, followed by alcohol and marijuana. The mean age of discharge was 45.1 years (SD 11.6) and they were discharged on average in 7.4 months after their first clinic visit. The primary reason for discharge was for an inappropriate urine drug screen (UDS) with illicit drug use being the most common at 40 percent and marijuana being the most common illicit drug. Subjects reporting a history of any drug use were nearly seven times more likely to be discharged. Hydrocodone was the most common nonprescribed opioid found in the UDS for those discharged for using nonprescribed opioids. Inappropriate UDS is a main factor for discharge due to violation of the opioid treatment agreement. Those with self-reported current or prior drug use were more likely to be discharged from the clinic.

  7. Do measures of surgical effectiveness at 1 year after lumbar spine surgery accurately predict 2-year outcomes?

    Science.gov (United States)

    Adogwa, Owoicho; Elsamadicy, Aladine A; Han, Jing L; Cheng, Joseph; Karikari, Isaac; Bagley, Carlos A

    2016-12-01

    OBJECTIVE With the recent passage of the Patient Protection and Affordable Care Act, there has been a dramatic shift toward critical analyses of quality and longitudinal assessment of subjective and objective outcomes after lumbar spine surgery. Accordingly, the emergence and routine use of real-world institutional registries have been vital to the longitudinal assessment of quality. However, prospectively obtaining longitudinal outcomes for patients at 24 months after spine surgery remains a challenge. The aim of this study was to assess if 12-month measures of treatment effectiveness accurately predict long-term outcomes (24 months). METHODS A nationwide, multiinstitutional, prospective spine outcomes registry was used for this study. Enrollment criteria included available demographic, surgical, and clinical outcomes data. All patients had prospectively collected outcomes measures and a minimum 2-year follow-up. Patient-reported outcomes instruments (Oswestry Disability Index [ODI], SF-36, and visual analog scale [VAS]-back pain/leg pain) were completed before surgery and then at 3, 6, 12, and 24 months after surgery. The Health Transition Index of the SF-36 was used to determine the 1- and 2-year minimum clinically important difference (MCID), and logistic regression modeling was performed to determine if achieving MCID at 1 year adequately predicted improvement and achievement of MCID at 24 months. RESULTS The study group included 969 patients: 300 patients underwent anterior lumbar interbody fusion (ALIF), 606 patients underwent transforaminal lumbar interbody fusion (TLIF), and 63 patients underwent lateral interbody fusion (LLIF). There was a significant correlation between the 12- and 24-month ODI (r = 0.82; p MCID thresholds for ODI at 12 months were 13-fold (p MCID at 24 months. Similarly, for the TLIF and LLIF cohorts, patients achieving MCID thresholds for ODI at 12 months were 13-fold and 14-fold (p MCID at 24 months. Outcome measures obtained at 12

  8. A composite score combining waist circumference and body mass index more accurately predicts body fat percentage in 6-to 13-year-old children

    NARCIS (Netherlands)

    Aeberli, I.; Gut-Knabenhans, M.; Kusche-Ammann, R.S.; Molinari, L.; Zimmermann, M.B.

    2013-01-01

    Body mass index (BMI) and waist circumference (WC) are widely used to predict % body fat (BF) and classify degrees of pediatric adiposity. However, both measures have limitations. The aim of this study was to evaluate whether a combination of WC and BMI would more accurately predict %BF than either

  9. Accurate prediction of immunogenic T-cell epitopes from epitope sequences using the genetic algorithm-based ensemble learning.

    Science.gov (United States)

    Zhang, Wen; Niu, Yanqing; Zou, Hua; Luo, Longqiang; Liu, Qianchao; Wu, Weijian

    2015-01-01

    T-cell epitopes play the important role in T-cell immune response, and they are critical components in the epitope-based vaccine design. Immunogenicity is the ability to trigger an immune response. The accurate prediction of immunogenic T-cell epitopes is significant for designing useful vaccines and understanding the immune system. In this paper, we attempt to differentiate immunogenic epitopes from non-immunogenic epitopes based on their primary structures. First of all, we explore a variety of sequence-derived features, and analyze their relationship with epitope immunogenicity. To effectively utilize various features, a genetic algorithm (GA)-based ensemble method is proposed to determine the optimal feature subset and develop the high-accuracy ensemble model. In the GA optimization, a chromosome is to represent a feature subset in the search space. For each feature subset, the selected features are utilized to construct the base predictors, and an ensemble model is developed by taking the average of outputs from base predictors. The objective of GA is to search for the optimal feature subset, which leads to the ensemble model with the best cross validation AUC (area under ROC curve) on the training set. Two datasets named 'IMMA2' and 'PAAQD' are adopted as the benchmark datasets. Compared with the state-of-the-art methods POPI, POPISK, PAAQD and our previous method, the GA-based ensemble method produces much better performances, achieving the AUC score of 0.846 on IMMA2 dataset and the AUC score of 0.829 on PAAQD dataset. The statistical analysis demonstrates the performance improvements of GA-based ensemble method are statistically significant. The proposed method is a promising tool for predicting the immunogenic epitopes. The source codes and datasets are available in S1 File.

  10. Sexual victimization history predicts academic performance in college women.

    Science.gov (United States)

    Baker, Majel R; Frazier, Patricia A; Greer, Christiaan; Paulsen, Jacob A; Howard, Kelli; Meredith, Liza N; Anders, Samantha L; Shallcross, Sandra L

    2016-11-01

    College women frequently report having experienced sexual victimization (SV) in their lifetime, including child sexual abuse and adolescent/adult sexual assault. Although the harmful mental health sequelae of SV have been extensively studied, recent research suggests that SV is also a risk factor for poorer college academic performance. The current studies examined whether exposure to SV uniquely predicted poorer college academic performance, even beyond contributions from three well-established predictors of academic performance: high school rank, composite standardized test scores (i.e., American College Testing [ACT]), and conscientiousness. Study 1 analyzed longitudinal data from a sample of female college students (N = 192) who were assessed at the beginning and end of one semester. SV predicted poorer cumulative end-of-semester grade point average (GPA) while controlling for well-established predictors of academic performance. Study 2 replicated these findings in a second longitudinal study of female college students (N = 390) and extended the analyses to include follow-up data on the freshmen and sophomore students (n = 206) 4 years later. SV predicted students' GPA in their final term at the university above the contributions of well-established academic predictors, and it was the only factor related to leaving college. These findings highlight the importance of expanding the scope of outcomes of SV to include academic performance, and they underscore the need to assess SV and other adverse experiences on college campuses to target students who may be at risk of poor performance or leaving college. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  11. Body mass index continues to accurately predict percent body fat as women age despite changes in muscle mass and height.

    Science.gov (United States)

    Ablove, Tova; Binkley, Neil; Leadley, Sarah; Shelton, James; Ablove, Robert

    2015-07-01

    Body mass index (BMI) is commonly used to predict obesity in clinical practice because it is suggested to closely correlate with percent body fat (%BF). With aging, women lose both lean mass and height. Because of this, many clinicians question whether BMI is an accurate predictor of obesity in aging women. In evaluating the equation for BMI (weight/height(2)), it is clear that both variables can have a dramatic effect on BMI calculation. We evaluated the relationship between BMI and %BF, as measured by dual-energy x-ray absorptiometry, in the setting of age-related changes in height loss and body composition in women. Our objective is to determine whether BMI continues to correlate with %BF as women age. Study participants were identified using data from five osteoporosis clinical trials, where healthy participants had full-body dual-energy x-ray absorptiometry scans. Deidentified data from 274 women aged between 35 and 95 years were evaluated. %BF, weight, age, tallest height, actual height, and appendicular lean mass were collected from all participants. BMI was calculated using the actual height and the tallest height of each study participant. %BF was compared with BMI and stratified for age. BMI calculated using the tallest height and BMI calculated using actual height both had strong correlations with %BF. Surprisingly, the effects of changes in height and lean body mass balance each other out in BMI calculation. There continues to be a strong correlation between BMI and %BF in adult women as they age.

  12. A rapid and accurate approach for prediction of interactomes from co-elution data (PrInCE).

    Science.gov (United States)

    Stacey, R Greg; Skinnider, Michael A; Scott, Nichollas E; Foster, Leonard J

    2017-10-23

    An organism's protein interactome, or complete network of protein-protein interactions, defines the protein complexes that drive cellular processes. Techniques for studying protein complexes have traditionally applied targeted strategies such as yeast two-hybrid or affinity purification-mass spectrometry to assess protein interactions. However, given the vast number of protein complexes, more scalable methods are necessary to accelerate interaction discovery and to construct whole interactomes. We recently developed a complementary technique based on the use of protein correlation profiling (PCP) and stable isotope labeling in amino acids in cell culture (SILAC) to assess chromatographic co-elution as evidence of interacting proteins. Importantly, PCP-SILAC is also capable of measuring protein interactions simultaneously under multiple biological conditions, allowing the detection of treatment-specific changes to an interactome. Given the uniqueness and high dimensionality of co-elution data, new tools are needed to compare protein elution profiles, control false discovery rates, and construct an accurate interactome. Here we describe a freely available bioinformatics pipeline, PrInCE, for the analysis of co-elution data. PrInCE is a modular, open-source library that is computationally inexpensive, able to use label and label-free data, and capable of detecting tens of thousands of protein-protein interactions. Using a machine learning approach, PrInCE offers greatly reduced run time, more predicted interactions at the same stringency, prediction of protein complexes, and greater ease of use over previous bioinformatics tools for co-elution data. PrInCE is implemented in Matlab (version R2017a). Source code and standalone executable programs for Windows and Mac OSX are available at https://github.com/fosterlab/PrInCE , where usage instructions can be found. An example dataset and output are also provided for testing purposes. PrInCE is the first fast and easy

  13. The evolution of predictive adaptive responses in human life history.

    Science.gov (United States)

    Nettle, Daniel; Frankenhuis, Willem E; Rickard, Ian J

    2013-09-07

    Many studies in humans have shown that adverse experience in early life is associated with accelerated reproductive timing, and there is comparative evidence for similar effects in other animals. There are two different classes of adaptive explanation for associations between early-life adversity and accelerated reproduction, both based on the idea of predictive adaptive responses (PARs). According to external PAR hypotheses, early-life adversity provides a 'weather forecast' of the environmental conditions into which the individual will mature, and it is adaptive for the individual to develop an appropriate phenotype for this anticipated environment. In internal PAR hypotheses, early-life adversity has a lasting negative impact on the individual's somatic state, such that her health is likely to fail more rapidly as she gets older, and there is an advantage to adjusting her reproductive schedule accordingly. We use a model of fluctuating environments to derive evolveability conditions for acceleration of reproductive timing in response to early-life adversity in a long-lived organism. For acceleration to evolve via the external PAR process, early-life cues must have a high degree of validity and the level of annual autocorrelation in the individual's environment must be almost perfect. For acceleration to evolve via the internal PAR process requires that early-life experience must determine a significant fraction of the variance in survival prospects in adulthood. The two processes are not mutually exclusive, and mechanisms for calibrating reproductive timing on the basis of early experience could evolve through a combination of the predictive value of early-life adversity for the later environment and its negative impact on somatic state.

  14. Family History Predicts Stress Fracture in Active Female Adolescents

    Science.gov (United States)

    Loud, Keith J.; Micheli, Lyle J.; Bristol, Stephanie; Austin, S. Bryn; Gordon, Catherine M.

    2011-01-01

    OBJECTIVE Increased physical activity and menstrual irregularity have been associated with increased risk for stress fracture among adult women active in athletics. The purposes of this study were to determine whether menstrual irregularity is also a risk factor for stress fracture in active female adolescents and to estimate the quantity of exercise associated with an increased risk for this injury. PATIENTS AND METHODS A case-control study was conducted of 13- to 22-year-old females diagnosed with their first stress fracture, each matched prospectively on age and self-reported ethnicity with 2 controls. Patients with chronic illnesses or use of medications known to affect bone mineral density were excluded, including use of hormonal preparations that could alter menstrual cycles. The primary outcome, stress fracture in any extremity or the spine, was confirmed radiographically. Girls with stress fracture had bone mineral density measured at the lumbar spine by dual-energy x-ray absorptiometry. RESULTS The mean ± SD age of the 168 participants was 15.9 ± 2.1 years; 91.7% were postmenarchal, with a mean age at menarche of 13.1 ± 1.1 years. The prevalence of menstrual irregularity was similar among cases and controls. There was no significant difference in the mean hours per week of total physical activity between girls in this sample with stress fracture (8.2 hours/week) and those without (7.4 hours/week). In multivariate models, case subjects had nearly 3 times the odds of having a family member with osteoporosis or osteopenia. In secondary analyses, participants with stress fracture had a low mean spinal bone mineral density for their age. CONCLUSIONS Among highly active female adolescents, only family history was independently associated with stress fracture. The magnitude of this association suggests that further investigations of inheritable skeletal factors are warranted in this population, along with evaluation of bone mineral density in girls with stress

  15. Predicting preeclampsia from a history of preterm birth.

    Science.gov (United States)

    Rasmussen, Svein; Ebbing, Cathrine; Irgens, Lorentz M

    2017-01-01

    To assess whether women with a history of preterm birth, independent on the presence of prelabour rupture of the membranes (PROM) and growth deviation of the newborn, are more likely to develop preeclampsia with preterm or preterm birth in a subsequent pregnancy. We conducted a population-based cohort study, based on Medical Birth Registry of Norway between 1967 and 2012, including 742,980 women with singleton pregnancies who were followed up from their 1st to 2nd pregnancy. In the analyses we included 712,511 women after excluding 30,469 women with preeclampsia in the first pregnancy. After preterm birth without preeclampsia in the first pregnancy, the risk of preterm preeclampsia in the second pregnancy was 4-7 fold higher than after term birth (odds ratios 3.5; 95% confidence interval (CI) 3.0-4.0 to 6.5; 95% CI 5.1-8.2). The risk of term preeclampsia in the pregnancy following a preterm birth was 2-3 times higher than after term birth (odds ratios 1.6; 95% CI 1.5-1.8 to 2.6; 95% CI 2.0-3.4). After spontaneous non-PROM preterm birth and preterm PROM, the risk of preterm preeclampsia was 3.3-3.6 fold higher than after spontaneous term birth. Corresponding risks of term preeclampsia was 1.6-1.8 fold higher. No significant time trends were found in the effect of spontaneous preterm birth in the first pregnancy on preterm or term preeclampsia in the second pregnancy. The results suggest that preterm birth, regardless of the presence of PROM, and preeclampsia share pathophysiologic mechanisms. These mechanisms may cause preterm birth in one pregnancy and preeclampsia in a subsequent pregnancy in the same woman. The association was particularly evident with preterm preeclampsia.

  16. Chloride:Sodium Ratio May Accurately Predict Corrected Chloride Disorders and the Presence of Unmeasured Anions in Dogs and Cats.

    Science.gov (United States)

    Goggs, Robert; Myers, Marc; De Rosa, Sage; Zager, Erik; Fletcher, Daniel J

    2017-01-01

    Disorders of chloride and mixed acid-base disturbances are common in veterinary emergency medicine. Rapid identification of these alterations and the presence of unmeasured anions aid prompt patient assessment and management. This study aimed to determine in dogs and cats if site-specific reference values for [Cl-]:[Na+] ratio and [Na+] - [Cl-] difference accurately identify corrected chloride abnormalities and to evaluate the predictive ability of the [Cl-]:[Na+] ratio for the identification of unmeasured anions. A database containing 33,117 canine, and 7,604 feline blood gas and electrolyte profiles was generated. Institution reference intervals were used to calculate site-specific reference values for the [Cl-]:[Na+] ratio and the [Na+] - [Cl-] difference. Contingency tables were used to assess the ability of these values to correctly identify corrected chloride disorders. Unmeasured anions were estimated by calculating strong ion gap (SIG). Continuous variables were compared using the Mann-Whitney U test. Correlations between continuous variables were assessed using Spearman's rho (rs). In dogs, site-specific reference values for the [Cl-]:[Na+] ratio correctly identified 94.6% of profiles as hyper-, normo-, or hypochloremic. For dogs with normal sodium concentrations, site-specific reference values for the [Na+] - [Cl-] difference correctly identified 97.0% of profiles. In dogs with metabolic acidosis (base deficit > 4.0), [Cl-]:[Na+] ratio and SIG were moderately but significantly negatively correlated (rs -0.592, P SIG was significantly greater in dogs with metabolic acidosis and hypochloremia compared to those without hypochloremia (P SIG were moderately significantly negatively correlated (rs -0.730, P SIG was significantly greater in cats with metabolic acidosis and hypochloremia compared to those without hypochloremia (P < 0.0001). Site-specific values for [Cl-]:[Na+] ratio and [Na+] - [Cl-] difference accurately identify

  17. Predicting plant responses to mycorrhizae: integrating evolutionary history and plant traits.

    Science.gov (United States)

    Reinhart, Kurt O; Wilson, Gail W T; Rinella, Matthew J

    2012-07-01

    We assessed whether (1) arbuscular mycorrhizal colonization of roots (RC) and/or plant responses to arbuscular mycorrhizae (MR) vary with plant phylogeny and (2) MR and RC can be more accurately predicted with a phylogenetic predictor relative to a null model and models with plant trait and taxonomic predictors. In a previous study, MR and RC of 95 grassland species were measured. We constructed a phylogeny for these species and found it explained variation in MR and RC. Next, we used multiple regressions to identify the models that most accurately predicted plant MR. Models including either phylogenetic or phenotypic and taxonomic information similarly improved our ability to predict MR relative to a null model. Our study illustrates the complex evolutionary associations among species and constraints of using phylogenetic information, relative to plant traits, to predict how a plant species will interact with AMF. Published 2012. This article is a US Government work and is in the public domain in the USA.

  18. Historie

    DEFF Research Database (Denmark)

    Poulsen, Jens Aage

    Historie i serien handler om læreplaner og læremidler og deres brug i skolefaget historie. Bogen indeholder nyttige redskaber til at analysere og vurdere læremidler......Historie i serien handler om læreplaner og læremidler og deres brug i skolefaget historie. Bogen indeholder nyttige redskaber til at analysere og vurdere læremidler...

  19. Predicting thermal history a-priori for magnetic nanoparticle hyperthermia of internal carcinoma

    Science.gov (United States)

    Dhar, Purbarun; Sirisha Maganti, Lakshmi

    2017-08-01

    This article proposes a simplistic and realistic method where a direct analytical expression can be derived for the temperature field within a tumour during magnetic nanoparticle hyperthermia. The approximated analytical expression for thermal history within the tumour is derived based on the lumped capacitance approach and considers all therapy protocols and parameters. The present method is simplistic and provides an easy framework for estimating hyperthermia protocol parameters promptly. The model has been validated with respect to several experimental reports on animal models such as mice/rabbit/hamster and human clinical trials. It has been observed that the model is able to accurately estimate the thermal history within the carcinoma during the hyperthermia therapy. The present approach may find implications in a-priori estimation of the thermal history in internal tumours for optimizing magnetic hyperthermia treatment protocols with respect to the ablation time, tumour size, magnetic drug concentration, field strength, field frequency, nanoparticle material and size, tumour location, and so on.

  20. A review on the young history of the wind power short-term prediction

    DEFF Research Database (Denmark)

    Costa, A.; Crespo, A.; Navarro, J.

    2008-01-01

    This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...

  1. Prediction of hemoglobin levels in whole blood donors: how to model donation history

    NARCIS (Netherlands)

    Baart, A.M.; Vergouwe, Y.; Atsma, F.; Moons, K.G.; Kort, W.L. de

    2014-01-01

    BACKGROUND: Recently, prediction models for hemoglobin (Hb) deferral risk have been developed. These models consider the previous Hb level plus change in Hb. Here, we investigated if the performance of models could be improved by considering more information on Hb level history. STUDY DESIGN AND

  2. Accurate particle speed prediction by improved particle speed measurement and 3-dimensional particle size and shape characterization technique

    DEFF Research Database (Denmark)

    Cernuschi, Federico; Rothleitner, Christian; Clausen, Sønnik

    2017-01-01

    methods, e.g. laser light scattering, and velocity by the double disk (DD) method. In this article we present two novel techniques, which allow a more accurate measurement of mass, velocity and shape, and we later compare the experimentally obtained flow velocities of particles with a simulation that also...... includes the particle's shape parameter, known as sphericity. Mass and sphericity are obtained from 3-dimensional data with an industrial X-ray computed tomography (CT) scanner. CT data can be used to accurately determine the volume-basis median of the particles (using the volume-equivalent particle......Accurate particle mass and velocity measurement is needed for interpreting test results in erosion tests of materials and coatings. The impact and damage of a surface is influenced by the kinetic energy of a particle, i.e. particle mass and velocity. Particle mass is usually determined with optical...

  3. Family history predicts major adverse cardiovascular events (MACE) in young adults with psoriasis

    DEFF Research Database (Denmark)

    Egeberg, Alexander; Bruun, Louise E; Mallbris, Lotus

    2016-01-01

    BACKGROUND: Patients with psoriasis may have increased risk of major adverse cardiovascular (CV) events (MACE), and a family history of CV disease (CVD) is an independent risk factor for MACE. OBJECTIVE: We investigated the risk of first-time MACE in patients with psoriasis with or without a family...... and severe disease, respectively. In patients with psoriasis but without a family history of CVD, there was no increased risk of MACE. LIMITATIONS: Results may not apply to late-onset psoriasis. CONCLUSIONS: A family history of CVD predicted the risk of first-time MACE in young adults with psoriasis...... history of CVD. METHODS: Between January 1, 1997, and December 31, 2011, we identified 2,722,375 individuals, including 25,774 and 4504 patients with mild and severe psoriasis, through administrative registers. Incidence rate ratios were estimated by Poisson regression. RESULTS: Mean baseline age was 26...

  4. Herbivore-induced plant volatiles accurately predict history of coexistence, diet breadth, and feeding mode of herbivores.

    NARCIS (Netherlands)

    Danner, H.; Desurmont, G.A.; Cristescu, S.M.; Dam, N.M. van

    2017-01-01

    Herbivore-induced plant volatiles (HIPVs) serve as specific cues to higher trophic levels. Novel, exotic herbivores entering native foodwebs may disrupt the infochemical network as a result of changes in HIPV profiles. Here, we analysed HIPV blends of native Brassica rapa plants infested with one of

  5. Family history of cancer predicts Papanicolaou screening behavior for African American and white women.

    Science.gov (United States)

    Williams, Karen Patricia; Reiter, Paul; Mabiso, Athur; Maurer, Joel; Paskett, Electra

    2009-01-01

    Understanding women's motivations for getting Papanicolaou (Pap) screening has the potential to impact cancer disparities. This study examined whether having a family history of cancer was a predictor for Pap screening. By using the National Health Interview Survey 2000 Cancer Control and Family modules, we identified a subsample (n=15,509) of African American (n=2774) and white women (n=12,735) unaffected by cancer, with and without a family history of cancer. Data were analyzed using logistic regression models. African American and white women with a positive family history of cancer were 42% (Phistory of cancer. Among African American women, those with a positive family history of cancer were 53% more likely to have had a recent Pap test, whereas among white women those with a positive family history of cancer were 41% more likely to have received a Pap test. African American women with a family history of cancer were more likely to have had a recent Pap test than white women with or without a family history of cancer. This study presents a unique perspective on Pap screening behavior. Having an immediate family member with any cancer statistically predicted having a recent Pap test for both African American and white women. Because these results demonstrated that regardless of the cancer type, having an immediate affected family member is a motivator for cervical cancer screening behavior, healthcare providers managing cancer treatment patients have a teachable opportunity that extends beyond the patient. Copyright (c) 2008 American Cancer Society.

  6. Accurate long-term prediction of height during the first four years of growth hormone treatment in prepubertal children with growth hormone deficiency or Turner Syndrome.

    Science.gov (United States)

    Ranke, Michael B; Lindberg, Anders; Brosz, Mathias; Kaspers, Stefan; Loftus, Jane; Wollmann, Hartmut; Kołtowska-Haggstrom, Maria; Roelants, Mathieu

    2012-01-01

    The study aim was to develop and validate models for long-term prediction of growth in prepubertal children with idiopathic growth hormone deficiency (GHD) or Turner syndrome (TS) for optimal, cost-effective growth hormone (GH) therapy. Height was predicted by sequential application of annual prediction algorithms for height velocity in cohorts of GHD (n = 664) and TS (n = 607) as documented within KIGS (Pfizer International Growth Database). As height prediction models also require an estimate of weight, new algorithms for weight increase during the first to fourth prepubertal years on GH were developed. When height was predicted from the start of GH treatment, the predicted and observed mean (SD) gain over 4 years was 30.4 (3.4) cm and 30.1 (4.9) cm, respectively, in GHD patients, and 27.2 (2.2) cm and 26.6 (3.5) cm, respectively, in TS patients. For all 4 years, gains of weight SD scores (SDS) were accurately described as a function of weight SDS and observed gain in height SDS (R(2) > 0.89). In GHD and TS patients treated with GH, an accurate prepubertal long-term prediction of height development in groups is possible. Based on this, an optimal individual height outcome could be simulated. Copyright © 2012 S. Karger AG, Basel.

  7. Towards accurate prediction of unbalance response, oil whirl and oil whip of flexible rotors supported by hydrodynamic bearings

    NARCIS (Netherlands)

    Eling, R.P.T.; te Wierik, M.; van Ostayen, R.A.J.; Rixen, D.J.

    2016-01-01

    Journal bearings are used to support rotors in a wide range of applications. In order to ensure reliable operation, accurate analyses of these rotor-bearing systems are crucial. Coupled analysis of the rotor and the journal bearing is essential in the case that the rotor is flexible. The accuracy of

  8. Predicted probability of meniscus tears: comparing history and physical examination with MRI.

    Science.gov (United States)

    Yan, R; Wang, H; Yang, Z; Ji, Z H; Guo, Y M

    2011-12-14

    The indication for surgical treatment of a meniscal lesion should not only rely on magnetic resonance imaging (MRI) findings, but also on a detailed history and a thorough clinical examination. However, various intra-articular lesions may often produce similar symptoms. So, what kinds of symptoms are more associated with a meniscal tear? Is MRI worth doing? The aims of this study were to identify sensitive and specific clinical tests and elements of patients' history with a high predictive value, and to assess the combined diagnostic accuracy of sensitive and specific clinical tests and elements of patients' history with MRI. Data from 281 consecutive knee arthroscopies to investigate and treat suspected internal knee pathologies were retrospectively collected between March 2009 and April 2010. The study group consisted of 262 knees. Statistically significant factors in the clinical diagnosis of meniscal tears were screened by a chi-square test. Logistic regression analysis was used to determine which factors associated with meniscal tears found during arthroscopy. The diagnostic values of MRI and the sensitive and specific clinical tests and elements of patients' history with high predictive value for meniscal tears were calculated. The overall diagnostic value of MRI for meniscal tears was: accuracy, 88.8%; sensitivity, 95.7%; specificity, 75.8%; positive predictive value (PPV), 88.2%; and negative predictive value (NPV), 90.4%. Giving way, locking and McMurray's test were independent diagnostic factors with a predicted correct percentage of 80.0% (p predicted correct percentage of meniscal tears found during arthroscopy to 91.6% (p factors for the diagnosis of meniscal tears. MRI has higher accuracy, sensitivity and NPV for the diagnosis of meniscal tears than giving way, locking and McMurray's test. The combination of giving way, locking, McMurray's test and MRI for confirmation is typical for a meniscal lesion diagnosis. Based on these findings, MRI should be

  9. Random forest algorithm yields accurate quantitative prediction models of benthic light at intertidal sites affected by toxic Lyngbya majuscula blooms

    NARCIS (Netherlands)

    Kehoe, M.J.; O’ Brien, K.; Grinham, A.; Rissik, D.; Ahern, K.S.; Maxwell, P.

    2012-01-01

    It is shown that targeted high frequency monitoring and modern machine learning methods lead to highly predictive models of benthic light flux. A state-of-the-art machine learning technique was used in conjunction with a high frequency data set to calibrate and test predictive benthic lights models

  10. Is it possible to accurately predict outcome of a drop-foot in patients admitted to a hospital stroke unit?

    NARCIS (Netherlands)

    Cioncoloni, D.; Veerbeek, J.M.; van Wegen, E.E.H.; Kwakkel, G.

    2013-01-01

    The aim of this study was to determine whether recovery from a drop-foot at 6 months can be predicted within 72 h after stroke and to investigate the effect of timing on the accuracy of prediction. One hundred and five patients with a first-ever anterior circulation stroke without full voluntary

  11. A Predictive Model for the Diagnosis of Allergic Drug Reactions According to the Medical History.

    Science.gov (United States)

    Hierro Santurino, Beatriz; Mateos Conde, Javier; Cabero Morán, María Teresa; Mirón Canelo, José Antonio; Armentia Medina, Alicia

    2016-01-01

    Quantification of the risk of an allergic drug reaction through the medical history is essential in clinical decision making. However, in normal clinical practice, this evaluation is generally entirely subjective. The objective of this study was to construct a mathematical model to predict the risk of allergic drug reactions using the data collected in the medical history. A total of 696 active principles, corresponding to 466 patients aged more than 14 years attending the Allergy Service of the University Hospital of Salamanca, were included. Simple binary logistic regression was used to determine associations between variables from the medical history and the final diagnosis, to construct a predictive model. Variables useful in predicting a final diagnosis of allergic drug reaction were age, sex, drug class, number of active principles, time to the reaction, number of doses, clinical presentation suggestive of allergic disease, and time to medical consultation. True adverse drug reactions were estimated to occur in 20% of active principles. However, possible allergic reactions could only be ruled out in 52.2%. The use of mathematical models could greatly improve the discriminatory capacity of the medical history. Both the overdiagnosis and underdiagnosis of allergic drug reactions should be considered a public health problem. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  12. 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 possessing

  13. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

    Directory of Open Access Journals (Sweden)

    Liqi Li

    Full Text Available Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM in conjunction with integrated features from position-specific score matrix (PSSM, PROFEAT and Gene Ontology (GO. A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

  14. ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling.

    Science.gov (United States)

    Lei, Tailong; Li, Youyong; Song, Yunlong; Li, Dan; Sun, Huiyong; Hou, Tingjun

    2016-01-01

    Determination of acute toxicity, expressed as median lethal dose (LD50), is one of the most important steps in drug discovery pipeline. Because in vivo assays for oral acute toxicity in mammals are time-consuming and costly, there is thus an urgent need to develop in silico prediction models of oral acute toxicity. In this study, based on a comprehensive data set containing 7314 diverse chemicals with rat oral LD50 values, relevance vector machine (RVM) technique was employed to build the regression models for the prediction of oral acute toxicity in rate, which were compared with those built using other six machine learning approaches, including k-nearest-neighbor regression, random forest (RF), support vector machine, local approximate Gaussian process, multilayer perceptron ensemble, and eXtreme gradient boosting. A subset of the original molecular descriptors and structural fingerprints (PubChem or SubFP) was chosen by the Chi squared statistics. The prediction capabilities of individual QSAR models, measured by q ext (2) for the test set containing 2376 molecules, ranged from 0.572 to 0.659. Considering the overall prediction accuracy for the test set, RVM with Laplacian kernel and RF were recommended to build in silico models with better predictivity for rat oral acute toxicity. By combining the predictions from individual models, four consensus models were developed, yielding better prediction capabilities for the test set (q ext (2) = 0.669-0.689). Finally, some essential descriptors and substructures relevant to oral acute toxicity were identified and analyzed, and they may be served as property or substructure alerts to avoid toxicity. We believe that the best consensus model with high prediction accuracy can be used as a reliable virtual screening tool to filter out compounds with high rat oral acute toxicity. Graphical abstractWorkflow of combinatorial QSAR modelling to predict rat oral acute toxicity.

  15. Nurses and physicians in a medical admission unit can accurately predict mortality of acutely admitted patients: a prospective cohort study.

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    Mikkel Brabrand

    Full Text Available There exist several risk stratification systems for predicting mortality of emergency patients. However, some are complex in clinical use and others have been developed using suboptimal methodology. The objective was to evaluate the capability of the staff at a medical admission unit (MAU to use clinical intuition to predict in-hospital mortality of acutely admitted patients.This is an observational prospective cohort study of adult patients (15 years or older admitted to a MAU at a regional teaching hospital. The nursing staff and physicians predicted in-hospital mortality upon the patients' arrival. We calculated discriminatory power as the area under the receiver-operating-characteristic curve (AUROC and accuracy of prediction (calibration by Hosmer-Lemeshow goodness-of-fit test.We had a total of 2,848 admissions (2,463 patients. 89 (3.1% died while admitted. The nursing staff assessed 2,404 admissions and predicted mortality in 1,820 (63.9%. AUROC was 0.823 (95% CI: 0.762-0.884 and calibration poor. Physicians assessed 738 admissions and predicted mortality in 734 (25.8% of all admissions. AUROC was 0.761 (95% CI: 0.657-0.864 and calibration poor. AUROC and calibration increased with experience. When nursing staff and physicians were in agreement (±5%, discriminatory power was very high, 0.898 (95% CI: 0.773-1.000, and calibration almost perfect. Combining an objective risk prediction score with staff predictions added very little.Using only clinical intuition, staff in a medical admission unit has a good ability to identify patients at increased risk of dying while admitted. When nursing staff and physicians agreed on their prediction, discriminatory power and calibration were excellent.

  16. Accurate and computationally efficient prediction of thermochemical properties of biomolecules using the generalized connectivity-based hierarchy.

    Science.gov (United States)

    Sengupta, Arkajyoti; Ramabhadran, Raghunath O; Raghavachari, Krishnan

    2014-08-14

    In this study we have used the connectivity-based hierarchy (CBH) method to derive accurate heats of formation of a range of biomolecules, 18 amino acids and 10 barbituric acid/uracil derivatives. The hierarchy is based on the connectivity of the different atoms in a large molecule. It results in error-cancellation reaction schemes that are automated, general, and can be readily used for a broad range of organic molecules and biomolecules. Herein, we first locate stable conformational and tautomeric forms of these biomolecules using an accurate level of theory (viz. CCSD(T)/6-311++G(3df,2p)). Subsequently, the heats of formation of the amino acids are evaluated using the CBH-1 and CBH-2 schemes and routinely employed density functionals or wave function-based methods. The calculated heats of formation obtained herein using modest levels of theory and are in very good agreement with those obtained using more expensive W1-F12 and W2-F12 methods on amino acids and G3 results on barbituric acid derivatives. Overall, the present study (a) highlights the small effect of including multiple conformers in determining the heats of formation of biomolecules and (b) in concurrence with previous CBH studies, proves that use of the more effective error-cancelling isoatomic scheme (CBH-2) results in more accurate heats of formation with modestly sized basis sets along with common density functionals or wave function-based methods.

  17. Early unpredictability predicts increased adolescent externalizing behaviors and substance use: A life history perspective.

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    Doom, Jenalee R; Vanzomeren-Dohm, Adrienne A; Simpson, Jeffry A

    2016-11-01

    According to evolutionary life history models, environmental harshness and unpredictability can both promote a fast life history strategy characterized by increased risk taking and enacting short-term, opportunistic behaviors. The current longitudinal study tests whether environmental unpredictability during childhood has stronger effects on risky behavior during adolescence than harshness, and whether there may be an early "sensitive period" during which unpredictability has particularly strong and unique effects on these outcomes. Using data from the Minnesota Longitudinal Study of Risk and Adaptation, prospective assessments of environmental unpredictability (changes in residence, cohabitation, and parental occupation) and harshness (mean socioeconomic status) from birth into adolescence were used to predict self-reported externalizing behaviors and substance use at age 16 (N = 220). Exposure to greater early unpredictability (between ages 0 and 5) predicted more externalizing behaviors as well as more alcohol and marijuana use at age 16, controlling for harshness and later unpredictability (between ages 6 and 16). Harshness predicted adolescent substance use, and later unpredictability predicted adolescent externalizing behaviors at the trend level. Early unpredictability and harshness also interacted, such that the highest levels of risk taking occurred in individuals who experienced more early unpredictability and lived in harsher environments. Age 16 externalizing behaviors, but not substance use, mediated the association between early unpredictability and externalizing/criminal behaviors at age 23. We discuss how exposure to early environmental unpredictability may alter biological and social-cognitive functioning from a life history perspective.

  18. Family history of venous thromboembolism predicts the diagnosis of acute pulmonary embolism in the emergency department.

    Science.gov (United States)

    Kelly, Christopher; Agy, Chad; Carlson, Margaret; Steenblik, Jacob; Bledsoe, Joseph; Hartsell, Stephen; Madsen, Troy

    2018-01-06

    Pulmonary embolism (PE) clinical decision rules do not consider a patient's family history of venous thromboembolism (VTE). We evaluated whether a family history of VTE predicts acute PE in the emergency department (ED). Over a 5.5-year study period, we enrolled a prospective convenience sample of patients presenting to an academic emergency department with chest pain and/or shortness of breath. We defined a family history of VTE as a first-degree relative with previous PE or deep vein thrombosis (DVT). We noted outcomes of testing during the patient's ED stay, including the diagnosis of acute PE by either computed tomography (CT) or ventilation/perfusion (VQ) scan. Of the 3024 study patients, 19.4% reported a family history of VTE and 1.9% were diagnosed with an acute PE during the ED visit. Patients with a family history of VTE were more likely to be diagnosed with a PE: 3.2% vs. 1.6% (p = 0.009). 82.3% of patients were Pulmonary Embolism Rule-out Criteria (PERC) positive, and among PERC-positive patients, those with a family history of VTE were more likely to be diagnosed with a PE: 3.6% vs. 1.9% (p = 0.016). Of patients who underwent testing for PE (33.7%), patients with a family history of VTE were more likely to be diagnosed with a PE: 9.4% vs. 4.9% (p = 0.032). Patients with a self-reported family history of VTE in a first-degree relative are more likely to be diagnosed with an acute PE in the ED, even among those patients considered to have a higher likelihood of PE. Copyright © 2018. Published by Elsevier Inc.

  19. Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

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    Vullo Alessandro

    2007-06-01

    Full Text Available Abstract Background Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio. Results Here we develop high-throughput machine learning systems for the prediction of protein secondary structure and solvent accessibility that exploit homology to proteins of known structure, where available, in the form of simple structural frequency profiles extracted from sets of PDB templates. We compare these systems to their state-of-the-art ab initio counterparts, and with a number of baselines in which secondary structures and solvent accessibilities are extracted directly from the templates. We show that structural information from templates greatly improves secondary structure and solvent accessibility prediction quality, and that, on average, the systems significantly enrich the information contained in the templates. For sequence similarity exceeding 30%, secondary structure prediction quality is approximately 90%, close to its theoretical maximum, and 2-class solvent accessibility roughly 85%. Gains are robust with respect to template selection noise, and significant for marginal sequence similarity and for short alignments, supporting the claim that these improved predictions may prove beneficial beyond the case in which clear homology is available. Conclusion The predictive system are publicly available at the address http://distill.ucd.ie.

  20. An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

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    Sergei L Kosakovsky Pond

    2009-11-01

    Full Text Available Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1 are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5% fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance

  1. Predicting responses to climate change requires all life-history stages.

    Science.gov (United States)

    Zeigler, Sara

    2013-01-01

    In Focus: Radchuk, V., Turlure, C. & Schtickzelle, N. (2013) Each life stage matters: the importance of assessing response to climate change over the complete life cycle in butterflies. Journal of Animal Ecology, 82, 275-285. Population-level responses to climate change depend on many factors, including unexpected interactions among life history attributes; however, few studies examine climate change impacts over complete life cycles of focal species. Radchuk, Turlure & Schtickzelle () used experimental and modelling approaches to predict population dynamics for the bog fritillary butterfly under warming scenarios. Although they found that warming improved fertility and survival of all stages with one exception, populations were predicted to decline because overwintering larvae, whose survival declined with warming, were disproportionately important contributors to population growth. This underscores the importance of considering all life history stages in analyses of climate change's effects on population dynamics. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

  2. Life-history traits predict perennial species response to fire in a desert ecosystem

    Science.gov (United States)

    Shryock, Daniel F.; DeFalco, Lesley A.; Esque, Todd C.

    2014-01-01

    The Mojave Desert of North America has become fire-prone in recent decades due to invasive annual grasses that fuel wildfires following years of high rainfall. Perennial species are poorly adapted to fire in this system, and post-fire shifts in species composition have been substantial but variable across community types. To generalize across a range of conditions, we investigated whether simple life-history traits could predict how species responded to fire. Further, we classified species into plant functional types (PFTs) based on combinations of life-history traits and evaluated whether these groups exhibited a consistent fire-response. Six life-history traits varied significantly between burned and unburned areas in short (up to 4 years) or long-term (up to 52 years) post-fire datasets, including growth form, lifespan, seed size, seed dispersal, height, and leaf longevity. Forbs and grasses consistently increased in abundance after fire, while cacti were reduced and woody species exhibited a variable response. Woody species were classified into three PFTs based on combinations of life-history traits. Species in Group 1 increased in abundance after fire and were characterized by short lifespans, small, wind-dispersed seeds, low height, and deciduous leaves. Species in Group 2 were reduced by fire and distinguished from Group 1 by longer lifespans and evergreen leaves. Group 3 species, which also decreased after fire, were characterized by long lifespans, large non-wind dispersed seeds, and taller heights. Our results show that PFTs based on life-history traits can reliably predict the responses of most species to fire in the Mojave Desert. Dominant, long-lived species of this region possess a combination of traits limiting their ability to recover, presenting a clear example of how a novel disturbance regime may shift selective environmental pressures to favor alternative life-history strategies.

  3. Predicting utility of exercise tests based on history/holter in patients with premature ventricular contractions.

    Science.gov (United States)

    Robinson, Brad; Xie, Li; Temple, Joel; Octavio, Jenna; Srayyih, Maytham; Thacker, Deepika; Kharouf, Rami; Davies, Ryan; Gidding, Samuel S

    2015-01-01

    Premature ventricular contractions (PVCs) are considered benign in patients with structurally normal hearts, particularly if they suppress with exercise. Catecholaminergic polymorphic ventricular tachycardia (CPVT) requires exercise testing to unmask the malignant phenotype. We studied risk factors and Holter monitor variables to help predict the necessity of exercise testing in patients with PVCs. We retrospectively reviewed 81 patients with PVCs that suppressed at peak exercise and structurally normal hearts referred to the exercise laboratory in 2011. We reviewed 11 patients from 2003 to 2012 whose PVCs were augmented at peak exercise (mean age 13 ± 4 years; 52 % male, 180 exercise studies). We recorded clinical risk factors and comorbidities (family history of arrhythmia or sudden unexpected death [SUD], presence of syncope) and Holter testing parameters. Family history of VT or SUD (P = 0.011) and presence of VT on Holter (P = 0.011) were significant in predicting failure of PVCs to suppress at peak heart rate on exercise testing. Syncope was not statistically significant in predicting suppression (P = 0.18); however, CPVT was diagnosed in four patients with syncope during exercise. Quantity of PVCs, Lown grade, couplets on Holter, monomorphism, and PVC elimination at peak heart rate on Holter were not predictors of PVC suppression on exercise testing. Patients with syncope during exercise, family history of arrhythmia or SUD, or a Holter monitor showing VT warrant exercise testing to assess for CPVT.

  4. Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

    Directory of Open Access Journals (Sweden)

    Wei Luo

    Full Text Available For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD outcomes (four NCDs and two major clinical risk factors, based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88 and those excluded from the development for use as a completely separated validation sample (median correlation 0.85, demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

  5. A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults

    Science.gov (United States)

    George, James D.; Bradshaw, Danielle I.; Hyde, Annette; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.

    2007-01-01

    The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO sub 2 max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean plus or minus standard deviation [SD]; maximal heart rate [HR sub…

  6. Combined AFP-CRUT with microvascular invasion accurately predicts mortality risk in patients with hepatocellular carcinoma following curative liver resection.

    Science.gov (United States)

    Huang, Gui-Qian; Zhu, Gui-Qi; Huang, Sha; You, Jie; Shi, Ke-Qing; Hu, Bin; Ruan, Lu-Yi; Zhou, Meng-Tao; Braddock, Martin; Zheng, Ming-Hua

    2015-01-01

    To establish and validate an equation of α-fetoprotein (AFP) change rate over unit time (AFP-CRUT) as a potential predictor of survival after resection in patients with hepatocellular carcinoma (HCC). The AFP-CRUT was constructed based on dynamic variation in AFP over time and then categorized into quintiles. The area under the receiver operating characteristic (ROC) curve showed the performance for survival prediction. As independent risk factors associated with mortality, microvascular invasion (MVI) (p = 0.003) and AFP-CRUT quintiles (p = 0.048) were combined to enhance the predictive effect. The highest 5-year overall survival rate following curative liver resection (93%) was observed in patients with MVI absent and AFP-CRUT in quintile 1 (49.64 to 209.61). In contrast, the lowest 5-year overall survival (7%) was obtained in quintile 5 (-469.29 to 6.45) with MVI present. In validation cohorts at both 12 and 24 months, AFP-CRUT performed well as a potential prognostic biomarker. Combining AFP-CRUT quintiles with MVI may predict significantly improved outcomes and enhance the predictive power for patient responses to therapeutic intervention.

  7. Should clinicians use average or peak scores on a dynamic risk-assessment measure to most accurately predict inpatient aggression?

    Science.gov (United States)

    Chu, Chi Meng; Thomas, Stuart D M; Daffern, Michael; Ogloff, James R P

    2013-12-01

    Recent advancements in risk assessment have led to the development of dynamic risk-assessment measures that are predictive of inpatient aggression in the short term. However, there are several areas within this field that warrant further empirical investigation, including whether the average, maximum, or most recent risk state assessment is the most valid for predicting subsequent aggression in the medium term. This prospective study compared the predictive validity of three indices (i.e. mean score, peak score, and most recent single time-point rating) of the Dynamic Appraisal of Situational Aggression (DASA) for inpatient aggression. Daily risk ratings were completed for 60 psychiatric inpatients (from the acute wards of a forensic psychiatric hospital) for up to 6 months; a total of 1054 DASA ratings were obtained. Results showed that mean and peak scores on the DASA were better predictors of interpersonal violence, verbal threat, and any inpatient aggression than the DASA single time-point most recent ratings. Overall, the results support the use of the prior week's mean and peak scores to aid the prediction of inpatient aggression within inpatient forensic psychiatric settings in the short to medium term. These results also have practical implications for clinicians considering risk-management strategies and the scoring of clinically-relevant items on risk-assessment measures. © 2012 The Authors; International Journal of Mental Health Nursing © 2012 Australian College of Mental Health Nurses Inc.

  8. Can the initial history predict whether a child with a head injury has been abused?

    Science.gov (United States)

    Hettler, Joeli; Greenes, David S

    2003-03-01

    Previous studies of child abuse have used the presenting history as part of the case definition of abuse. Thus, data from these studies cannot be used to determine the diagnostic utility of historical features for identifying cases of abuse. The objective of this study was to determine the diagnostic utility of certain historical features for identifying cases of abusive head trauma. We retrospectively studied all children, aged 0 to 3 years, who had acute traumatic intracranial injury and were admitted to a tertiary care pediatric hospital from 1993 to 2000. Cases were categorized as either "definite abuse" or "not definite abuse" on the basis of radiologic, ophthalmologic, and physical examination findings, without regard to the presenting history. Forty-nine (30%) of 163 children met the criteria for definite abuse. Having no history of trauma had a high specificity (0.97) and positive predictive value (PPV; 0.92) for abuse. Among the subgroup of patients with persistent neurologic abnormality at hospital discharge (n = 34), having a history of no or low-impact trauma had a specificity of 1.0 and a PPV of 1.0 for definite abuse. Injuries were blamed on home resuscitative efforts in 12% of definite abuse cases and 0% of not definite abuse cases. The initial history of trauma was changed in 9% of definite abuse cases, as compared with 0% of not definite abuse cases. Among young children with a head injury, certain historical features have high specificity and PPV for diagnosing child abuse.

  9. Can Social History Variables Predict Prison Inmates’ Risk for Latent Tuberculosis Infection?

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    Tyler E. Weant

    2012-01-01

    Full Text Available Improved screening and treatment of latent tuberculosis infection (LTBI in correctional facilities may improve TB control. The Ohio Department of Rehabilitation and Correction (ODRC consists of 32 prisons. Inmates are screened upon entry to ODRC and yearly thereafter. The objective of the study was to determine if social history factors such as tobacco, alcohol, and drug use are significant predictors of LTBI and treatment outcomes. We reviewed the medical charts of inmates and randomly selected age-matched controls at one ODRC facility for 2009. We used a conditional logistic regression to assess associations between selected social history variables and LTBI diagnosis. Eighty-nine inmates with a history of LTBI and 88 controls were identified. No social history variable was a significant predictor of LTBI. Medical comorbidities such as asthma, rheumatoid arthritis, and hepatitis C were significantly higher in inmates with LTBI. 84% of inmates diagnosed with LTBI had either completed or were on treatment. Annual TB screening may not be cost-effective in all inmate populations. Identification of factors to help target screening populations at risk for TB is critical. Social history variables did not predict LTBI in our inmate population. Additional studies are needed to identify inmates for the targeted TB testing.

  10. Formation of NO from N2/O2 mixtures in a flow reactor: Toward an accurate prediction of thermal NO

    DEFF Research Database (Denmark)

    Abian, Maria; Alzueta, Maria U.; Glarborg, Peter

    2015-01-01

    We have conducted flow reactor experiments for NO formation from N2/O2 mixtures at high temperatures and atmospheric pressure, controlling accurately temperature and reaction time. Under these conditions, atomic oxygen equilibrates rapidly with O2. The experimental results were interpreted...... by a detailed chemical model to determine the rate constant for the reaction N2 + O ⇌ NO + N (R1). We obtain k1 = 1.4 × 1014 exp(-38,300/T) cm3 mol-1 s-1 at 1700-1800 K, with an error limit of ±30%. This value is 25% below the recommendation of Baulch et al. for k1, while it corresponds to a value k1b...

  11. From dimer to condensed phases at extreme conditions: accurate predictions of the properties of water by a Gaussian charge polarizable model.

    Science.gov (United States)

    Paricaud, Patrice; Predota, Milan; Chialvo, Ariel A; Cummings, Peter T

    2005-06-22

    Water exhibits many unusual properties that are essential for the existence of life. Water completely changes its character from ambient to supercritical conditions in a way that makes it possible to sustain life at extreme conditions, leading to conjectures that life may have originated in deep-sea vents. Molecular simulation can be very useful in exploring biological and chemical systems, particularly at extreme conditions for which experiments are either difficult or impossible; however this scenario entails an accurate molecular model for water applicable over a wide range of state conditions. Here, we present a Gaussian charge polarizable model (GCPM) based on the model developed earlier by Chialvo and Cummings [Fluid Phase Equilib. 150, 73 (1998)] which is, to our knowledge, the first that satisfies the water monomer and dimer properties, and simultaneously yields very accurate predictions of dielectric, structural, vapor-liquid equilibria, and transport properties, over the entire fluid range. This model would be appropriate for simulating biological and chemical systems at both ambient and extreme conditions. The particularity of the GCPM model is the use of Gaussian distributions instead of points to represent the partial charges on the water molecules. These charge distributions combined with a dipole polarizability and a Buckingham exp-6 potential are found to play a crucial role for the successful and simultaneous predictions of a variety of water properties. This work not only aims at presenting an accurate model for water, but also at proposing strategies to develop classical accurate models for the predictions of structural, dynamic, and thermodynamic properties.

  12. Accurate prediction of the electronic properties of low-dimensional graphene derivatives using a screened hybrid density functional.

    Science.gov (United States)

    Barone, Veronica; Hod, Oded; Peralta, Juan E; Scuseria, Gustavo E

    2011-04-19

    Over the last several years, low-dimensional graphene derivatives, such as carbon nanotubes and graphene nanoribbons, have played a central role in the pursuit of a plausible carbon-based nanotechnology. Their electronic properties can be either metallic or semiconducting depending purely on morphology, but predicting their electronic behavior has proven challenging. The combination of experimental efforts with modeling of these nanometer-scale structures has been instrumental in gaining insight into their physical and chemical properties and the processes involved at these scales. Particularly, approximations based on density functional theory have emerged as a successful computational tool for predicting the electronic structure of these materials. In this Account, we review our efforts in modeling graphitic nanostructures from first principles with hybrid density functionals, namely the Heyd-Scuseria-Ernzerhof (HSE) screened exchange hybrid and the hybrid meta-generalized functional of Tao, Perdew, Staroverov, and Scuseria (TPSSh). These functionals provide a powerful tool for quantitatively studying structure-property relations and the effects of external perturbations such as chemical substitutions, electric and magnetic fields, and mechanical deformations on the electronic and magnetic properties of these low-dimensional carbon materials. We show how HSE and TPSSh successfully predict the electronic properties of these materials, providing a good description of their band structure and density of states, their work function, and their magnetic ordering in the cases in which magnetism arises. Moreover, these approximations are capable of successfully predicting optical transitions (first and higher order) in both metallic and semiconducting single-walled carbon nanotubes of various chiralities and diameters with impressive accuracy. This versatility includes the correct prediction of the trigonal warping splitting in metallic nanotubes. The results predicted

  13. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems.

    Directory of Open Access Journals (Sweden)

    Ram Samudrala

    2009-04-01

    Full Text Available The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates--effector proteins--are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

  14. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    Science.gov (United States)

    Wang, Ting; He, Quanze; Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing.

  15. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    Directory of Open Access Journals (Sweden)

    Ting Wang

    Full Text Available Massively parallel sequencing (MPS combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs by sequencing cell-free fetal DNA (cffDNA from maternal plasma, so-called non-invasive prenatal testing (NIPT. However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR and false positive rate (FPR in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1% in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples, suggesting that it is reliable and robust enough for clinical testing.

  16. Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data

    Directory of Open Access Journals (Sweden)

    Martin eReczko

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small regulatory genes regulating gene expression by targetingmessenger RNA. Though computational methods for miRNA target prediction are the prevailingmeans to analyze their function, they still miss a large fraction of the targeted genes and additionallypredict a large number of false positives. Here we introduce a novel algorithm called DIANAmicroT-ANN which combines multiple novel target site features through an artificial neural network(ANN and is trained using recently published high-throughput data measuring the change of proteinlevels after miRNA overexpression, providing positive and negative targeting examples. The featurescharacterizing each miRNA recognition element include binding structure, conservation level and aspecific profile of structural accessibility. The ANN is trained to integrate the features of eachrecognition element along the 3’ untranslated region into a targeting score, reproducing the relativerepression fold change of the protein. Tested on two different sets the algorithm outperforms otherwidely used algorithms and also predicts a significant number of unique and reliable targets notpredicted by the other methods. For 542 human miRNAs DIANA-microT-ANN predicts 120,000targets not provided by TargetScan 5.0. The algorithm is freely available athttp://microrna.gr/microT-ANN.

  17. Central venous parathyroid hormone monitoring using a novel, specific anatomic method accurately predicts cure during minimally invasive parathyroidectomy.

    Science.gov (United States)

    Edwards, Courtney M; Folek, Jessica; Dayawansa, Samantha; Govednik, Cara M; Quinn, Courtney E; Sigmond, Benjamin R; Lee, Cortney Y; Angel, Melissa S; Hendricks, John C; Lairmore, Terry C

    2016-12-01

    Measurement of intraoperative parathyroid hormone (PTH) levels is an important adjunct to confirm biochemical cure during parathyroidectomy. The purpose of this study was to evaluate a simplified anatomic technique for PTH sampling from the central veins through the minimally invasive neck incision, and to compare the predictive accuracy of central and peripheral PTH values. A specific anatomic method for central PTH sampling was employed in 48 patients. Samples were drawn simultaneously from peripheral and central veins at baseline and 10 minutes postexcision of all hyperfunctioning parathyroid glands. The central venous PTH levels independently predicted biochemical cure according to the Miami criterion in all the patients. There was no significant difference in the postexcision central and peripheral values, which were 24.40 + 1.86 and 21.69 + 1.74, respectively (P = .877, ANOVA test). This study provides the original description of a simplified technique for measurement of intraoperative PTH levels in the central veins with direct comparison to peripheral venous levels, and confirmation of accuracy in predicting biochemical cure when relying on centrally obtained values alone. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction.

    Science.gov (United States)

    Pan, Xiaoyong; Fan, Yong-Xian; Yan, Junchi; Shen, Hong-Bin

    2016-08-09

    Non-coding RNAs (ncRNAs) play crucial roles in many biological processes, such as post-transcription of gene regulation. ncRNAs mainly function through interaction with RNA binding proteins (RBPs). To understand the function of a ncRNA, a fundamental step is to identify which protein is involved into its interaction. Therefore it is promising to computationally predict RBPs, where the major challenge is that the interaction pattern or motif is difficult to be found. In this study, we propose a computational method IPMiner (Interaction Pattern Miner) to predict ncRNA-protein interactions from sequences, which makes use of deep learning and further improves its performance using stacked ensembling. One of the IPMiner's typical merits is that it is able to mine the hidden sequential interaction patterns from sequence composition features of protein and RNA sequences using stacked autoencoder, and then the learned hidden features are fed into random forest models. Finally, stacked ensembling is used to integrate different predictors to further improve the prediction performance. The experimental results indicate that IPMiner achieves superior performance on the tested lncRNA-protein interaction dataset with an accuracy of 0.891, sensitivity of 0.939, specificity of 0.831, precision of 0.945 and Matthews correlation coefficient of 0.784, respectively. We further comprehensively investigate IPMiner on other RNA-protein interaction datasets, which yields better performance than the state-of-the-art methods, and the performance has an increase of over 20 % on some tested benchmarked datasets. In addition, we further apply IPMiner for large-scale prediction of ncRNA-protein network, that achieves promising prediction performance. By integrating deep neural network and stacked ensembling, from simple sequence composition features, IPMiner can automatically learn high-level abstraction features, which had strong discriminant ability for RNA-protein detection. IPMiner achieved

  19. 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 hypotheses. However, by evaluating the consistency of theoretical predictions with empirically-estimated effective size, insights can be gained regarding life-history characteristics, as well as 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. Here we describe and demonstrate this approach by addressing the conservation of a reintroduced population of Asiatic wild ass (Equus hemionus). We estimate the variance effective size (Nev ) from genetic data (Nev = 24.3), and we formulate predictions for the impacts on Nev of demography, polygyny, female variance in life-time reproductive success, and heritability of female reproductive success. By contrasting the genetic estimation with theoretical predictions, we find that polygyny is the strongest factor effecting genetic drift, as only when accounting for polygyny were predictions consistent with the genetically-measured Nev , with 10.6% mating males per generation when heritability of female RS was unaccounted for (polygyny responsible for 81% decrease in Nev ), and 19.5% when it was accounted for (polygyny responsible for 67% decrease in Nev ). Heritability of female reproductive success was also found to affect Nev , with hf2 = 0.91 (heritability responsible for 41% decrease in Nev ). The low effective population size is of concern, and we suggest specific management actions focusing on factors identified as strongly affecting Nev -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

  20. Which dialysis unit blood pressure is the most accurate for predicting home blood pressure in patients undergoing hemodialysis?

    Science.gov (United States)

    Yoon, In-Cheol; Choi, Hye-Min; Oh, Dong-Jin

    2017-01-01

    We investigated which dialysis unit blood pressure (BP) is the most useful for predicting home BP in patients undergoing hemodialysis (HD). Patients undergoing HD who had been treated > 3 months were included in this study. Exclusion criteria were hospitalized patients with acute illness and changes in dry weight and anti-hypertensive drugs 2 weeks before the study. We used the dialysis unit BP recording data, such as pre-HD, intra-HD, post-HD, mean pre-HD, and post-HD (pre-post-HD), mean pre-HD, intra-HD, and post-HD (pre-intra-post-HD) BP. Home BP (the same period of dialysis unit BP) was monitored as a reference method during 2 weeks using the same automatic oscillometric device. Patients were asked to record their BP three times daily (wake up, between noon and 6:00 PM, and at bedtime). Significant differences were detected between home systolic blood pressure (SBP) and pre-HD, post-HD, and intra-HD SBP (p = 0.003, p = 0.001, p = 0.016, respectively). In contrast, no differences were observed between home SBP and pre-intra-post-HD and pre-post-HD SBP (p = 0.235, p = 0.307, respectively). Areas under the receiver operating characteristic curve for pre-intra-post-HD and prepost-HD SBP with 2-week home BP as the reference standard were 0.812 and 0.801, respectively. These results suggest that pre-intra-post-HD and pre-post-HD SBP had similar accuracy for predicting mean 2-week home SBP in HD patients. Therefore, pre-intra-post-HD and pre-post-HD SBP should be useful for predicting home SBP in HD patients if ambulatory or home BP measurements are unavailable.

  1. Accuration of Time Series and Spatial Interpolation Method for Prediction of Precipitation Distribution on the Geographical Information System

    Science.gov (United States)

    Prasetyo, S. Y. J.; Hartomo, K. D.

    2018-01-01

    The Spatial Plan of the Province of Central Java 2009-2029 identifies that most regencies or cities in Central Java Province are very vulnerable to landslide disaster. The data are also supported by other data from Indonesian Disaster Risk Index (In Indonesia called Indeks Risiko Bencana Indonesia) 2013 that suggest that some areas in Central Java Province exhibit a high risk of natural disasters. This research aims to develop an application architecture and analysis methodology in GIS to predict and to map rainfall distribution. We propose our GIS architectural application of “Multiplatform Architectural Spatiotemporal” and data analysis methods of “Triple Exponential Smoothing” and “Spatial Interpolation” as our significant scientific contribution. This research consists of 2 (two) parts, namely attribute data prediction using TES method and spatial data prediction using Inverse Distance Weight (IDW) method. We conduct our research in 19 subdistricts in the Boyolali Regency, Central Java Province, Indonesia. Our main research data is the biweekly rainfall data in 2000-2016 Climatology, Meteorology, and Geophysics Agency (In Indonesia called Badan Meteorologi, Klimatologi, dan Geofisika) of Central Java Province and Laboratory of Plant Disease Observations Region V Surakarta, Central Java. The application architecture and analytical methodology of “Multiplatform Architectural Spatiotemporal” and spatial data analysis methodology of “Triple Exponential Smoothing” and “Spatial Interpolation” can be developed as a GIS application framework of rainfall distribution for various applied fields. The comparison between the TES and IDW methods show that relative to time series prediction, spatial interpolation exhibit values that are approaching actual. Spatial interpolation is closer to actual data because computed values are the rainfall data of the nearest location or the neighbour of sample values. However, the IDW’s main weakness is that some

  2. A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain

    Directory of Open Access Journals (Sweden)

    Nicolas Panel

    2017-09-01

    Full Text Available PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or “PB/LIE” free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

  3. A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain.

    Science.gov (United States)

    Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J; Simonson, Thomas

    2017-01-01

    PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or "PB/LIE" free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

  4. Generalized spin-ratio scaled MP2 method for accurate prediction of intermolecular interactions for neutral and ionic species.

    Science.gov (United States)

    Tan, Samuel; Barrera Acevedo, Santiago; Izgorodina, Ekaterina I

    2017-02-14

    The accurate calculation of intermolecular interactions is important to our understanding of properties in large molecular systems. The high computational cost of the current "gold standard" method, coupled cluster with singles and doubles and perturbative triples (CCSD(T), limits its application to small- to medium-sized systems. Second-order Møller-Plesset perturbation (MP2) theory is a cheaper alternative for larger systems, although at the expense of its decreased accuracy, especially when treating van der Waals complexes. In this study, a new modification of the spin-component scaled MP2 method was proposed for a wide range of intermolecular complexes including two well-known datasets, S22 and S66, and a large dataset of ionic liquids consisting of 174 single ion pairs, IL174. It was found that the spin ratio, ϵΔs=EINT(OS)EINT(SS), calculated as the ratio of the opposite-spin component to the same-spin component of the interaction correlation energy fell in the range of 0.1 and 1.6, in contrast to the range of 3-4 usually observed for the ratio of absolute correlation energy, ϵs=EOSESS, in individual molecules. Scaled coefficients were found to become negative when the spin ratio fell in close proximity to 1.0, and therefore, the studied intermolecular complexes were divided into two groups: (1) complexes with ϵΔsratio scaled second-order Møller-Plesset perturbation, treats both dispersion-driven and hydrogen-bonded complexes equally well, thus validating its robustness with respect to the interaction type ranging from ionic to neutral species at minimal computational cost.

  5. Can Fan-Beam Interactive Computed Tomography Accurately Predict Indirect Decompression in Minimally Invasive Spine Surgery Fusion Procedures?

    Science.gov (United States)

    Janssen, Insa; Lang, Gernot; Navarro-Ramirez, Rodrigo; Jada, Ajit; Berlin, Connor; Hilis, Aaron; Zubkov, Micaella; Gandevia, Lena; Härtl, Roger

    2017-11-01

    Recently, novel mobile intraoperative fan-beam computed tomography (CT) was introduced, allowing for real-time navigation and immediate intraoperative evaluation of neural decompression in spine surgery. This study sought to investigate whether intraoperatively assessed neural decompression during minimally invasive spine surgery (MISS) has a predictive value for clinical and radiographic outcome. A retrospective study of patients undergoing intraoperative CT (iCT)-guided extreme lateral interbody fusion or transforaminal lumbar interbody fusion was conducted. 1) Preoperative, 2) intraoperative (after cage implantation, 3) postoperative, and 4) follow-up radiographic and clinical parameters obtained from radiography or CT were quantified. Thirty-four patients (41 spinal segments) were analyzed. iCT-based navigation was successfully accomplished in all patients. Radiographic parameters showed significant improvement from preoperatively to intraoperatively after cage implantation in both MISS procedures (extreme lateral interbody fusion/transforaminal lumbar interbody fusion) (P ≤ 0.05). Radiologic parameters for both MISS fusion procedures did not show significant differences to the assessed radiographic measures at follow-up (P > 0.05). Radiologic outcome values did not decrease when compared intraoperatively (after cage implantation) to latest follow-up. Intraoperative fan-beam CT is capable of assessing neural decompression intraoperatively with high accuracy, allowing for precise prediction of radiologic outcome and earliest possible feedback during MISS fusion procedures. These findings are highly valuable for routine practice and future investigations toward finding a threshold for neural decompression that translates into clinical improvement. If sufficient neural decompression has been confirmed with iCT imaging studies, additional postoperative and/or follow-up imaging studies might no longer be required if patients remain asymptomatic. Copyright © 2017

  6. Colonisation of toxic environments drives predictable life-history evolution in livebearing fishes (Poeciliidae).

    Science.gov (United States)

    Riesch, Rüdiger; Plath, Martin; Schlupp, Ingo; Tobler, Michael; Brian Langerhans, R

    2014-01-01

    New World livebearing fishes (family Poeciliidae) have repeatedly colonised toxic, hydrogen sulphide-rich waters across their natural distribution. Physiological considerations and life-history theory predict that these adverse conditions should favour the evolution of larger offspring. Here, we examined nine poeciliid species that independently colonised toxic environments, and show that these fishes have indeed repeatedly evolved much larger offspring size at birth in sulphidic waters, thus uncovering a widespread pattern of predictable evolution. However, a second pattern, only indirectly predicted by theory, proved additionally common: a reduction in the number of offspring carried per clutch (i.e. lower fecundity). Our analyses reveal that this secondary pattern represents a mere consequence of a classic life-history trade-off combined with strong selection on offspring size alone. With such strong natural selection in extreme environments, extremophile organisms may commonly exhibit multivariate phenotypic shifts even though not all diverging traits necessarily represent adaptations to the extreme conditions. © 2013 John Wiley & Sons Ltd/CNRS.

  7. Generalized spin-ratio scaled MP2 method for accurate prediction of intermolecular interactions for neutral and ionic species

    Science.gov (United States)

    Tan, Samuel; Barrera Acevedo, Santiago; Izgorodina, Ekaterina I.

    2017-02-01

    The accurate calculation of intermolecular interactions is important to our understanding of properties in large molecular systems. The high computational cost of the current "gold standard" method, coupled cluster with singles and doubles and perturbative triples (CCSD(T), limits its application to small- to medium-sized systems. Second-order Møller-Plesset perturbation (MP2) theory is a cheaper alternative for larger systems, although at the expense of its decreased accuracy, especially when treating van der Waals complexes. In this study, a new modification of the spin-component scaled MP2 method was proposed for a wide range of intermolecular complexes including two well-known datasets, S22 and S66, and a large dataset of ionic liquids consisting of 174 single ion pairs, IL174. It was found that the spin ratio, ɛΔ s=E/INT O SEIN T S S , calculated as the ratio of the opposite-spin component to the same-spin component of the interaction correlation energy fell in the range of 0.1 and 1.6, in contrast to the range of 3-4 usually observed for the ratio of absolute correlation energy, ɛs=E/OSES S , in individual molecules. Scaled coefficients were found to become negative when the spin ratio fell in close proximity to 1.0, and therefore, the studied intermolecular complexes were divided into two groups: (1) complexes with ɛΔ s< 1 and (2) complexes with ɛΔ s≥ 1 . A separate set of coefficients was obtained for both groups. Exclusion of counterpoise correction during scaling was found to produce superior results due to decreased error. Among a series of Dunning's basis sets, cc-pVTZ and cc-pVQZ were found to be the best performing ones, with a mean absolute error of 1.4 kJ mol-1 and maximum errors below 6.2 kJ mol-1. The new modification, spin-ratio scaled second-order Møller-Plesset perturbation, treats both dispersion-driven and hydrogen-bonded complexes equally well, thus validating its robustness with respect to the interaction type ranging from ionic

  8. Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

    Science.gov (United States)

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

    Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing

  9. Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

    Science.gov (United States)

    Rahmati, Mehdi

    2017-08-01

    Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

  10. Asthma, Family History of Drug Allergy, and Age Predict Amoxicillin Allergy in Children.

    Science.gov (United States)

    Faitelson, Yoram; Boaz, Mona; Dalal, Ilan

    2017-12-06

    Suspected adverse reactions to amoxicillin are common, but there are no known factors that can predict amoxicillin allergy in children. In addition, methods used for the diagnosis of amoxicillin allergy are not standardized and their role in diagnosis is not clear. To identify predictive factors and to assess the role of skin test in the diagnosis of amoxicillin allergy in children. Children with a history of immediate (excluding anaphylaxis) or nonimmediate reactions to amoxicillin were tested by skin prick test, followed by oral graded challenge with amoxicillin. Clinical characteristics of the reaction before and after the challenge were recorded, and data of personal and relatives' drug allergies and atopy were collected for statistical analysis. Skin prick tests followed by an oral graded challenge with amoxicillin were performed on 133 children. The skin test result was not of clinical value because it was negative in all children. Three children (2%) had an immediate reaction and 7 children (5%) had a nonimmediate reaction. Asthma (odds ratio [OR], 0.12; 95% CI, 0.017-0.869; P = .03), family history of drug allergy (OR, 0.12; 95% CI, 0.026-0.613; P = .01), older age at reaction (OR, 0.837; 95% CI, 0.699-1; P = .05), and angioedema (OR, 0.22; 95% CI, 0.043-1.12; marginally significant at P = .069) were associated with reduced chance to pass the oral challenge. Skin prick test did not contribute to the diagnosis of amoxicillin allergy. The presence of asthma, family history of drug allergy, and older age at reaction can be used as predictive factors for true amoxicillin allergy in children. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  11. HDL size is more accurate than HDL cholesterol to predict carotid subclinical atherosclerosis in individuals classified as low cardiovascular risk.

    Science.gov (United States)

    Parra, Eliane Soler; Panzoldo, Natalia Baratella; Zago, Vanessa Helena de Souza; Scherrer, Daniel Zanetti; Alexandre, Fernanda; Bakkarat, Jamal; Nunes, Valeria Sutti; Nakandakare, Edna Regina; Quintão, Eder Carlos Rocha; Nadruz-Jr, Wilson; de Faria, Eliana Cotta; Sposito, Andrei C

    2014-01-01

    Misclassification of patients as low cardiovascular risk (LCR) remains a major concern and challenges the efficacy of traditional risk markers. Due to its strong association with cholesterol acceptor capacity, high-density lipoprotein (HDL) size has been appointed as a potential risk marker. Hence, we investigate whether HDL size improves the predictive value of HDL-cholesterol in the identification of carotid atherosclerotic burden in individuals stratified to be at LCR. 284 individuals (40-75 years) classified as LCR by the current US guidelines were selected in a three-step procedure from primary care centers of the cities of Campinas and Americana, SP, Brazil. Apolipoprotein B-containing lipoproteins were precipitated by polyethylene glycol and HDL size was measured by dynamic light scattering (DLS) technique. Participants were classified in tertiles of HDL size (8.22 nm). Carotid intima-media thickness (cIMT) 8.22 nm was independently associated with low cIMT in either unadjusted and adjusted models for age, gender and Homeostasis Model Assessment 2 index for insulin sensitivity, ethnicity and body mass index (Odds ratio 0.23; 95% confidence interval 0.07-0.74, p = 0.013). The mean HDL size estimated with DLS constitutes a better predictor for subclinical carotid atherosclerosis than the conventional measurements of plasma HDL-cholesterol in individuals classified as LCR.

  12. HDL size is more accurate than HDL cholesterol to predict carotid subclinical atherosclerosis in individuals classified as low cardiovascular risk.

    Directory of Open Access Journals (Sweden)

    Eliane Soler Parra

    Full Text Available Misclassification of patients as low cardiovascular risk (LCR remains a major concern and challenges the efficacy of traditional risk markers. Due to its strong association with cholesterol acceptor capacity, high-density lipoprotein (HDL size has been appointed as a potential risk marker. Hence, we investigate whether HDL size improves the predictive value of HDL-cholesterol in the identification of carotid atherosclerotic burden in individuals stratified to be at LCR.284 individuals (40-75 years classified as LCR by the current US guidelines were selected in a three-step procedure from primary care centers of the cities of Campinas and Americana, SP, Brazil. Apolipoprotein B-containing lipoproteins were precipitated by polyethylene glycol and HDL size was measured by dynamic light scattering (DLS technique. Participants were classified in tertiles of HDL size (8.22 nm. Carotid intima-media thickness (cIMT 8.22 nm was independently associated with low cIMT in either unadjusted and adjusted models for age, gender and Homeostasis Model Assessment 2 index for insulin sensitivity, ethnicity and body mass index (Odds ratio 0.23; 95% confidence interval 0.07-0.74, p = 0.013.The mean HDL size estimated with DLS constitutes a better predictor for subclinical carotid atherosclerosis than the conventional measurements of plasma HDL-cholesterol in individuals classified as LCR.

  13. Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.

    Science.gov (United States)

    Abelin, Jennifer G; Keskin, Derin B; Sarkizova, Siranush; Hartigan, Christina R; Zhang, Wandi; Sidney, John; Stevens, Jonathan; Lane, William; Zhang, Guang Lan; Eisenhaure, Thomas M; Clauser, Karl R; Hacohen, Nir; Rooney, Michael S; Carr, Steven A; Wu, Catherine J

    2017-02-21

    Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Predicting the effectiveness of extracorporeal shock wave lithotripsy on urinary tract stones. Risk groups for accurate retreatment.

    Science.gov (United States)

    Hevia, M; García, Á; Ancizu, F J; Merino, I; Velis, J M; Tienza, A; Algarra, R; Doménech, P; Diez-Caballero, F; Rosell, D; Pascual, J I; Robles, J E

    2017-09-01

    Extracorporeal shock wave lithotripsy (ESWL) is a non-invasive, safe and effective treatment for urinary tract lithiasis. Its effectiveness varies depending on the location and size of the stones as well as other factors; several sessions are occasionally required. The objective is to attempt to predict its success or failure, when the influential variables are known beforehand. We analysed 211 patients who had had previous CT scans and were treated with ESWL between 2010 and 2014. The influential variables in requiring retreatment were studied using binary logistic regression models (univariate and multivariate analysis): maximum density, maximum diameter, area, location, disintegration and distance from the adipose panniculus. With the influential variables, a risk model was designed by assessing all possible combinations with logistic regression (version 20.0 IBM SPSS). The independent influential variables on the need for retreatment are: maximum density >864HU, maximum diameter >7.5mm and pyelocaliceal location. Using these variables, the best model includes 3risk groups with a probability of requiring significantly different retreatment: group 1-low risk (0 variables) with 20.2%; group 2-intermediate risk (1-2 variables) with 49.2%; and group 3-high risk (3 variables) with 62.5%. The density, maximum diameter and pyelocaliceal location of the stones are determinant factors in terms of the effectiveness of treatment with ESWL. Using these variables, which can be obtained in advance of deciding on a treatment, the designed risk model provides a precise approach in choosing the most appropriate treatment for each particular case. Copyright © 2017 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  15. Infectious titres of sheep scrapie and bovine spongiform encephalopathy agents cannot be accurately predicted from quantitative laboratory test results.

    Science.gov (United States)

    González, Lorenzo; Thorne, Leigh; Jeffrey, Martin; Martin, Stuart; Spiropoulos, John; Beck, Katy E; Lockey, Richard W; Vickery, Christopher M; Holder, Thomas; Terry, Linda

    2012-11-01

    It is widely accepted that abnormal forms of the prion protein (PrP) are the best surrogate marker for the infectious agent of prion diseases and, in practice, the detection of such disease-associated (PrP(d)) and/or protease-resistant (PrP(res)) forms of PrP is the cornerstone of diagnosis and surveillance of the transmissible spongiform encephalopathies (TSEs). Nevertheless, some studies question the consistent association between infectivity and abnormal PrP detection. To address this discrepancy, 11 brain samples of sheep affected with natural scrapie or experimental bovine spongiform encephalopathy were selected on the basis of the magnitude and predominant types of PrP(d) accumulation, as shown by immunohistochemical (IHC) examination; contra-lateral hemi-brain samples were inoculated at three different dilutions into transgenic mice overexpressing ovine PrP and were also subjected to quantitative analysis by three biochemical tests (BCTs). Six samples gave 'low' infectious titres (10⁶·⁵ to 10⁶·⁷ LD₅₀ g⁻¹) and five gave 'high titres' (10⁸·¹ to ≥ 10⁸·⁷ LD₅₀ g⁻¹) and, with the exception of the Western blot analysis, those two groups tended to correspond with samples with lower PrP(d)/PrP(res) results by IHC/BCTs. However, no statistical association could be confirmed due to high individual sample variability. It is concluded that although detection of abnormal forms of PrP by laboratory methods remains useful to confirm TSE infection, infectivity titres cannot be predicted from quantitative test results, at least for the TSE sources and host PRNP genotypes used in this study. Furthermore, the near inverse correlation between infectious titres and Western blot results (high protease pre-treatment) argues for a dissociation between infectivity and PrP(res).

  16. Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

    Science.gov (United States)

    Powell, Erica Dion

    2013-01-01

    This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

  17. In 'big bang' major incidents do triage tools accurately predict clinical priority?: a systematic review of the literature.

    Science.gov (United States)

    Kilner, T M; Brace, S J; Cooke, M W; Stallard, N; Bleetman, A; Perkins, G D

    2011-05-01

    The term "big bang" major incidents is used to describe sudden, usually traumatic,catastrophic events, involving relatively large numbers of injured individuals, where demands on clinical services rapidly outstrip the available resources. Triage tools support the pre-hospital provider to prioritise which patients to treat and/or transport first based upon clinical need. The aim of this review is to identify existing triage tools and to determine the extent to which their reliability and validity have been assessed. A systematic review of the literature was conducted to identify and evaluate published data validating the efficacy of the triage tools. Studies using data from trauma patients that report on the derivation, validation and/or reliability of the specific pre-hospital triage tools were eligible for inclusion.Purely descriptive studies, reviews, exercises or reports (without supporting data) were excluded. The search yielded 1982 papers. After initial scrutiny of title and abstract, 181 papers were deemed potentially applicable and from these 11 were identified as relevant to this review (in first figure). There were two level of evidence one studies, three level of evidence two studies and six level of evidence three studies. The two level of evidence one studies were prospective validations of Clinical Decision Rules (CDR's) in children in South Africa, all the other studies were retrospective CDR derivation, validation or cohort studies. The quality of the papers was rated as good (n=3), fair (n=7), poor (n=1). There is limited evidence for the validity of existing triage tools in big bang major incidents.Where evidence does exist it focuses on sensitivity and specificity in relation to prediction of trauma death or severity of injury based on data from single or small number patient incidents. The Sacco system is unique in combining survivability modelling with the degree by which the system is overwhelmed in the triage decision system. The

  18. Physiologically based pharmacokinetic modelling and in vivo [I]/Ki accurately predict P-glycoproteinmediated drug-drug interactions with dabigatran etexilate

    Science.gov (United States)

    Zhao, Yuansheng; Hu, Zhe-Yi

    2014-01-01

    Background and purpose In vitro inhibitory potency (Ki)-based predictions of P-glycoprotein (P-gp)-mediated drug-drug interactions (DDIs) are hampered by the substantial variability in inhibitory potency. In this study, in vivo-based [I]/Ki values were used to predict the DDI risks of a P-gp substrate dabigatran etexilate (DABE) using physiologically based pharmacokinetic (PBPK) modelling. Experimental approach A baseline PBPK model was established with digoxin, a known P-gp substrate. The Km (P-gp transport) of digoxin in the baseline PBPK model was adjusted to Kmi to fit the change of digoxin pharmacokinetics in the presence of a P-gp inhibitor. Then ‘in vivo’ [I]/Ki of this P-gp inhibitor was calculated using Kmi/Km. Baseline PBPK model was developed for DABE, and the ‘in vivo’ [I]/Ki was incorporated into this model to simulate the static effect of P-gp inhibitor on DABE pharmacokinetics. This approach was verified by comparing the observed and the simulated DABE pharmacokinetics in the presence of five different P-gp inhibitors. Key results This approach accurately predicted the effects of five P-gp inhibitors on DABE pharmacokinetics (98–133% and 89–104% for the ratios of AUC and Cmax respectively). The effects of 16 other P-gp inhibitors on the pharmacokinetics of DABE were also confidently simulated. Conclusions and implications ‘In vivo’ [I]/Ki and PBPK modelling, used in combination, can accurately predict P-gp-mediated DDIs. The described framework provides a mechanistic basis for the proper design of clinical DDI studies, as well as avoiding unnecessary clinical DDI studies. PMID:24283665

  19. Life history trade-off moderates model predictions of diversity loss from climate change.

    Directory of Open Access Journals (Sweden)

    Helen Moor

    Full Text Available Climate change can trigger species range shifts, local extinctions and changes in diversity. Species interactions and dispersal capacity are important mediators of community responses to climate change. The interaction between multispecies competition and variation in dispersal capacity has recently been shown to exacerbate the effects of climate change on diversity and to increase predictions of extinction risk dramatically. Dispersal capacity, however, is part of a species' overall ecological strategy and are likely to trade off with other aspects of its life history that influence population growth and persistence. In plants, a well-known example is the trade-off between seed mass and seed number. The presence of such a trade-off might buffer the diversity loss predicted by models with random but neutral (i.e. not impacting fitness otherwise differences in dispersal capacity. Using a trait-based metacommunity model along a warming climatic gradient the effect of three different dispersal scenarios on model predictions of diversity change were compared. Adding random variation in species dispersal capacity caused extinctions by the introduction of strong fitness differences due an inherent property of the dispersal kernel. Simulations including a fitness-equalising trade-off based on empirical relationships between seed mass (here affecting dispersal distance, establishment probability, and seedling biomass and seed number (fecundity maintained higher initial species diversity and predicted lower extinction risk and diversity loss during climate change than simulations with variable dispersal capacity. Large seeded species persisted during climate change, but developed lags behind their climate niche that may cause extinction debts. Small seeded species were more extinction-prone during climate change but tracked their niches through dispersal and colonisation, despite competitive resistance from residents. Life history trade-offs involved in

  20. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    Science.gov (United States)

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  1. New analytical model for the ozone electronic ground state potential surface and accurate ab initio vibrational predictions at high energy range.

    Science.gov (United States)

    Tyuterev, Vladimir G; Kochanov, Roman V; Tashkun, Sergey A; Holka, Filip; Szalay, Péter G

    2013-10-07

    An accurate description of the complicated shape of the potential energy surface (PES) and that of the highly excited vibration states is of crucial importance for various unsolved issues in the spectroscopy and dynamics of ozone and remains a challenge for the theory. In this work a new analytical representation is proposed for the PES of the ground electronic state of the ozone molecule in the range covering the main potential well and the transition state towards the dissociation. This model accounts for particular features specific to the ozone PES for large variations of nuclear displacements along the minimum energy path. The impact of the shape of the PES near the transition state (existence of the "reef structure") on vibration energy levels was studied for the first time. The major purpose of this work was to provide accurate theoretical predictions for ozone vibrational band centres at the energy range near the dissociation threshold, which would be helpful for understanding the very complicated high-resolution spectra and its analyses currently in progress. Extended ab initio electronic structure calculations were carried out enabling the determination of the parameters of a minimum energy path PES model resulting in a new set of theoretical vibrational levels of ozone. A comparison with recent high-resolution spectroscopic data on the vibrational levels gives the root-mean-square deviations below 1 cm(-1) for ozone band centres up to 90% of the dissociation energy. New ab initio vibrational predictions represent a significant improvement with respect to all previously available calculations.

  2. Prostate cancer risk prediction based on complete prostate cancer family history.

    Science.gov (United States)

    Albright, Frederick; Stephenson, Robert A; Agarwal, Neeraj; Teerlink, Craig C; Lowrance, William T; Farnham, James M; Albright, Lisa A Cannon

    2015-03-01

    Prostate cancer (PC) relative risks (RRs) are typically estimated based on status of close relatives or presence of any affected relatives. This study provides RR estimates using extensive and specific PC family history. A retrospective population-based study was undertaken to estimate RRs for PC based on complete family history of PC. A total of 635,443 males, all with ancestral genealogy data, were analyzed. RRs for PC were determined based upon PC rates estimated from males with no PC family history (without PC in first, second, or third degree relatives). RRs were determined for a variety of constellations, for example, number of first through third degree relatives; named (grandfather, father, uncle, cousins, brothers); maternal, paternal relationships, and age of onset. In the 635,443 males analyzed, 18,105 had PC. First-degree RRs ranged from 2.46 (=1 first-degree relative affected, CI = 2.39-2.53) to 7.65 (=4 first-degree relatives affected, CI = 6.28-9.23). Second-degree RRs for probands with 0 affected first-degree relatives ranged from 1.51 (≥1 second-degree relative affected, CI = 1.47-1.56) to 3.09 (≥5 second-degree relatives affected, CI = 2.32-4.03). Third-degree RRs with 0 affected first- and 0 affected second-degree relatives ranged from 1.15 (≥1 affected third-degree relative, CI = 1.12-1.19) to 1.50 (≥5 affected third-degree relatives, CI = 1.35-1.66). RRs based on age at diagnosis were higher for earlier age at diagnoses; for example, RR = 5.54 for ≥1 first-degree relative diagnosed before age 50 years (CI = 1.12-1.19) and RR = 1.78 for >1 second-degree relative diagnosed before age 50 years, CI = 1.33, 2.33. RRs for equivalent maternal versus paternal family history were not significantly different. A more complete PC family history using close and distant relatives and age at diagnosis results in a wider range of estimates of individual RR that are potentially more accurate than RRs estimated

  3. Indirect color prediction of amorphous carbohydrate melts as a function of thermal history.

    Science.gov (United States)

    van Sleeuwen, Rutger M T; Gosse, Anaїck J; Normand, Valery

    2013-07-01

    Glassy carbohydrate microcapsules are widely used for the encapsulation of flavors in food applications, and are made using various thermal processes (for example, extrusion). During manufacturing, these carbohydrate melts are held at elevated temperatures and color can form due to nonenzymatic browning reactions. These reactions can negatively or positively affect the color and flavor of microcapsules. The rate of color formation of maltodextrin and maltodextrin/sucrose melts at elevated temperatures was determined spectrophotometrically and was found to follow pseudo zero-order kinetics. The effect of temperature was adequately modeled by an Arrhenius relationship. Reaction rate constants and Arrhenius parameters were determined for individual wavelengths in the visible range (360 to 700 nm at 1 nm intervals). Transient processes (temperature changes with time) were modeled as a sequence of small isothermal events, and the equivalent thermal history at a reference temperature calculated using the Arrhenius relationship. Therefore, spectral transmittance curves could be predicted with knowledge of the time/temperature relationship. Validation was conducted by subjecting both melts to a transient thermal history. Experimental transmittance spectrum compared favorably against predicted values. These spectra were optionally converted to any desirable color space (for example, CIELAB, XYZ, RGB) or derived parameter (for example, Browning Index). The tool could be used to better control nonenzymatic browning reactions in industrial food processes. © 2013 Institute of Food Technologists®

  4. Radiology clinical synopsis: a simple solution for obtaining an adequate clinical history for the accurate reporting of imaging studies on patients in intensive care units

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Mervyn D. [Riley Hospital for Children, Indianapolis, IN (United States); Alam, Khurshaid [Indiana University, School of Medicine, Indianapolis, IN (United States)

    2005-09-01

    Lack of clinical history on radiology requisitions is a universal problem. We describe a simple Web-based system that readily provides radiology-relevant clinical history to the radiologist reading radiographs of intensive care unit (ICU) patients. Along with the relevant history, which includes primary and secondary diagnoses, disease progression and complications, the system provides the patient's name, record number and hospital location. This information is immediately available to reporting radiologists. New clinical information is immediately entered on-line by the radiologists as they are reviewing images. After patient discharge, the data are stored and immediately available if the patient is readmitted. The system has been in routine clinical use in our hospital for nearly 2 years. (orig.)

  5. Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'.

    Science.gov (United States)

    Draper, John; Enot, David P; Parker, David; Beckmann, Manfred; Snowdon, Stuart; Lin, Wanchang; Zubair, Hassan

    2009-07-21

    Metabolomics experiments using Mass Spectrometry (MS) technology measure the mass to charge ratio (m/z) and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of ionised. In reality the annotation process is confounded by the fact that many ionisation products will be not only molecular isotopes but also salt/solvent adducts and neutral loss fragments of original metabolites. This report describes an annotation strategy that will allow searching based on all potential ionisation products predicted to form during electrospray ionisation (ESI). Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50%) of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data. We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to

  6. Can Kohn-Sham density functional theory predict accurate charge distributions for both single-reference and multi-reference molecules?

    Science.gov (United States)

    Verma, Pragya; Truhlar, Donald G

    2017-05-24

    Dipole moments are the first moment of electron density and are fundamental quantities that are often available from experiments. An exchange-correlation functional that leads to an accurate representation of the charge distribution of a molecule should accurately predict the dipole moments of the molecule. It is well known that Kohn-Sham density functional theory (DFT) is more accurate for the energetics of single-reference systems than for the energetics of multi-reference ones, but there has been less study of charge distributions. In this work, we benchmark 48 density functionals chosen with various combinations of ingredients, against accurate experimental data for dipole moments of 78 molecules, in particular 55 single-reference molecules and 23 multi-reference ones. We chose both organic and inorganic molecules, and within the category of inorganic molecules there are both main-group and transition-metal-containing molecules, with some of them being multi-reference. As one would expect, the multi-reference molecules are not as well described by single-reference DFT, and the functionals tested in this work do show larger mean unsigned errors (MUEs) for the 23 multi-reference molecules than the single-reference ones. Five of the 78 molecules have relatively large experimental error bars and were therefore not included in calculating the overall MUEs. For the 73 molecules not excluded, we find that three of the hybrid functionals, B97-1, PBE0, and TPSSh (each with less than or equal to 25% Hartree-Fock (HF) exchange), the range-separated hybrid functional, HSE06 (with HF exchange decreasing from 25% to 0 as interelectronic distance increases), and the hybrid functional, PW6B95 (with 28% HF exchange) are the best performing functionals with each yielding an MUE of 0.18 D. Perhaps the most significant finding of this study is that there exists great similarity among the success rate of various functionals in predicting dipole moments. In particular, of 39

  7. "Writing Wasn't Really Stressed, Accurate Historical Analysis Was Stressed": Student Perceptions of In-Class Writing in the Inverted, General Education, University History Survey Course

    Science.gov (United States)

    Murphree, Daniel S.

    2014-01-01

    Taking introductory history courses and writing analytical essays are not the favorite activities of most first-year university students. Undergraduates, seemingly, would rather enroll in classes that pertain only to their majors or job-preparation regimen. If forced to take General Education Program (GEP) courses, students typically favor those…

  8. Life-history traits and landscape characteristics predict macro-moth responses to forest fragmentation.

    Science.gov (United States)

    Slade, Eleanor M; Merckx, Thomas; Riutta, Terhi; Bebber, Daniel P; Redhead, David; Riordan, Philip; Macdonald, David W

    2013-07-01

    How best to manage forest patches, mitigate the consequences of forest fragmentation, and enable landscape permeability are key questions facing conservation scientists and managers. Many temperate forests have become increasingly fragmented, resulting in reduced interior forest habitat, increased edge habitats, and reduced connectivity. Using a citizen science landscape-scale mark-release-recapture study on 87 macro-moth species, we investigated how both life-history traits and landscape characteristics predicted macro-moth responses to forest fragmentation. Wingspan, wing shape, adult feeding, and larval feeding guild predicted macro-moth mobility, although the predictive power of wingspan and wing shape depended on the species' affinity to the forest. Solitary trees and small fragments functioned as "stepping stones," especially when their landscape connectivity was increased, by being positioned within hedgerows or within a favorable matrix. Mobile forest specialists were most affected by forest fragmentation: despite their high intrinsic dispersal capability, these species were confined mostly to the largest of the forest patches due to their strong affinity for the forest habitat, and were also heavily dependent on forest connectivity in order to cross the agricultural matrix. Forest fragments need to be larger than five hectares and to have interior forest more than 100 m from the edge in order to sustain populations of forest specialists. Our study provides new insights into the movement patterns of a functionally important insect group, with implications for the landscape-scale management of forest patches within agricultural landscapes.

  9. Suicidal behavior in children and adolescents: does a history of trauma predict less severe suicidal attempts?

    Science.gov (United States)

    Koutek, Jirí; Kocourkova, Jirina; Hladikova, Marie; Hrdlicka, Michal

    2009-03-01

    The aim of this study was to identify risk factors and possible predictors of severity of suicidal behavior of children and adolescents. Seventy-seven patients (15 boys and 62 girls) aged 15.5+/-1.6 years on average, hospitalized due to a suicidal attempt in the department of pediatric psychiatry, were examined. Structured interviews with patients and their parents were used to clinically assess circumstances of suicidal behavior, relevant risk factors and severity of suicidal behavior. The results indicated that patients with any previous traumatic experience tended to have somatically less severe suicidal attempts (p=0.050). Intensity of suicidal intent was associated with a history of depression (p=0.014) and anxiety disorders (p=0.004), and the current stress from a mental disorder (p=0.014). Somatic severity of suicidal behavior was significantly associated with intensity of suicidal intent (p=0.014). A history of any trauma (previous traumatic experience predicted less severe suicidal behavior, p=0.053) and the current stress from sexual problems (p=0.067) were identified as predictors of somatic severity of suicidality. These two predictors showed only a trend level of significance. The only significant predictor of intensity of suicidal intent was the current stress from a mental illness (p=0.017). Several risk factors of somatic severity of suicidal behavior and intensity of suicidal intent were described. The most important finding of the study was the association between a history of psychological trauma and a tendency to have less somatically severe suicidal behavior.

  10. Life-history predicts past and present population connectivity in two sympatric sea stars.

    Science.gov (United States)

    Puritz, Jonathan B; Keever, Carson C; Addison, Jason A; Barbosa, Sergio S; Byrne, Maria; Hart, Michael W; Grosberg, Richard K; Toonen, Robert J

    2017-06-01

    Life-history traits, especially the mode and duration of larval development, are expected to strongly influence the population connectivity and phylogeography of marine species. Comparative analysis of sympatric, closely related species with differing life histories provides the opportunity to specifically investigate these mechanisms of evolution but have been equivocal in this regard. Here, we sample two sympatric sea stars across the same geographic range in temperate waters of Australia. Using a combination of mitochondrial DNA sequences, nuclear DNA sequences, and microsatellite genotypes, we show that the benthic-developing sea star, Parvulastra exigua, has lower levels of within- and among-population genetic diversity, more inferred genetic clusters, and higher levels of hierarchical and pairwise population structure than Meridiastra calcar, a species with planktonic development. While both species have populations that have diverged since the middle of the second glacial period of the Pleistocene, most P. exigua populations have origins after the last glacial maxima (LGM), whereas most M. calcar populations diverged long before the LGM. Our results indicate that phylogenetic patterns of these two species are consistent with predicted dispersal abilities; the benthic-developing P. exigua shows a pattern of extirpation during the LGM with subsequent recolonization, whereas the planktonic-developing M. calcar shows a pattern of persistence and isolation during the LGM with subsequent post-Pleistocene introgression.

  11. Risk assessment, life history strategies, and turtles: could declines be prevented or predicted?

    Science.gov (United States)

    Burger, J; Garber, S D

    1995-12-01

    The process of ecological risk assessment should involve the ability to predict adverse outcomes of particular environmental contaminants or human intrusions. Ecological risk assessment generally focuses on populations, communities, and ecosystems, rather than on individual health. We explore the importance of life history strategies of aquatic turtles to their risk from environmental contaminants and other human activities using three examples: the wood turtle Clemmys insculpta, a freshwater species; the diamondback terrapin Malaclemys terrapin, a littoral species; and marine turtles as a group. These turtles are partly herbivorous and are at low or intermediate levels on the food chain, yet are particularly vulnerable due to their life history strategies of being long-lived with relatively low survival of young. They suffer a variety of natural mortality factors that include predation, starvation, and disease, as well as inundation and destruction of nesting beaches and their eggs by storms. Yet they also face a number of anthropogenic hazards, including toxic chemicals and floatables (plastics); capture for food, other products, and pets; incidental mortality in fishing gear; disturbance while nesting or moving on land; injuries or death by collision with boats; and increased predator exposure because of humans. The three turtle species (or groups of species) examined have experienced these natural and anthropogenic pressures differentially, with resultant differences in the rates of population declines. Because they are lower on the food chain than other obligate carnivores, they are less vulnerable to toxics, and to date, toxics seem a relatively inconsequential environmental risk to turtles.

  12. Amphibian species traits, evolutionary history and environment predict Batrachochytrium dendrobatidis infection patterns, but not extinction risk.

    Science.gov (United States)

    Greenberg, Dan A; Palen, Wendy J; Mooers, Arne Ø

    2017-12-01

    The fungal pathogen Batrachochytrium dendrobatidis (B. dendrobatidis) has emerged as a major agent of amphibian extinction, requiring conservation intervention for many susceptible species. Identifying susceptible species is challenging, but many aspects of species biology are predicted to influence the evolution of host resistance, tolerance, or avoidance strategies towards disease. In turn, we may expect species exhibiting these distinct strategies to differ in their ability to survive epizootic disease outbreaks. Here, we test for phylogenetic and trait-based patterns of B. dendrobatidis infection risk and infection intensity among 302 amphibian species by compiling a global data set of B. dendrobatidis infection surveys across 95 sites. We then use best-fit models that associate traits, taxonomy and environment with B. dendrobatidis infection risk and intensity to predict host disease mitigation strategies (tolerance, resistance, avoidance) for 122 Neotropical amphibian species that experienced epizootic B. dendrobatidis outbreaks, and noted species persistence or extinction from these events. Aspects of amphibian species life history, habitat use and climatic niche were consistently linked to variation in B. dendrobatidis infection patterns across sites around the world. However, predicted B. dendrobatidis infection risk and intensity based on site environment and species traits did not reveal a consistent pattern between the predicted host disease mitigation strategy and extinction outcome. This suggests that either tolerant or resistant species may have no advantage in ameliorating disease during epizootic events, or that other factors drive the persistence of amphibian populations during chytridiomycosis outbreaks. These results suggest that using a trait-based approach may allow us to identify species with resistance or tolerance to endemic B. dendrobatidis infections, but that this approach may be insufficient to ultimately identify species at

  13. Prediction of Happy-Sad mood from daily behaviors and previous sleep history.

    Science.gov (United States)

    Sano, Akane; Yu, Amy Z; McHill, Andrew W; Phillips, Andrew J K; Taylor, Sara; Jaques, Natasha; Klerman, Elizabeth B; Picard, Rosalind W

    2015-01-01

    We collected and analyzed subjective and objective data using surveys and wearable sensors worn day and night from 68 participants for ~30 days each, to address questions related to the relationships among sleep duration, sleep irregularity, self-reported Happy-Sad mood and other daily behavioral factors in college students. We analyzed this behavioral and physiological data to (i) identify factors that classified the participants into Happy-Sad mood using support vector machines (SVMs); and (ii) analyze how accurately sleep duration and sleep regularity for the past 1-5 days classified morning Happy-Sad mood. We found statistically significant associations amongst Sad mood and poor health-related factors. Behavioral factors including the frequency of negative social interactions, and negative emails, and total academic activity hours showed the best performance in separating the Happy-Sad mood groups. Sleep regularity and sleep duration predicted daily Happy-Sad mood with 65-80% accuracy. The number of nights giving the best prediction of Happy-Sad mood varied for different individuals.

  14. Discovery of a general method of solving the Schrödinger and dirac equations that opens a way to accurately predictive quantum chemistry.

    Science.gov (United States)

    Nakatsuji, Hiroshi

    2012-09-18

    Just as Newtonian law governs classical physics, the Schrödinger equation (SE) and the relativistic Dirac equation (DE) rule the world of chemistry. So, if we can solve these equations accurately, we can use computation to predict chemistry precisely. However, for approximately 80 years after the discovery of these equations, chemists believed that they could not solve SE and DE for atoms and molecules that included many electrons. This Account reviews ideas developed over the past decade to further the goal of predictive quantum chemistry. Between 2000 and 2005, I discovered a general method of solving the SE and DE accurately. As a first inspiration, I formulated the structure of the exact wave function of the SE in a compact mathematical form. The explicit inclusion of the exact wave function's structure within the variational space allows for the calculation of the exact wave function as a solution of the variational method. Although this process sounds almost impossible, it is indeed possible, and I have published several formulations and applied them to solve the full configuration interaction (CI) with a very small number of variables. However, when I examined analytical solutions for atoms and molecules, the Hamiltonian integrals in their secular equations diverged. This singularity problem occurred in all atoms and molecules because it originates from the singularity of the Coulomb potential in their Hamiltonians. To overcome this problem, I first introduced the inverse SE and then the scaled SE. The latter simpler idea led to immediate and surprisingly accurate solution for the SEs of the hydrogen atom, helium atom, and hydrogen molecule. The free complement (FC) method, also called the free iterative CI (free ICI) method, was efficient for solving the SEs. In the FC method, the basis functions that span the exact wave function are produced by the Hamiltonian of the system and the zeroth-order wave function. These basis functions are called complement

  15. The Need for Accurate Risk Prediction Models for Road Mapping, Shared Decision Making and Care Planning for the Elderly with Advanced Chronic Kidney Disease.

    Science.gov (United States)

    Stryckers, Marijke; Nagler, Evi V; Van Biesen, Wim

    2016-11-01

    As people age, chronic kidney disease becomes more common, but it rarely leads to end-stage kidney disease. When it does, the choice between dialysis and conservative care can be daunting, as much depends on life expectancy and personal expectations of medical care. Shared decision making implies adequately informing patients about their options, and facilitating deliberation of the available information, such that decisions are tailored to the individual's values and preferences. Accurate estimations of one's risk of progression to end-stage kidney disease and death with or without dialysis are essential for shared decision making to be effective. Formal risk prediction models can help, provided they are externally validated, well-calibrated and discriminative; include unambiguous and measureable variables; and come with readily applicable equations or scores. Reliable, externally validated risk prediction models for progression of chronic kidney disease to end-stage kidney disease or mortality in frail elderly with or without chronic kidney disease are scant. Within this paper, we discuss a number of promising models, highlighting both the strengths and limitations physicians should understand for using them judiciously, and emphasize the need for external validation over new development for further advancing the field.

  16. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  17. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.

  18. Orbitofrontal Cortex Signals Expected Outcomes with Predictive Codes When Stable Contingencies Promote the Integration of Reward History.

    Science.gov (United States)

    Riceberg, Justin S; Shapiro, Matthew L

    2017-02-22

    Memory can inform goal-directed behavior by linking current opportunities to past outcomes. The orbitofrontal cortex (OFC) may guide value-based responses by integrating the history of stimulus-reward associations into expected outcomes, representations of predicted hedonic value and quality. Alternatively, the OFC may rapidly compute flexible "online" reward predictions by associating stimuli with the latest outcome. OFC neurons develop predictive codes when rats learn to associate arbitrary stimuli with outcomes, but the extent to which predictive coding depends on most recent events and the integrated history of rewards is unclear. To investigate how reward history modulates OFC activity, we recorded OFC ensembles as rats performed spatial discriminations that differed only in the number of rewarded trials between goal reversals. The firing rate of single OFC neurons distinguished identical behaviors guided by different goals. When >20 rewarded trials separated goal switches, OFC ensembles developed stable and anticorrelated population vectors that predicted overall choice accuracy and the goal selected in single trials. When rewarded trials separated goal switches, OFC population vectors decorrelated rapidly after each switch, but did not develop anticorrelated firing patterns or predict choice accuracy. The results show that, whereas OFC signals respond rapidly to contingency changes, they predict choices only when reward history is relatively stable, suggesting that consecutive rewarded episodes are needed for OFC computations that integrate reward history into expected outcomes.SIGNIFICANCE STATEMENT Adapting to changing contingencies and making decisions engages the orbitofrontal cortex (OFC). Previous work shows that OFC function can either improve or impair learning depending on reward stability, suggesting that OFC guides behavior optimally when contingencies apply consistently. The mechanisms that link reward history to OFC computations remain obscure

  19. Predicting mental conditions based on "history of present illness" in psychiatric notes with deep neural networks.

    Science.gov (United States)

    Tran, Tung; Kavuluru, Ramakanth

    2017-11-01

    Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenario by providing the first set of neuropsychiatric notes to participants. This study summarizes our efforts and results in proposing a novel data use case for this dataset as part of the third track in this shared task. We explore the feasibility and effectiveness of predicting a set of common mental conditions a patient has based on the short textual description of patient's history of present illness typically occurring in the beginning of a psychiatric initial evaluation note. We clean and process the 1000 records made available through the N-GRID clinical NLP task into a key-value dictionary and build a dataset of 986 examples for which there is a narrative for history of present illness as well as Yes/No responses with regards to presence of specific mental conditions. We propose two independent deep neural network models: one based on convolutional neural networks (CNN) and another based on recurrent neural networks with hierarchical attention (ReHAN), the latter of which allows for interpretation of model decisions. We conduct experiments to compare these methods to each other and to baselines based on linear models and named entity recognition (NER). Our CNN model with optimized thresholding of output probability estimates achieves best overall mean micro-F score of 63.144% for 11 common mental conditions with statistically significant gains (ptext segment averaging 300 words, it is a good predictor for a few conditions such as anxiety, depression, panic disorder, and attention deficit hyperactivity disorder. Proposed CNN and RNN models outperform baseline approaches and complement each other when evaluating on a per-label basis. Copyright © 2017. Published by Elsevier Inc.

  20. Profiling crop pollinators: life history traits predict habitat use and crop visitation by Mediterranean wild bees.

    Science.gov (United States)

    Pisanty, Gideon; Mandelik, Yael

    2015-04-01

    Wild pollinators, bees in particular, may greatly contribute to crop pollination and provide a safety net against declines in commercial pollinators. However, the identity, life history traits, and environmental sensitivities of main crop pollinator species.have received limited attention. These are crucial for predicting pollination services of different communities and for developing management practices that enhance crop pollinators. We sampled wild bees in three crop systems (almond, confection sunflower, and seed watermelon) in a mosaic Israeli Mediterranean landscape. Bees were sampled in field/orchard edges and interiors, and in seminatural scrub surrounding the fields/orchards. We also analyzed land cover at 50-2500 m radii around fields/orchards. We used this data to distinguish crop from non-crop pollinators based on a set of life history traits (nesting, lecty, sociality, body size) linked to habitat preference and crop visitation. Bee abundance and species richness decreased from the surrounding seminatural habitat to the field/orchard interior, especially across the seminatural habitat-field edge ecotone. Thus, although rich bee communities were found near fields, only small fractions crossed the ecotone and visited crop flowers in substantial numbers. The bee assemblage in agricultural fields/orchards and on crop flowers was dominated by ground-nesting bees of the tribe Halictini, which tend to nest within fields. Bees' habitat preferences were determined mainly by nesting guild, whereas crop visitation was determined mainly by sociality. Lecty and body size also affected both measures. The percentage of surrounding seminatural habitat at 250-2500 m radii had a positive effect on wild bee diversity in field edges, for all bee guilds, while at 50-100 m radii, only aboveground nesters were positively affected. In sum, we found that crop and non-crop pollinators are distinguished by behavioral and morphological traits. Hence, analysis of life-history

  1. TIMI Risk Score accurately predicts risk of death in 30-day and one-year follow-up in STEMI patients treated with primary percutaneous coronary interventions.

    Science.gov (United States)

    Kozieradzka, Anna; Kamiński, Karol; Dobrzycki, Sławomir; Nowak, Konrad; Musiał, Włodzimierz

    2007-07-01

    TIMI Risk Score for ST-elevation myocardial infarction (STEMI) was developed in a cohort of patients treated with fibrinolysis. It was though to predict in-hospital and short-term prognosis. Later studies validated this approach in large cohorts of patients, regardless of the applied treatment and presented its good power to predict 30-day mortality. We applied the TIMI Risk Score to our registry of STEMI patients treated with primary percutaneous intervention (pPCI) to validate the possibility to predict one-year survival. Our registry comprised 494 consecutive patients (mean age 58.5+/-11.3 years) with STEMI treated with pPCI who were followed for approximately one year. STEMI was diagnosed based on typical criteria: chest pain, ECG changes and rise in myocardial necrosis markers. In all patients TIMI Risk Score for STEMI was calculated and they were divided into three groups: low risk (0-5 points), medium risk (6-7) and high risk (>7 points). Multivariate logistic regression analysis, Kaplan-Meier survival analysis with Cox and log-rank tests as well as c statistics from receiver-operator curves (ROC) were used for statistical analysis. TIMI 3 flow was obtained in 95.5% of patients. Median TIMI risk score was 4 (ranging from 0 to 10). During follow-up there were 47 deaths (9.5%). There was a statistically significant difference in survival between all risk groups both in 30-day and one-year follow-up (p TIMI Risk Score had good power to predict 30-day (c statistic 0.834, 95% CI 0.757-0.91, p TIMI Risk score maintained its very good prognostic value. All analysed risk groups significantly differed between each other with respect to mortality (p TIMI Risk Score was one of the independent risk factors of death during one-year follow-up (OR 1.59, p TIMI Risk Score accurately defines the population of STEMI patients who are at high risk of death not only during the first 30 days, but also during a long-term follow-up. This simple score should be included in the

  2. bSiteFinder, an improved protein-binding sites prediction server based on structural alignment: more accurate and less time-consuming.

    Science.gov (United States)

    Gao, Jun; Zhang, Qingchen; Liu, Min; Zhu, Lixin; Wu, Dingfeng; Cao, Zhiwei; Zhu, Ruixin

    2016-01-01

    Protein-binding sites prediction lays a foundation for functional annotation of protein and structure-based drug design. As the number of available protein structures increases, structural alignment based algorithm becomes the dominant approach for protein-binding sites prediction. However, the present algorithms underutilize the ever increasing numbers of three-dimensional protein-ligand complex structures (bound protein), and it could be improved on the process of alignment, selection of templates and clustering of template. Herein, we built so far the largest database of bound templates with stringent quality control. And on this basis, bSiteFinder as a protein-binding sites prediction server was developed. By introducing Homology Indexing, Chain Length Indexing, Stability of Complex and Optimized Multiple-Templates Clustering into our algorithm, the efficiency of our server has been significantly improved. Further, the accuracy was approximately 2-10 % higher than that of other algorithms for the test with either bound dataset or unbound dataset. For 210 bound dataset, bSiteFinder achieved high accuracies up to 94.8 % (MCC 0.95). For another 48 bound/unbound dataset, bSiteFinder achieved high accuracies up to 93.8 % for bound proteins (MCC 0.95) and 85.4 % for unbound proteins (MCC 0.72). Our bSiteFinder server is freely available at http://binfo.shmtu.edu.cn/bsitefinder/, and the source code is provided at the methods page. An online bSiteFinder server is freely available at http://binfo.shmtu.edu.cn/bsitefinder/. Our work lays a foundation for functional annotation of protein and structure-based drug design. With ever increasing numbers of three-dimensional protein-ligand complex structures, our server should be more accurate and less time-consuming.Graphical Abstract bSiteFinder (http://binfo.shmtu.edu.cn/bsitefinder/) as a protein-binding sites prediction server was developed based on the largest database of bound templates so far with stringent quality

  3. Leaf and life history traits predict plant growth in a green roof ecosystem.

    Directory of Open Access Journals (Sweden)

    Jeremy Lundholm

    Full Text Available Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that

  4. IMPre: an accurate and efficient software for prediction of T- and B-cell receptor germline genes and alleles from rearranged repertoire data

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2016-11-01

    Full Text Available Large-scale study of the properties of T-cell receptor (TCR and B-cell receptor (BCR repertoires through next-generation sequencing is providing excellent insights into the understanding of adaptive immune responses. Variable(DiversityJoining V(DJ germline genes and alleles must be characterized in detail to facilitate repertoire analyses. However, most species do not have well-characterized TCR/BCR germline genes because of their high homology. Also, more germline alleles are required for humans and other species, which limits the capacity for studying immune repertoires. Herein, we developed Immune Germline Prediction (IMPre, a tool for predicting germline V/J genes and alleles using deep-sequencing data derived from TCR/BCR repertoires. We developed a new algorithm, Seed_Clust, for clustering, produced a multiway tree for assembly and optimized the sequence according to the characteristics of rearrangement. We trained IMPre on human samples of T-cell receptor beta (TRB and immunoglobulin heavy chain (IGH, and then tested it on additional human samples. Accuracy of 97.7%, 100%, 92.9% and 100% was obtained for TRBV, TRBJ, IGHV and IGHJ, respectively. Analyses of subsampling performance for these samples showed IMPre to be robust using different data quantities. Subsequently, IMPre was tested on samples from rhesus monkeys and human long sequences: the highly accurate results demonstrated IMPre to be stable with animal and multiple data types. With rapid accumulation of high-throughput sequence data for TCR and BCR repertoires, IMPre can be applied broadly for obtaining novel genes and a large number of novel alleles. IMPre is available at https://github.com/zhangwei2015/IMPre.

  5. Fibrotic focus: An important parameter for accurate prediction of a high level of tumor-associated macrophage infiltration in invasive ductal carcinoma of the breast.

    Science.gov (United States)

    Shimada, Hiroko; Hasebe, Takahiro; Sugiyama, Michiko; Shibasaki, Satomi; Sugitani, Ikuko; Ueda, Shigeto; Gotoh, Yoshiya; Yasuda, Masanori; Arai, Eiichi; Osaki, Akihiko; Saeki, Toshiaki

    2017-07-01

    Our group and others have previously reported that a fibrotic focus is a very useful histological factor for the accurate prediction of the outcome of patients with invasive ductal carcinoma of the breast. We classified 258 cases of invasive ductal carcinoma into those with and those without a fibrotic focus to investigate whether the presence of a fibrotic focus was significantly associated with the degree of tumor-associated macrophage (CD68, CD163 or CD204-positive) infiltration or whether the presence of tumor-associated macrophage infiltration heightened the malignant potential of invasive ductal carcinoma with a fibrotic focus. Multiple regression analyses demonstrated that a fibrotic focus was the only factor that was significantly associated with a high level of CD68-, CD163- or CD204-positive tumor-associated macrophage infiltration. The combined assessment of the presence or absence of a fibrotic focus and a high or a low level of CD204-positive tumor-associated macrophage infiltration clearly demonstrated that CD204-positive tumor-associated macrophage infiltration had a significant prognostic power only for patients with invasive ductal carcinoma with a fibrotic focus in multivariate analyses; CD204-positive tumor-associated macrophages might only exert a significant effect on tumor progression when a fibrotic focus is present within the invasive ductal carcinoma of the breast. © 2017 Japanese Society of Pathology and John Wiley & Sons Australia, Ltd.

  6. Integrating trans-abdominal ultrasonography with fecal steroid metabolite monitoring to accurately diagnose pregnancy and predict the timing of parturition in the red panda (Ailurus fulgens styani).

    Science.gov (United States)

    Curry, Erin; Browning, Lissa J; Reinhart, Paul; Roth, Terri L

    2017-05-01

    Red pandas (Ailurus fulgens styani) exhibit a variable gestation length and may experience a pseudopregnancy indistinguishable from true pregnancy; therefore, it is not possible to deduce an individual's true pregnancy status and parturition date based on breeding dates or fecal progesterone excretion patterns alone. The goal of this study was to evaluate the use of transabdominal ultrasonography for pregnancy diagnosis in red pandas. Two to three females were monitored over 4 consecutive years, generating a total of seven profiles (four pregnancies, two pseudopregnancies, and one lost pregnancy). Fecal samples were collected and assayed for progesterone (P4) and estrogen conjugate (EC) to characterize patterns associated with breeding activity and parturition events. Animals were trained for voluntary transabdominal ultrasound and examinations were performed weekly. Breeding behaviors and fecal EC data suggest that the estrus cycle of this species is 11-12 days in length. Fecal steroid metabolite analyses also revealed that neither P4 nor EC concentrations were suitable indicators of pregnancy in this species; however, a secondary increase in P4 occurred 69-71 days prior to parturition in all pregnant females, presumably coinciding with embryo implantation. Using ultrasonography, embryos were detected as early as 62 days post-breeding/50 days pre-partum and serial measurements of uterine lumen diameter were documented throughout four pregnancies. Advances in reproductive diagnostics, such as the implementation of ultrasonography, may facilitate improved husbandry of pregnant females and allow for the accurate prediction of parturition. © 2017 Wiley Periodicals, Inc.

  7. Family history of premature coronary heart disease and risk prediction in the EPIC-Norfolk prospective population study

    NARCIS (Netherlands)

    Sivapalaratnam, Suthesh; Boekholdt, S. Matthijs; Trip, Mieke D.; Sandhu, Manjinder S.; Luben, Robert; Kastelein, John J. P.; Wareham, Nicholas J.; Khaw, Kay-Tee

    2010-01-01

    Objective The value of a family history for coronary heart disease (CHD) in addition to established cardiovascular risk factors in predicting an individual's risk of CHD is unclear. In the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort, the authors tested whether adding family

  8. Preschool Speech Error Patterns Predict Articulation and Phonological Awareness Outcomes in Children with Histories of Speech Sound Disorders

    Science.gov (United States)

    Preston, Jonathan L.; Hull, Margaret; Edwards, Mary Louise

    2013-01-01

    Purpose: To determine if speech error patterns in preschoolers with speech sound disorders (SSDs) predict articulation and phonological awareness (PA) outcomes almost 4 years later. Method: Twenty-five children with histories of preschool SSDs (and normal receptive language) were tested at an average age of 4;6 (years;months) and were followed up…

  9. Testing life history predictions in a long-lived seabird: A population matrix approach with improved parameter estimation

    Science.gov (United States)

    Doherty, P.F.; Schreiber, E.A.; Nichols, J.D.; Hines, J.E.; Link, W.A.; Schenk, G.A.; Schreiber, R.W.

    2004-01-01

    Life history theory and associated empirical generalizations predict that population growth rate (λ) in long-lived animals should be most sensitive to adult survival; the rates to which λ is most sensitive should be those with the smallest temporal variances; and stochastic environmental events should most affect the rates to which λ is least sensitive. To date, most analyses attempting to examine these predictions have been inadequate, their validity being called into question by problems in estimating parameters, problems in estimating the variability of parameters, and problems in measuring population sensitivities to parameters. We use improved methodologies in these three areas and test these life-history predictions in a population of red-tailed tropicbirds (Phaethon rubricauda). We support our first prediction that λ is most sensitive to survival rates. However the support for the second prediction that these rates have the smallest temporal variance was equivocal. Previous support for the second prediction may be an artifact of a high survival estimate near the upper boundary of 1 and not a result of natural selection canalizing variances alone. We did not support our third prediction that effects of environmental stochasticity (El Niño) would most likely be detected in vital rates to which λ was least sensitive and which are thought to have high temporal variances. Comparative data-sets on other seabirds, within and among orders, and in other locations, are needed to understand these environmental effects.

  10. History of Major Depressive Disorder Prospectively Predicts Worse Quality of Life in Women with Breast Cancer

    Science.gov (United States)

    Small, Brent J.; Minton, Susan; Andrykowski, Michael; Jacobsen, Paul B.

    2012-01-01

    Background Data are scarce about whether past history of major depressive disorder in the absence of current depression places breast cancer patients at risk for worse quality of life. Purpose The current study prospectively examined quality of life during chemotherapy in breast cancer patients with a history of resolved major depressive disorder (n=29) and no history of depression (n=144). Methods Women with Stages 0–II breast cancer were assessed prior to and at the completion of chemotherapy. Major depressive disorder was assessed via structured interview and quality of life with the SF-36. Results Patients with past major depressive disorder displayed greater declines in physical functioning relative to patients with no history of depression (p≤0.01). Conclusions Findings suggest that breast cancer patients with a history of resolved major depressive disorder are at increased risk for declines in physical functioning during chemotherapy relative to patients with no history of depression. PMID:22167580

  11. Cosmological constraints from the CFHTLenS shear measurements using a new, accurate, and flexible way of predicting non-linear mass clustering

    Science.gov (United States)

    Angulo, Raul E.; Hilbert, Stefan

    2015-03-01

    We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.

  12. Albumin-Bilirubin and Platelet-Albumin-Bilirubin Grades Accurately Predict Overall Survival in High-Risk Patients Undergoing Conventional Transarterial Chemoembolization for Hepatocellular Carcinoma.

    Science.gov (United States)

    Hansmann, Jan; Evers, Maximilian J; Bui, James T; Lokken, R Peter; Lipnik, Andrew J; Gaba, Ron C; Ray, Charles E

    2017-09-01

    To evaluate albumin-bilirubin (ALBI) and platelet-albumin-bilirubin (PALBI) grades in predicting overall survival in high-risk patients undergoing conventional transarterial chemoembolization for hepatocellular carcinoma (HCC). This single-center retrospective study included 180 high-risk patients (142 men, 59 y ± 9) between April 2007 and January 2015. Patients were considered high-risk based on laboratory abnormalities before the procedure (bilirubin > 2.0 mg/dL, albumin 1.2 mg/dL); presence of ascites, encephalopathy, portal vein thrombus, or transjugular intrahepatic portosystemic shunt; or Model for End-Stage Liver Disease score > 15. Serum albumin, bilirubin, and platelet values were used to determine ALBI and PALBI grades. Overall survival was stratified by ALBI and PALBI grades with substratification by Child-Pugh class (CPC) and Barcelona Liver Clinic Cancer (BCLC) stage using Kaplan-Meier analysis. C-index was used to determine discriminatory ability and survival prediction accuracy. Median survival for 79 ALBI grade 2 patients and 101 ALBI grade 3 patients was 20.3 and 10.7 months, respectively (P grade 2 and 144 PALBI grade 3 patients was 20.3 and 12.9 months, respectively (P = .0667). Substratification yielded distinct ALBI grade survival curves for CPC B (P = .0022, C-index 0.892), BCLC A (P = .0308, C-index 0.887), and BCLC C (P = .0287, C-index 0.839). PALBI grade demonstrated distinct survival curves for BCLC A (P = 0.0229, C-index 0.869). CPC yielded distinct survival curves for the entire cohort (P = .0019) but not when substratified by BCLC stage (all P > .05). ALBI and PALBI grades are accurate survival metrics in high-risk patients undergoing conventional transarterial chemoembolization for HCC. Use of these scores allows for more refined survival stratification within CPC and BCLC stage. Copyright © 2017 SIR. Published by Elsevier Inc. All rights reserved.

  13. Sister's fracture history may be associated with perimenopausal bone fragility and modifies the predictability of fracture risk.

    Science.gov (United States)

    Sirola, J; Salovaara, K; Tuppurainen, M; Jurvelin, J S; Alhava, E; Kröger, H

    2009-04-01

    The present study investigated the effects of first degree relatives' fractures on fracture incidence after the menopause. Sister's, but not other relatives', wrist or hip fracture history was associated with increased risk of fragility fractures after the menopause. This suggests genetic predisposition to bone fragility among postmenopausal women. The aim of the present study was to investigate the association between first degree relatives' fractures and perimenopausal bone fragility. The study sample of 971 perimenopausal women was extracted from randomly selected Kuopio Osteoporosis Risk Factor and Prevention cohort and measured with dual X-ray absorptiometry in femoral neck (FN) in baseline (1989-1991), in 5 years (1994-97), and in 10 years (1999-2001). All low-trauma energy fractures during the 10-year follow-up were recorded based on self-reports and validated from medical records. First degree relatives' history of life-time hip and wrist fractures (exact classification or trauma energy not specified) was questioned by postal inquiries. There was a significant correlation between fathers' vs. brothers' and mothers' vs. sisters' fractures (p fractures were associated with significantly lowered 10-year fragility fracture-free survival rate (HR = 0.56, p = 0.006). Sisters' or other relatives' fractures were not associated with FN bone loss rate or bone mineral density (BMD) in the follow-up measurements (p = NS in ANCOVA). The predictive power of BMD for fragility fractures differed according to sisters' fracture history: Baseline FN T score predicted fracture-free survival only among women without sisters' fracture history (HR 0.62, p fracture in Cox regression). In conclusion, sisters' fracture history is associated with 10-year fracture-free survival in perimenopausal women but not with BMD or its changes. Predictability of fragility fracture risk with BMD may depend on sister's fracture history. This may indirectly suggest genetic predisposition to bone

  14. Stress sensitivity interacts with depression history to predict depressive symptoms among youth: Prospective changes following first depression onset

    Science.gov (United States)

    Technow, Jessica R.; Hazel, Nicholas A.; Abela, John R. Z.; Hankin, Benjamin L.

    2015-01-01

    Predictors of depressive symptoms may differ before and after the first onset of major depression due to stress sensitization. Dependent stressors, or those to which characteristics of individuals contribute, have been shown to predict depressive symptoms in youth. The current study sought to clarify how stressors’ roles may differ before and after the first depressive episode. Adolescents (N = 382, aged 11 to 15 at baseline) were assessed at baseline and every three months over the course of two years with measures of stressors and depressive symptoms. Semi-structured interviews were conducted every 6 months to assess for clinically significant depressive episodes. Hierarchical linear modeling showed a significant interaction between history of depression and idiographic fluctuations in dependent stressors to predict prospective elevations of symptoms, such that dependent stressors were more predictive of depressive symptoms after onset of disorder. Independent stressors predicted symptoms, but the strength of the association did not vary by depression history. These results suggest a synthesis of stress sensitization and generation processes that might maintain inter-episode depressive symptoms among youth with a history of clinical depression. PMID:25123081

  15. Can family history and cord blood IgE predict sensitization and allergic diseases up to adulthood?

    DEFF Research Database (Denmark)

    Borrits Pagh Nissen, Susanne; Fomsgaard Kjær, Henrik; Høst, Arne

    2015-01-01

    used. RESULTS: A total of 455 infants were included, 188 with CB-IgE ≥0.5 kU/l and 267 with CB-IgE history and elevated CB-IgE were significantly associated to allergic disease until 26 yr. Concerning any allergic...... with high NPV and specificity, but low PPV and sensitivity. CONCLUSION: Although family history and elevated CB-IgE were significantly associated with primarily atopic disease until 26 yr, none of these were strong predictors for subsequent sensitization and allergic symptoms from childhood until early......BACKGROUND: Long-term studies of the predictive value of family history and cord blood IgE level until adulthood are few, and their conclusions have been contradictory. METHODS: Screening of total IgE in 1617 cord blood samples was performed in a Danish birth cohort. All infants with cord blood Ig...

  16. Fracture predictive ability of physical performance tests and history of falls in elderly women: a 10-year prospective study.

    Science.gov (United States)

    Wihlborg, A; Englund, M; Åkesson, K; Gerdhem, P

    2015-08-01

    In a large cohort of elderly women followed for 10 years, we found that balance, gait speed, and self-reported history of fall independently predicted fracture. These clinical risk factors are easily evaluated and therefore advantageous in a clinical setting. They would improve fracture risk assessment and thereby also fracture prevention. The aim of this study was to identify additional risk factors for osteoporosis-related fracture by investigating the fracture predictive ability of physical performance tests and self-reported history of falls. In the population-based Osteoporosis Prospective Risk Assessment study (OPRA), 1044 women were recruited at the age of 75 and followed for 10 years. At inclusion, knee extension force, standing balance, gait speed, and bone mineral density (BMD) were examined. Falls the year before investigation was assessed by questionnaire. Cox proportional hazards regression analysis was used to determine fracture hazard ratios (HR) with BMD, history of fracture, BMI, smoking habits, bisphosphonate, vitamin D, glucocorticoid, and alcohol use as covariates. Continuous variables were standardized and HR shown for each standard deviation change. Of all women, 427 (41%) sustained at least one fracture during the 10-year follow-up. Failing the balance test had an HR of 1.98 (1.18-3.32) for hip fracture. Each standard deviation decrease in gait speed was associated with an HR of 1.37 (1.14-1.64) for hip fracture. Previous fall had an HR of 1.30 (1.03-1.65) for any fracture; 1.39 (1.08-1.79) for any osteoporosis-related fracture; and 1.60 (1.03-2.48) for distal forearm fracture. Knee extension force did not show fracture predictability. The balance test, gait speed test, and self-reported history of fall all hold independent fracture predictability. Consideration of these clinical risk factors for fracture would improve the fracture risk assessment and subsequently also fracture prevention.

  17. The value of genetic information for diabetes risk prediction - differences according to sex, age, family history and obesity.

    Directory of Open Access Journals (Sweden)

    Kristin Mühlenbruch

    Full Text Available BACKGROUND: Genome-wide association studies have identified numerous single nucleotide polymorphisms associated with type 2 diabetes through the past years. In previous studies, the usefulness of these genetic markers for prediction of diabetes was found to be limited. However, differences may exist between substrata of the population according to the presence of major diabetes risk factors. This study aimed to investigate the added predictive value of genetic information (42 single nucleotide polymorphisms in subgroups of sex, age, family history of diabetes, and obesity. METHODS: A case-cohort study (random subcohort N = 1,968; incident cases: N = 578 within the European Prospective Investigation into Cancer and Nutrition Potsdam study was used. Prediction models without and with genetic information were evaluated in terms of the area under the receiver operating characteristic curve and the integrated discrimination improvement. Stratified analyses included subgroups of sex, age (<50 or ≥50 years, family history (positive if either father or mother or a sibling has/had diabetes, and obesity (BMI< or ≥30 kg/m(2. RESULTS: A genetic risk score did not improve prediction above classic and metabolic markers, but - compared to a non-invasive prediction model - genetic information slightly improved the area under the receiver operating characteristic curve (difference [95%-CI]: 0.007 [0.002-0.011]. Stratified analyses showed stronger improvement in the older age group (0.010 [0.002-0.018], the group with a positive family history (0.012 [0.000-0.023] and among obese participants (0.015 [-0.005-0.034] compared to the younger participants (0.005 [-0.004-0.014], participants with a negative family history (0.003 [-0.001-0.008] and non-obese (0.007 [0.000-0.014], respectively. No difference was found between men and women. CONCLUSION: There was no incremental value of genetic information compared to standard non-invasive and metabolic

  18. Using Landsat-derived disturbance history (1972-2010) to predict current forest structure

    Science.gov (United States)

    Dirk Pflugmacher; Warren B. Cohen; Robert E. Kennedy

    2012-01-01

    Lidar is currently the most accurate method for remote estimation of forest structure, but it has limited spatial and temporal coverage. Conversely, Landsat data are more widely available, but exhibit a weaker relationship with structure under medium to high leaf area conditions. One potentially valuable means of enhancing the relationship between Landsat reflectance...

  19. Does a history of bullying and abuse predict lower urinary tract symptoms, chronic pain, and sexual dysfunction?

    Science.gov (United States)

    Nault, Tori; Gupta, Priyanka; Ehlert, Michael; Dove-Medows, Emily; Seltzer, Marlene; Carrico, Donna J; Gilleran, Jason; Bartley, Jamie; Peters, Kenneth M; Sirls, Larry

    2016-11-01

    To investigate associations of bullying and abuse with pelvic floor symptoms, urogenital pain, and sexual health characteristics of women presenting to a multidisciplinary women's urology center. Retrospective review of a prospective database. Patients completed questions about bullying, abuse, sexual health and validated questionnaires including the Pelvic Floor Dysfunction Inventory (PFDI-20), Overactive Bladder Questionnaire (OAB-q), and visual analog scale (VAS 0-10) for genitourinary pain. Statistical analyses included Chi-squared and t tests, which compared victims of bullying and/or abuse to non-victims. Three hundred and eighty patients were reviewed. Three hundred and thirty-eight had data on bullying and abuse history. Out of 380, 94 (24.7 %) reported that they were victims of bullying. Out of 380, 104 (27.4 %) reported that they were victims of abuse. Women with a history of bullying and abuse had increased overall pain scores compared to those without a history of either. Women with a history of abuse and bullying had increased PFDI-20, POPDI, and UDI-6 scores compared to women who were not bullied or abused. There was no difference in being sexually active or in sexual satisfaction between the groups. Patients with a history of abuse and bullying had the greatest percentage of dyspareunia (p = 0.009). Women with a history of bullying, abuse, or both predict increased pelvic floor distress, urological symptoms, increased urogenital pain, and increased dyspareunia. Clinicians should screen for exposure to bullying or abuse in order to provide comprehensive resources to address these psychosocial issues.

  20. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lamberth, K; Harndahl, M

    2008-01-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding....... The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8......–11 for all 122 alleles. artificial neural network predictions are given as actual IC50 values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has...

  1. History taking and leukocyturia predict the presence of asymptomatic bacteriuria in women with diabetes mellitus

    NARCIS (Netherlands)

    Meiland, R; Geerlings, SE; Stolk, RP; Hoes, AW; Hoepelman, AIM

    2004-01-01

    Objective: To investigate the accuracy of history taking to diagnose asymptomatic bacteriuria (ASB) in diabetic women, and the added value of leukocyturia. Methods: Data were obtained from a multicenter study including 465 women with diabetes. Many patient characteristics were considered as

  2. Parental consanguinity and family history of coronary artery disease strongly predict early stenosis.

    Science.gov (United States)

    Youhanna, Sonia; Platt, Daniel E; Rebeiz, Abdallah; Lauridsen, Michael; Deeb, Mary E; Nasrallah, Antoine; Alam, Samir; Puzantian, Houry; Kabbani, Samer; Ghoul, Melanie; Zreik, Tony G; el Bayeh, Hamid; Abchee, Antoine; Zalloua, Pierre

    2010-10-01

    Coronary artery disease (CAD) is a multifactorial disease with acquired and inherited components. We investigated the roles of family history and consanguinity on CAD risk and age at diagnosis in 4284 patients. The compounded impact of diabetes, hyperlipidemia, hypertension, smoking, and BMI, which are known CAD risk factors, on CAD risk and age at diagnosis was also explored. CAD was determined by cardiac catheterization. Logistic regression and stratification were performed to determine the impact of family history and consanguinity on risk and onset of CAD, controlling for diabetes, hyperlipidemia, hypertension, smoking, and BMI. Family history of CAD and gender significantly increased the risk for young age at diagnosis of CAD (pConsanguinity did not promote risk of CAD (p=0.38), but did affect age of disease diagnosis (pconsanguinity were considered as unique risk factors for CAD, compared to 62.8 years for the no-risk-factor patient category (pconsanguinity in the presence of family history lowers the age of disease diagnosis significantly for CAD, emphasizing the role of strong genetic and cultural CAD modifiers. These findings highlight the increased role of genetic determinants of CAD in some population subgroups, and suggest that populations and family structure influence genetic heterogeneity between patients with CAD. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  3. History of syncope predicts loss of consciousness after head trauma: Retrospective study.

    Science.gov (United States)

    Zyśko, Dorota; Sutton, Richard; Timler, Dariusz; Furtan, Stanisław; Melander, Olle; Fedorowski, Artur

    2014-01-01

    Head trauma may present as transient loss of consciousness (TLOC) currently classified as traumatic in origin, in contrast to non-traumatic forms, such as syncope. Whether past history of syncope predisposes to loss of consciousness after head injury has been poorly studied. A retrospective analysis of data obtained from 818 consecutive patients admitted to Emergency Departments was conducted. Face-to-face semi-structured interviews were performed, where patients' past history of syncope and head injury were explored. Head injury events were stratified as high- or low-energy trauma. Data regarding past syncopal events were explored in regard to number, age at the first occurrence, and syncope circumstances. Multivariate logistic regression model was applied to assess the relationship between loss of consciousness during head injury and past history of syncope. Both past history of non-traumatic TLOC (odds ratio [OR] 3.78; 95% confidence interval [CI] 2.13-6.68, p consciousness after head injury. The clinical importance of this finding merits further investigation.

  4. Interrelationship between family history of alcoholism and generational status in the prediction of alcohol dependence in US Hispanics.

    Science.gov (United States)

    Chartier, K G; Thomas, N S; Kendler, K S

    2017-01-01

    Both a family history of alcoholism and migration-related factors like US v. foreign nativity increase the risk for developing alcohol use disorders in Hispanic Americans. For this study, we integrated these two lines of research to test whether the relationship between familial alcoholism and alcohol dependence changes with successive generations in the United States. Data were from the waves 1 and 2 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Subjects self-identified Hispanic ethnicity (N = 4122; n = 1784 first, n = 1169 second, and n = 1169 third or later generation) and reported ever consuming ⩾12 drinks in a 1-year period. A family history of alcoholism was assessed in first- and second-degree relatives. Analyses predicting the number of alcohol dependence symptoms were path models. Alcohol dependence symptoms were associated with a stronger family history of alcoholism and later generational status. There was a significant interaction effect between familial alcoholism and generational status; the relationship of familial alcoholism with alcohol dependence symptoms increased significantly with successive generations in the United States, more strongly in women than men. Acculturation partially mediated the interaction effect between familial alcoholism and generational status on alcohol dependence, although not in the expected direction. Familial alcoholism interacted with generational status in predicting alcohol dependence symptoms in US Hispanic drinkers. This relationship suggests that heritability for alcoholism is influenced by a higher-order environmental factor, likely characterized by a relaxing of social restrictions on drinking.

  5. History of suffocation, state-trait anxiety, and anxiety sensitivity in predicting 35% carbon dioxide-induced panic.

    Science.gov (United States)

    Monkul, E Serap; Onur, Elif; Tural, Umit; Hatch, John P; Alkın, Tunç; Yücel, Baris; Fidaner, Hüray

    2010-09-30

    The aim of this study was to examine the effects of history of suffocation, state-trait anxiety, and anxiety sensitivity on response to a 35% carbon dioxide (CO₂) challenge in panic disorder patients, their healthy first-degree relatives and healthy comparisons. Thirty-two patients with panic disorder, 32 first-degree relatives, and 34 healthy volunteers underwent the 35% CO₂ challenge. We assessed baseline anxiety with the Anxiety Sensitivity Index (ASI) and State-Trait Anxiety Inventory (STAI1), and panic symptoms with the Panic Symptom List (PSL III-R). A history of suffocation was associated with greater risk of CO₂ reactivity in the combined sample. Patients had more anxiety sensitivity and state and trait anxiety than relatives and healthy comparisons; the difference between relatives and healthy comparisons was not significant. In female patients, trait anxiety predicted CO₂-induced panic. Having a CO₂-sensitive panic disorder patient as a first-degree relative did not predict CO₂-induced panic in a healthy relative. History of suffocation may be an important predictor of CO₂-induced panic. Trait anxiety may have a gender-specific relation to CO₂ reactivity. Copyright © 2009 Elsevier Ltd. All rights reserved.

  6. Family history of cancer predicts endometrial cancer risk independently of Lynch Syndrome: Implications for genetic counselling.

    Science.gov (United States)

    Johnatty, Sharon E; Tan, Yen Y; Buchanan, Daniel D; Bowman, Michael; Walters, Rhiannon J; Obermair, Andreas; Quinn, Michael A; Blomfield, Penelope B; Brand, Alison; Leung, Yee; Oehler, Martin K; Kirk, Judy A; O'Mara, Tracy A; Webb, Penelope M; Spurdle, Amanda B

    2017-11-01

    To determine endometrial cancer (EC) risk according to family cancer history, including assessment by degree of relatedness, type of and age at cancer diagnosis of relatives. Self-reported family cancer history was available for 1353 EC patients and 628 controls. Logistic regression was used to quantify the association between EC and cancer diagnosis in ≥1 first or second degree relative, and to assess whether level of risk differed by degree of relationship and/or relative's age at diagnosis. Risk was also evaluated for family history of up to three cancers from known familial syndromes (Lynch, Cowden, hereditary breast and ovarian cancer) overall, by histological subtype and, for a subset of 678 patients, by EC tumor mismatch repair (MMR) gene expression. Report of EC in ≥1 first- or second-degree relative was associated with significantly increased risk of EC (P=3.8×10-7), independent of lifestyle risk factors. There was a trend in increasing EC risk with closer relatedness and younger age at EC diagnosis in relatives (PTrend=4.43×10-6), and with increasing numbers of Lynch cancers in relatives (PTrend≤0.0001). EC risk associated with family history did not differ by proband tumor MMR status, or histological subtype. Reported EC in first- or second-degree relatives remained associated with EC risk after conservative correction for potential misreported family history (OR 2.0; 95% CI, 1.24-3.37, P=0.004). The strongest predictor of EC risk was closer relatedness and younger EC diagnosis age in ≥1 relative. Associations remained significant irrespective of proband MMR status, and after excluding MMR pathogenic variant carriers, indicating that Lynch syndrome genes do not fully explain familial EC risk. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Prediction of Happy-Sad mood from daily behaviors and previous sleep history

    OpenAIRE

    Sano, Akane; Yu, Amy; McHill, Andrew W.; Phillips, Andrew J. K.; Taylor, Sara; Jaques, Natasha; Klerman, Elizabeth B.; Picard, Rosalind W.

    2015-01-01

    We collected and analyzed subjective and objective data using surveys and wearable sensors worn day and night from 68 participants, for 30 days each, to address questions related to the relationships among sleep duration, sleep irregularity, self-reported Happy-Sad mood and other factors in college students. We analyzed daily and monthly behavior and physiology and identified factors that affect mood, including how accurately sleep duration and sleep regularity for the past 1-5 days classifie...

  8. Accurate prediction of explicit solvent atom distribution in HIV-1 protease and F-ATP synthase by statistical theory of liquids

    Science.gov (United States)

    Sindhikara, Daniel; Yoshida, Norio; Hirata, Fumio

    2012-02-01

    We have created a simple algorithm for automatically predicting the explicit solvent atom distribution of biomolecules. The explicit distribution is coerced from the 3D continuous distribution resulting from a 3D-RISM calculation. This procedure predicts optimal location of solvent molecules and ions given a rigid biomolecular structure. We show examples of predicting water molecules near KNI-275 bound form of HIV-1 protease and predicting both sodium ions and water molecules near the rotor ring of F-ATP synthase. Our results give excellent agreement with experimental structure with an average prediction error of 0.45-0.65 angstroms. Further, unlike experimental methods, this method does not suffer from the partial occupancy limit. Our method can be performed directly on 3D-RISM output within minutes. It is useful not only as a location predictor but also as a convenient method for generating initial structures for MD calculations.

  9. Predicting the natural mortality of marine fish from life history characteristics

    DEFF Research Database (Denmark)

    Gislason, Henrik

    For fish much of the life history is determined by body size. Body size and asymptotic size significantly influences important life history processes such as growth, maturity, egg production, and natural mortality. Futhermore, for a population to persist, offspring must be able to replace...... their parents on a one-for-one basis in the long run. Otherwise the population would either increase exponentially or become extinct. Combining data on growth and specific fecundity in a size-based fish community model of the North Sea and using the requirement of a one-for-one replacement provides...... the information necessary to estimate the scaling of natural mortality with size and asymptotic size. The estimated scaling is compared with output from multispecies fish stock models, with the empirical scaling of the maximum number of recruits per unit of spawning stock biomass with body size...

  10. Family history density predicts long term substance use outcomes in an adolescent treatment sample

    OpenAIRE

    Khoddam, R; Worley, M; Browne, KC; Doran, N; Brown, SA

    2015-01-01

    © 2014 Elsevier Ireland Ltd. Aims: This study explored whether the density of family history (FH) of substance use disorders relates to post-treatment substance use outcomes in adolescents, with the primary aim of determining whether FH exerts a relatively stronger influence on longer-term outcomes. Method: The present investigation examined adolescents (ages 12-18, n= 366) from two independent samples who were treated for alcohol/substance use disorder (ASUD) and re-assessed during the eight...

  11. Metabolic syndrome independently predicts future diabetes in women with a history of gestational diabetes mellitus.

    Science.gov (United States)

    Cho, Nam H; Ahn, Chang Ho; Moon, Joon Ho; Kwak, Soo Heon; Choi, Sung Hee; Lim, Soo; Park, Kyong Soo; Metzger, Boyd E; Jang, Hak C

    2016-08-01

    Metabolic syndrome (MetS) is an established predisposing condition for type 2 diabetes mellitus (T2DM). However, it is not thoroughly evaluated whether MetS increases the risk of T2DM in women with a previous history of gestational diabetes mellitus (GDM) who already at high risk of T2DM compared with the general population. We investigated the impact of MetS on the development of postpartum diabetes in women with a history of GDM.This was a multicenter, prospective cohort study of women diagnosed with GDM. The follow-up evaluations, including the oral glucose tolerance test, were completed at 6 weeks postpartum and annually thereafter. MetS was diagnosed at the initial postpartum evaluation according to the revised criteria of the National Cholesterol Education Program-Adult Treatment Panel III. The risk of developing type 2 diabetes (T2DM) in the follow-up period was analyzed based on the presence of MetS, and the adjusted risk was calculated using a Cox proportional hazards model.A total of 412 women without diabetes at the initial postpartum evaluation participated in the annual follow-up for median 3.8 years. MetS was prevalent in 66 (19.2%) women at the initial postpartum evaluation. The incidences of diabetes in women with and without MetS were 825 and 227 per 10,000 person-years, respectively (P history of GDM.

  12. History of High Motion Sickness Susceptibility Predicts Vestibular Dysfunction Following Sport/Recreation-Related Concussion.

    Science.gov (United States)

    Sufrinko, Alicia M; Kegel, Nathan E; Mucha, Anne; Collins, Michael W; Kontos, Anthony P

    2017-11-20

    To compare vestibular dysfunction at 1 to 10 and 11 to 20 days following sport/recreation-related concussion (SRC) in athletes with and without history of motion sickness susceptibility. Secondary aims of this study were to investigate differences in neurocognitive performance and affective symptoms in these groups. Cross-sectional. Concussion Specialty Clinic. One hundred twenty-four adolescents and adults (82 males, 42 females) aged 14 to 26 (16.36 ± 2.10) years, diagnosed with SRC in the past 10 (4.56 ± 2.54) days; 47 participants composed the sample for quartile analyses. Motion sickness susceptibility questionnaire short form score. Computerized neurocognitive test scores, vestibular/oculomotor screening scores (VOMS), and symptom factor scores from a standardized concussion symptom inventory. There was no association between history of motion sickness susceptibility and VOMS scores (above or below clinical cutoff) at 1 to 10 days after injury, although at 11 to 20 days after injury there was an association between high motion sickness susceptibility and symptoms above clinical cutoff on 5 of the 6 VOMS items (P values 0.01-0.04). The high motion sickness group had more affective symptoms on the symptom inventory than the no motion sickness group (P = 0.002) at 1 to 10 days after injury. Groups did not differ on computerized neurocognitive testing (P = 0.11). Athletes with a preexisting history of motion sensitivity may exhibit more prolonged vestibular dysfunction following SRC, and may experience more affective symptoms early in recovery.

  13. Executive Function Predicts Adaptive Behavior in Children with Histories of Heavy Prenatal Alcohol Exposure and Attention Deficit/Hyperactivity Disorder

    Science.gov (United States)

    Ware, Ashley L.; Crocker, Nicole; O’Brien, Jessica W.; Deweese, Benjamin N.; Roesch, Scott C.; Coles, Claire D.; Kable, Julie A.; May, Philip A.; Kalberg, Wendy O.; Sowell, Elizabeth R.; Jones, Kenneth Lyons; Riley, Edward P.; Mattson, Sarah N.

    2011-01-01

    Purpose of Study Prenatal exposure to alcohol often results in disruption to discrete cognitive and behavioral domains, including executive function (EF) and adaptive functioning. In the current study, the relation between these two domains was examined in children with histories of heavy prenatal alcohol exposure, non-exposed children with a diagnosis of attention-deficit/hyperactivity disorder (ADHD), and typically developing controls. Methods As part of a multisite study, three groups of children (8-18y, M = 12.10) were tested: children with histories of heavy prenatal alcohol exposure (ALC, N=142), non-exposed children with ADHD (ADHD, N=82), and typically developing controls (CON, N=133) who did not have ADHD or a history of prenatal alcohol exposure. Children completed subtests of the Delis-Kaplan Executive Function System (D-KEFS) and their primary caregivers completed the Vineland Adaptive Behavior Scales-II (VABS). Data were analyzed using regression analyses. Results Analyses showed that EF measures were predictive of adaptive abilities and significant interactions between D-KEFS measures and group were present. For the ADHD group, the relation between adaptive abilities and EF was more general, with three of the four EF measures showing a significant relation with adaptive score. In contrast, for the ALC group, this relation was specific to the nonverbal EF measures. In the CON group, performance on EF tasks did not predict adaptive scores over the influence of age. Conclusion These results support prior research in ADHD suggesting that EF deficits are predictive of poorer adaptive behavior and extend this finding to include children with heavy prenatal exposure to alcohol. However, the relation between EF and adaptive ability differed by group, suggesting unique patterns of abilities in these children. These results provide enhanced understanding of adaptive deficits in these populations, as well as demonstrate the ecological validity of laboratory

  14. Executive function predicts adaptive behavior in children with histories of heavy prenatal alcohol exposure and attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Ware, Ashley L; Crocker, Nicole; O'Brien, Jessica W; Deweese, Benjamin N; Roesch, Scott C; Coles, Claire D; Kable, Julie A; May, Philip A; Kalberg, Wendy O; Sowell, Elizabeth R; Jones, Kenneth Lyons; Riley, Edward P; Mattson, Sarah N

    2012-08-01

    Prenatal exposure to alcohol often results in disruption to discrete cognitive and behavioral domains, including executive function (EF) and adaptive functioning. In the current study, the relation between these 2 domains was examined in children with histories of heavy prenatal alcohol exposure, nonexposed children with a diagnosis of attention-deficit/hyperactivity disorder (ADHD), and typically developing controls. As part of a multisite study, 3 groups of children (8 to 18 years, M = 12.10) were tested: children with histories of heavy prenatal alcohol exposure (ALC, n = 142), nonexposed children with ADHD (ADHD, n = 82), and typically developing controls (CON, n = 133) who did not have ADHD or a history of prenatal alcohol exposure. Children completed subtests of the Delis-Kaplan Executive Function System (D-KEFS), and their primary caregivers completed the Vineland Adaptive Behavior Scales-II. Data were analyzed using regression analyses. Analyses showed that EF measures were predictive of adaptive abilities, and significant interactions between D-KEFS measures and group were present. For the ADHD group, the relation between adaptive abilities and EF was more general, with 3 of the 4 EF measures showing a significant relation with adaptive score. In contrast, for the ALC group, this relation was specific to the nonverbal EF measures. In the CON group, performance on EF tasks did not predict adaptive scores over the influence of age. These results support prior research in ADHD, suggesting that EF deficits are predictive of poorer adaptive behavior and extend this finding to include children with heavy prenatal exposure to alcohol. However, the relation between EF and adaptive ability differed by group, suggesting unique patterns of abilities in these children. These results provide enhanced understanding of adaptive deficits in these populations, as well as demonstrate the ecological validity of laboratory measures of EF. Copyright © 2012 by the Research

  15. An index predictive of cognitive outcome in retired professional American Football players with a history of sports concussion.

    Science.gov (United States)

    Wright, Mathew J; Woo, Ellen; Birath, J Brandon; Siders, Craig A; Kelly, Daniel F; Wang, Christina; Swerdloff, Ronald; Romero, Elizabeth; Kernan, Claudia; Cantu, Robert C; Guskiewicz, Kevin

    2016-01-01

    Various concussion characteristics and personal factors are associated with cognitive recovery in athletes. We developed an index based on concussion frequency, severity, and timeframe, as well as cognitive reserve (CR), and we assessed its predictive power regarding cognitive ability in retired professional football players. Data from 40 retired professional American football players were used in the current study. On average, participants had been retired from football for 20 years. Current neuropsychological performances, indicators of CR, concussion history, and play data were used to create an index for predicting cognitive outcome. The sample displayed a range of concussions, concussion severities, seasons played, CR, and cognitive ability. Many of the participants demonstrated cognitive deficits. The index strongly predicted global cognitive ability (R(2) = .31). The index also predicted the number of areas of neuropsychological deficit, which varied as a function of the deficit classification system used (Heaton: R(2) = .15; Wechsler: R(2) = .28). The current study demonstrated that a unique combination of CR, sports concussion, and game-related data can predict cognitive outcomes in participants who had been retired from professional American football for an average of 20 years. Such indices may prove to be useful for clinical decision making and research.

  16. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations

    National Research Council Canada - National Science Library

    Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

    2014-01-01

    .... Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40...

  17. Major depressive disorder in adolescents: family psychiatric history predicts severe behavioral disinhibition.

    Science.gov (United States)

    King, Cheryl A; Knox, Michele S; Henninger, Nathan; Nguyen, Tuan Anh; Ghaziuddin, Neera; Maker, Azmaira; Hanna, Gregory L

    2006-02-01

    Major Depressive Disorder (MDD) becomes increasingly prevalent during adolescence and is associated with substantial psychiatric comorbidity and psychosocial impairment. The marked behavioral heterogeneity evident among adolescents with MDD suggests the possibility of distinct subtypes. This study was designed to determine whether family psychiatric histories differ between groups of MDD adolescents defined by the presence or absence of severe behavioral disinhibition. Adolescents with MDD (n = 71) completed the Buss-Durkee Hostility Inventory--Adapted, Adolescent Aggressive Incidents Interview (AAII), Measure of Aggression, Violence, and Rage in Children, Diagnostic Interview Schedule for Children, Suicidal Ideation Questionnaire-JR., Suicidal Behavior Inventory, and Reynolds Adolescent Depression Scale. Parents completed the Family Informant Schedule and Criteria, Children's Affective Liability Scale, AAII, and a partial DISC. Behavioral disinhibition (BD) measures were used to assign adolescents to MDD+BD (n = 41) and MDD-BD (n = 30) groups. The MDD+BD group had a higher prevalence of drug use disorders in biological fathers than the MDD-BD group. The MDD+BD group also had higher proportions of paternal second degree relatives with alcohol use disorders, drug use disorders, and psychiatric hospitalizations, and a higher proportion of maternal second degree relatives with antisocial personality disorder. Limitations include reliance on single informants for family psychiatric histories and the failure to distinguish between child- and adolescent-onset depression. Family psychiatric histories differentiated MDD adolescents grouped by the presence or absence of behavioral disinhibition, suggesting possible etiologic mechanisms. Further research on subtypes or comorbid presentations may assist in the development of targeted treatment strategies.

  18. Substance Abuse among High-Risk Sexual Offenders: Do Measures of Lifetime History of Substance Abuse Add to the Prediction of Recidivism over Actuarial Risk Assessment Instruments?

    Science.gov (United States)

    Looman, Jan; Abracen, Jeffrey

    2011-01-01

    There has been relatively little research on the degree to which measures of lifetime history of substance abuse add to the prediction of risk based on actuarial measures alone among sexual offenders. This issue is of relevance in that a history of substance abuse is related to relapse to substance using behavior. Furthermore, substance use has…

  19. Do obesity and parental history of myocardial infaction improve cardiovascular risk prediction?

    NARCIS (Netherlands)

    Dis, van I.; Geleijnse, J.M.; Kromhout, D.; Boer, J.M.; Boshuizen, H.C.; Verschuren, W.M.

    2013-01-01

    Background: In clinical practice, individuals at increased risk of cardiovascular diseases (CVD) are identified on the basis of age, sex, smoking, blood pressure, and serum total and high-density lipoprotein cholesterol. We examined whether CVD risk prediction improved when obesity (body mass index

  20. The Predictive Adaptive Response: Modeling the Life-History Evolution of the Butterfly

    NARCIS (Netherlands)

    Heuvel, van den J.; Saastamoinen, M.; Brakefield, P.M.; Kirkwood, T.B.; Zwaan, B.J.; Shanley, D.P.

    2013-01-01

    A predictive adaptive response (PAR) is a type of developmental plasticity where the response to an environmental cue is not immediately advantageous but instead is later in life. The PAR is a way for organisms to maximize fitness in varying environments. Insects living in seasonal environments are

  1. Combined measurement of fetal lung volume and pulmonary artery resistance index is more accurate for prediction of neonatal respiratory distress syndrome in preterm fetuses: a pilot study.

    Science.gov (United States)

    Laban, Mohamed; Mansour, Ghada M; El-Kotb, Ahmed; Hassanin, Alaa; Laban, Zina; Saleh, Abdelrahman

    2017-10-12

    The objective of this study is to estimate optimal cut-off values for mean fetal lung volume (FLV) and pulmonary artery resistance index (PA-RI) as non-invasive measures to predict neonatal respiratory distress syndrome (RDS) in preterm fetuses. A prospective study conducted at Ain Shams University Maternity Hospital, Egypt from May 2015 to July 2017: 80 eligible women diagnosed with preterm labor were recruited at 32-36 weeks' gestation. Before delivery, three-dimensional ultrasound was used to estimate FLV using virtual organ computer-aided analysis (VOCAL), while PA-RI was measured by Doppler ultrasonography. A total of 80 women were examined. Thirty-seven (46%) of the newborns developed neonatal RDS. FLV was significantly lower in neonates who developed RDS (p = .04), whereas PARI was significantly higher in those who did not (p = .02). Cut-off values of FLV ≤27.2 cm3 and PARI ≥0.77 predicted the subsequent development of RDS. Combining both cut-offs generated a more sensitive and specific methodical approach for the prediction of RDS (sensitivity 100%, specificity 88.5%). Measurement of FLV or PA-RI can predict RDS in preterm fetuses. Combined use of both measures bolstered their predictive significance.

  2. Do obesity and parental history of myocardial infarction improve cardiovascular risk prediction?

    Science.gov (United States)

    van Dis, Ineke; Geleijnse, Johanna M; Kromhout, Daan; Boer, Jolanda M A; Boshuizen, Hendriek; Verschuren, W M Monique

    2013-10-01

    In clinical practice, individuals at increased risk of cardiovascular diseases (CVD) are identified on the basis of age, sex, smoking, blood pressure, and serum total and high-density lipoprotein cholesterol. We examined whether CVD risk prediction improved when obesity (body mass index ≥30 kg/m(2)) and premature (risk factor model. Risk factors were measured in 1993-97 in 12,818 participants (53% female) aged 35-65 in the Dutch MORGEN project. Cases of fatal and nonfatal CVD during 10 years of follow up were identified through record linkage. Classical risk factor equations, obtained by Cox proportional hazard analysis, were extended with obesity, paternal MI, and maternal MI. We calculated the net reclassification index (NRI), a measure for correct reclassification of subjects, to check improvement in risk prediction using 5 and 10% increments in absolute CVD risk. A CVD event occurred in 280 men and 140 women. Obesity and maternal MI were positively and significantly related to total CVD after adjustment for classical risk factors (both hazard ratios ∼1.5). Adding obesity and parental MI to CVD risk prediction yielded a significant NRI of 4.5% in men and a non-significant NRI of 2.6% in women when 5% risk categories were used. For 10% categories, the NRIs were slightly larger (5.5% and 3.3%, respectively). The improvements in risk prediction were mainly due to obesity. Modest improvements in CVD risk prediction can be obtained when obesity and, to a lesser extent, parental MI are added to the risk function.

  3. The roles of family history of dyslexia, language, speech production and phonological processing in predicting literacy progress.

    Science.gov (United States)

    Carroll, Julia M; Mundy, Ian R; Cunningham, Anna J

    2014-09-01

    It is well established that speech, language and phonological skills are closely associated with literacy, and that children with a family risk of dyslexia (FRD) tend to show deficits in each of these areas in the preschool years. This paper examines what the relationships are between FRD and these skills, and whether deficits in speech, language and phonological processing fully account for the increased risk of dyslexia in children with FRD. One hundred and fifty-three 4-6-year-old children, 44 of whom had FRD, completed a battery of speech, language, phonology and literacy tasks. Word reading and spelling were retested 6 months later, and text reading accuracy and reading comprehension were tested 3 years later. The children with FRD were at increased risk of developing difficulties in reading accuracy, but not reading comprehension. Four groups were compared: good and poor readers with and without FRD. In most cases good readers outperformed poor readers regardless of family history, but there was an effect of family history on naming and nonword repetition regardless of literacy outcome, suggesting a role for speech production skills as an endophenotype of dyslexia. Phonological processing predicted spelling, while language predicted text reading accuracy and comprehension. FRD was a significant additional predictor of reading and spelling after controlling for speech production, language and phonological processing, suggesting that children with FRD show additional difficulties in literacy that cannot be fully explained in terms of their language and phonological skills. © 2014 John Wiley & Sons Ltd.

  4. Space Shuttle Launch Probability Analysis: Understanding History so We Can Predict the Future

    Science.gov (United States)

    Cates, Grant R.

    2014-01-01

    The Space Shuttle was launched 135 times and nearly half of those launches required 2 or more launch attempts. The Space Shuttle launch countdown historical data of 250 launch attempts provides a wealth of data that is important to analyze for strictly historical purposes as well as for use in predicting future launch vehicle launch countdown performance. This paper provides a statistical analysis of all Space Shuttle launch attempts including the empirical probability of launch on any given attempt and the cumulative probability of launch relative to the planned launch date at the start of the initial launch countdown. This information can be used to facilitate launch probability predictions of future launch vehicles such as NASA's Space Shuttle derived SLS. Understanding the cumulative probability of launch is particularly important for missions to Mars since the launch opportunities are relatively short in duration and one must wait for 2 years before a subsequent attempt can begin.

  5. Prediction of Fatigue Life of a Continuous Bridge Girder Based on Vehicle Induced Stress History

    Directory of Open Access Journals (Sweden)

    V.G. Rao

    2003-01-01

    Full Text Available The fatigue damage assessment of bridge components by conducting a full scale fatigue testing is often prohibitive. A need, therefore, exists to estimate the fatigue damage in bridge components by a simulation of bridge-vehicle interaction dynamics due to the action of the actual traffic. In the present paper, a systematic method has been outlined to find the fatigue damage in the continuous bridge girder based on stress range frequency histogram and fatigue strength parameters of the bridge materials. Vehicle induced time history of maximum flexural stresses has been obtained by Monte Carlo simulation process and utilized to develop the stress range frequency histogram taking into consideration of the annual traffic volume. The linear damage accumulation theory is then applied to calculate cumulative damage index and fatigue life of the bridge. Effect of the bridge span, pavement condition, increase of vehicle operating speed, weight and suspension characteristics on fatigue life of the bridge have been examined.

  6. Human glycemic response curves after intake of carbohydrate foods are accurately predicted by combining in vitro gastrointestinal digestion with in silico kinetic modeling

    Directory of Open Access Journals (Sweden)

    Susann Bellmann

    2018-02-01

    Conclusion: Based on the demonstrated accuracy and predictive quality, this in vitro–in silico technology can be used for the testing of food products on their glycemic response under standardized conditions and may stimulate the production of (slow carbs for the prevention of metabolic diseases.

  7. History of preeclampsia is more predictive of cardiometabolic and cardiovascular risk factors than obesity.

    Science.gov (United States)

    Heidema, Wieteke M; Scholten, Ralph R; Lotgering, Fred K; Spaanderman, Marc E A

    2015-11-01

    To determine to what extent a history of preeclampsia affects traditional cardiometabolic (insulin resistance and dyslipidemia) and cardiovascular (hypertension and micro-albuminuria) risk factors of the metabolic syndrome irrespective of BMI. In a retrospective case-control study we compared 90 formerly preeclamptic women, divided in 3 BMI-classes (BMI 19.5-24.9, 25.0-29.9, ≥30.0kg/m(2)) to 30 controls, matched for BMI, age and parity. Cardiometabolic and cardiovascular risk factors (WHO-criteria) were tested 6-18 months post partum. Statistical analysis included unpaired t-tests, Mann-Whitney U test, or Chi square test and two-way ANOVA. Constituents of the metabolic syndrome (glucose, insulin, HOMAIR, HDL-cholesterol, triglycerides, blood pressure, micro-albuminuria) were higher in formerly preeclamptic women than in BMI-matched controls. Resultantly, traditional risk factors were more prevalent in formerly preeclamptic women than in controls (insulin resistance 80% vs 30%, dyslipidemia 52% vs 3%, hypertension 24% vs 0%, micro-albuminuria 30% vs 0%). Cardiometabolic risk factors increased with BMI, to the same extent in both groups. Formerly preeclamptic women had metabolic syndrome more often than their BMI-matched controls (38% vs 3%, prisk factors of the metabolic syndrome are more prevalent in formerly preeclamptic women than in BMI-matched controls and increase with BMI to the same extent in both groups. A history of preeclampsia seems to be a stronger indicator of cardiovascular risk than obesity per se. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. The predictive power of family history measures of alcohol and drug problems and internalizing disorders in a college population.

    Science.gov (United States)

    Kendler, Kenneth S; Edwards, Alexis; Myers, John; Cho, Seung Bin; Adkins, Amy; Dick, Danielle

    2015-07-01

    A family history (FH) of psychiatric and substance use problems is a potent risk factor for common internalizing and externalizing disorders. In a large web-based assessment of mental health in college students, we developed a brief set of screening questions for a FH of alcohol problems (AP), drug problems (DP) and depression-anxiety in four classes of relatives (father, mother, aunts/uncles/grandparents, and siblings) as reported by the student. Positive reports of a history of AP, DP, and depression-anxiety were substantially correlated within relatives. These FH measures predicted in the student, in an expected pattern, dimensions of personality and impulsivity, alcohol consumption and problems, smoking and nicotine dependence, use of illicit drugs, and symptoms of depression and anxiety. Using the mean score from the four classes of relatives was more predictive than using a familial/sporadic dichotomy. Interactions were seen between the FH of AP, DP, and depression-anxiety and peer deviance in predicting symptoms of alcohol and tobacco dependence. As the students aged, the FH of AP became a stronger predictor of alcohol problems. While we cannot directly assess the validity of these FH reports, the pattern of findings suggest that our brief screening items were able to assess, with some accuracy, the FH of substance misuse and internalizing psychiatric disorders in relatives. If correct, these measures can play an important role in the creation of developmental etiologic models for substance and internalizing psychiatric disorders which constitute one of the central goals of the overall project. © 2015 Wiley Periodicals, Inc.

  9. Impossible Predictions of the Unprecedented: Analogy, History, and the Work of Prognostication

    Science.gov (United States)

    Denning, Kathryn

    At the beginning of exobiology and SETI as research programs circa 1960, it was reasonable and responsible for scientists and others to consider the potential effects of a detection of other life, or contact with it, upon humanity. It is no coincidence that this was a time of reckoning with the power of science and technology. The Cold War was settling in, space programs were beginning, and the technologies of war and those of discovery were then, as now, intertwined, in a way that made Carl Sagan, Philip Morrison, Joshua Lederberg, and others, concerned for humanity's future, and the future of life. Those concerns are as well-founded as ever. However, 50 years on, after half a century of predictions and untested hypotheses, we still only know that a detection of extraterrestrial life could come tomorrow, in the next century, or never. Many potential scenarios have been identified and explored, planetary protection protocols have been implemented for astrobiology, policy concerning SETI detections has been created and debated, and some valuable empirical work has been done concerning potential cultural reactions. We might now reasonably ask: what are our real goals here? And do they match what we are actually accomplishing? Are these exercises still beneficial, or are they reaching the point of diminishing returns? Might there be undesirable effects of prognostications about detection and contact? Elsewhere, I have discussed at some length what I think can sensibly be done to prepare for a detection. This leaves me with a further argument to make here: first, that the use of historical analogies of intercultural contact on Earth to predict or explore the potential consequences of contact with ETI may now be essentially useless or perhaps worse than useless; second, that the longstanding practice of prediction about contact now also invites scrutiny in terms of its utility; and third, that turning our attention to pressing topics at the intersection of astrobiology

  10. Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, H.

    1996-12-01

    This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or {open_quotes}synergy{close_quotes} between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The {open_quotes}Vibration{close_quotes} view of the combined program is then presented.

  11. A numerical/empirical technique for history matching and predicting cyclic steam performance in Canadian oil sands reservoirs

    Science.gov (United States)

    Leshchyshyn, Theodore Henry

    The oil sands of Alberta contain some one trillion barrels of bitumen-in-place, most contained in the McMurray, Wabiskaw, Clearwater, and Grand Rapids formations. Depth of burial is 0--550 m, 10% of which is surface mineable, the rest recoverable by in-situ technology-driven enhanced oil recovery schemes. To date, significant commercial recovery has been attributed to Cyclic Steam Stimulation (CSS) using vertical wellbores. Other techniques, such as Steam Assisted Gravity Drainage (SAGD) are proving superior to other recovery methods for increasing early oil production but at initial higher development and/or operating costs. Successful optimization of bitumen production rates from the entire reservoir is ultimately decided by the operator's understanding of the reservoir in its original state and/or the positive and negative changes which occur in oil sands and heavy oil deposits upon heat stimulation. Reservoir description is the single most important factor in attaining satisfactory history matches and forecasts for optimized production of the commercially-operated processes. Reservoir characterization which lacks understanding can destroy a project. For example, incorrect assumptions in the geological model for the Wolf Lake Project in northeast Alberta resulted in only about one-half of the predicted recovery by the original field process. It will be shown here why the presence of thin calcite streaks within oil sands can determine the success or failure of a commercial cyclic steam project. A vast amount of field data, mostly from the Primrose Heavy Oil Project (PHOP) near Cold Lake, Alberta, enabled the development a simple set of correlation curves for predicting bitumen production using CSS. A previously calibtrated thermal numerical simulation model was used in its simplist form, that is, a single layer, radial grid blocks, "fingering" or " dilation" adjusted permeability curves, and no simulated fracture, to generate the first cycle production

  12. Efficient and accurate two-scale FE-FFT-based prediction of the effective material behavior of elasto-viscoplastic polycrystals

    Science.gov (United States)

    Kochmann, Julian; Wulfinghoff, Stephan; Ehle, Lisa; Mayer, Joachim; Svendsen, Bob; Reese, Stefanie

    2017-09-01

    Recently, two-scale FE-FFT-based methods (e.g., Spahn et al. in Comput Methods Appl Mech Eng 268:871-883, 2014; Kochmann et al. in Comput Methods Appl Mech Eng 305:89-110, 2016) have been proposed to predict the microscopic and overall mechanical behavior of heterogeneous materials. The purpose of this work is the extension to elasto-viscoplastic polycrystals, efficient and robust Fourier solvers and the prediction of micromechanical fields during macroscopic deformation processes. Assuming scale separation, the macroscopic problem is solved using the finite element method. The solution of the microscopic problem, which is embedded as a periodic unit cell (UC) in each macroscopic integration point, is found by employing fast Fourier transforms, fixed-point and Newton-Krylov methods. The overall material behavior is defined by the mean UC response. In order to ensure spatially converged micromechanical fields as well as feasible overall CPU times, an efficient but simple solution strategy for two-scale simulations is proposed. As an example, the constitutive behavior of 42CrMo4 steel is predicted during macroscopic three-point bending tests.

  13. Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

    Energy Technology Data Exchange (ETDEWEB)

    Daly, Megan E.; Luxton, Gary [Department of Radiation Oncology, Stanford University, Stanford, CA (United States); Choi, Clara Y.H. [Department of Neurosurgery, Stanford University, Stanford, CA (United States); Gibbs, Iris C. [Department of Radiation Oncology, Stanford University, Stanford, CA (United States); Chang, Steven D.; Adler, John R. [Department of Neurosurgery, Stanford University, Stanford, CA (United States); Soltys, Scott G., E-mail: sgsoltys@stanford.edu [Department of Radiation Oncology, Stanford University, Stanford, CA (United States)

    2012-04-01

    Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for {alpha}/{beta}, volume parameter n, 50% complication probability dose TD{sub 50}, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of {alpha}/{beta} and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of {alpha}/{beta} and n yielded better predictions (0.7 complications), with n = 0.023 and {alpha}/{beta} = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high {alpha}/{beta} value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models

  14. Oceanography and life history predict contrasting genetic population structure in two Antarctic fish species.

    Science.gov (United States)

    Young, Emma F; Belchier, Mark; Hauser, Lorenz; Horsburgh, Gavin J; Meredith, Michael P; Murphy, Eugene J; Pascoal, Sonia; Rock, Jennifer; Tysklind, Niklas; Carvalho, Gary R

    2015-06-01

    Understanding the key drivers of population connectivity in the marine environment is essential for the effective management of natural resources. Although several different approaches to evaluating connectivity have been used, they are rarely integrated quantitatively. Here, we use a 'seascape genetics' approach, by combining oceanographic modelling and microsatellite analyses, to understand the dominant influences on the population genetic structure of two Antarctic fishes with contrasting life histories, Champsocephalus gunnari and Notothenia rossii. The close accord between the model projections and empirical genetic structure demonstrated that passive dispersal during the planktonic early life stages is the dominant influence on patterns and extent of genetic structuring in both species. The shorter planktonic phase of C. gunnari restricts direct transport of larvae between distant populations, leading to stronger regional differentiation. By contrast, geographic distance did not affect differentiation in N. rossii, whose longer larval period promotes long-distance dispersal. Interannual variability in oceanographic flows strongly influenced the projected genetic structure, suggesting that shifts in circulation patterns due to climate change are likely to impact future genetic connectivity and opportunities for local adaptation, resilience and recovery from perturbations. Further development of realistic climate models is required to fully assess such potential impacts.

  15. The physics of Wall Street a brief history of predicting the unpredictable

    CERN Document Server

    Weatherall, James Owen

    2013-01-01

    After the economic meltdown of 2008, Warren Buffett famously warned, “beware of geeks bearing formulas.” But as James Weatherall demonstrates, not all geeks are created equal. While many of the mathematicians and software engineers on Wall Street failed when their abstractions turned ugly in practice, a special breed of physicists has a much deeper history of revolutionizing finance. Taking us from fin-de-siècle Paris to Rat Pack-era Las Vegas, from wartime government labs to Yippie communes on the Pacific coast, Weatherall shows how physicists successfully brought their science to bear on some of the thorniest problems in economics, from options pricing to bubbles. The crisis was partly a failure of mathematical modeling. But even more, it was a failure of some very sophisticated financial institutions to think like physicists. Models—whether in science or finance—have limitations; they break down under certain conditions. And in 2008, sophisticated models fell into the hands of people who didn’t...

  16. Edaphic history over seedling characters predicts integration and plasticity of integration across geologically variable populations ofArabidopsis thaliana.

    Science.gov (United States)

    Cousins, Elsa A; Murren, Courtney J

    2017-12-01

    Studies on phenotypic plasticity and plasticity of integration have uncovered functionally linked modules of aboveground traits and seedlings of Arabidopsis thaliana , but we lack details about belowground variation in adult plants. Functional modules can be comprised of additional suites of traits that respond to environmental variation. We assessed whether shoot and root responses to nutrient environments in adult A. thaliana were predictable from seedling traits or population-specific geologic soil characteristics at the site of origin. We compared 17 natural accessions from across the native range of A. thaliana using 14-day-old seedlings grown on agar or sand and plants grown to maturity across nutrient treatments in sand. We measured aboveground size, reproduction, timing traits, root length, and root diameter. Edaphic characteristics were obtained from a global-scale dataset and related to field data. We detected significant among-population variation in root traits of seedlings and adults and in plasticity in aboveground and belowground traits of adult plants. Phenotypic integration of roots and shoots varied by population and environment. Relative integration was greater in roots than in shoots, and integration was predicted by edaphic soil history, particularly organic carbon content, whereas seedling traits did not predict later ontogenetic stages. Soil environment of origin has significant effects on phenotypic plasticity in response to nutrients, and on phenotypic integration of root modules and shoot modules. Root traits varied among populations in reproductively mature individuals, indicating potential for adaptive and integrated functional responses of root systems in annuals. © 2017 Botanical Society of America.

  17. Stable, high-order SBP-SAT finite difference operators to enable accurate simulation of compressible turbulent flows on curvilinear grids, with application to predicting turbulent jet noise

    Science.gov (United States)

    Byun, Jaeseung; Bodony, Daniel; Pantano, Carlos

    2014-11-01

    Improved order-of-accuracy discretizations often require careful consideration of their numerical stability. We report on new high-order finite difference schemes using Summation-By-Parts (SBP) operators along with the Simultaneous-Approximation-Terms (SAT) boundary condition treatment for first and second-order spatial derivatives with variable coefficients. In particular, we present a highly accurate operator for SBP-SAT-based approximations of second-order derivatives with variable coefficients for Dirichlet and Neumann boundary conditions. These terms are responsible for approximating the physical dissipation of kinetic and thermal energy in a simulation, and contain grid metrics when the grid is curvilinear. Analysis using the Laplace transform method shows that strong stability is ensured with Dirichlet boundary conditions while weaker stability is obtained for Neumann boundary conditions. Furthermore, the benefits of the scheme is shown in the direct numerical simulation (DNS) of a Mach 1.5 compressible turbulent supersonic jet using curvilinear grids and skew-symmetric discretization. Particularly, we show that the improved methods allow minimization of the numerical filter often employed in these simulations and we discuss the qualities of the simulation.

  18. Sexual anxiety and eroticism predict the development of sexual problems in youth with a history of sexual abuse.

    Science.gov (United States)

    Simon, Valerie A; Feiring, Candice

    2008-05-01

    Youth with confirmed histories of sexual abuse (N = 118) were followed longitudinally to examine associations between their initial sexual reactions to abuse and subsequent sexual functioning. Participants were interviewed at abuse discovery (ages 8 through 15) and again 1 and 6 years later. Eroticism and sexual anxiety emerged as distinct indices of abuse-specific sexual reactions and predicted subsequent sexual functioning. Eroticism was associated with indicators of heightened sexuality, including more sexual risk behavior and views of sexual intimacy focused on partners' needs. Sexual anxiety was associated with indicators of diminished sexuality, including few sexual partners and avoidant views of sexual intimacy. Age at abuse discovery moderated some associations, suggesting that the timing of abuse-specific reactions affects trajectories of sexual development. Findings point to the need for a developmental approach to understanding how abuse-specific sexual reactions disrupt sexual development and the need for early interventions promoting healthy sexual development.

  19. Fukuoka criteria accurately predict risk for adverse outcomes during follow-up of pancreatic cysts presumed to be intraductal papillary mucinous neoplasms.

    Science.gov (United States)

    Mukewar, Saurabh; de Pretis, Nicolo; Aryal-Khanal, Anupama; Ahmed, Nazir; Sah, Raghuwansh; Enders, Felicity; Larson, Joseph J; Levy, Michael J; Takahashi, Naoki; Topazian, Mark; Pearson, Randall; Vege, Santhi S; Chari, Suresh T

    2017-10-01

    Fukuoka consensus guidelines classify pancreatic cystic lesions (PCLs) presumed to be intraductal papillary mucinous neoplasms (IPMNs) into Fukuoka positive (FP) (subgroups of high-risk (HR) and worrisome features (WFs)) and Fukuoka negative (FN) (non-HR feature/WF cysts). We retrospectively estimated 5-year risk of pancreatic cancer (PC) in FN, WF and HR cysts of patients with PCL-IPMN. From Mayo Clinic databases, we randomly selected 2000 patients reported to have a PCL; we excluded inflammatory or suspected non-IPMN cysts and those without imaging follow-up. We re-reviewed cross-sectional imaging and abstracted clinical and follow-up data on PCL-IPMNs. The study contained 802 patients with FN cysts and 358 with FP cysts. Patients with PCL-IPMN had median (IQR) follow-up of 4.2 (1.8-7.1) years. Among FN cysts, 5-year PC risk was low (2-3%) regardless of cyst size (p=0.67). After excluding events in the first 6 months, 5-year PC risk remained low (0-2%) regardless of cyst size (p=0.61). Among FP cysts, HR cysts (n=66) had greater 5-year PC risk than WF cysts (n=292) (49.7% vs 4.1%; p10 mm (79.8% vs 37.3% vs 39.4%, respectively; p=0.01). Fukuoka guidelines accurately stratify PCL-IPMNs for PC risk, with FN cysts having lowest and HR cysts having greatest risk. After 6-month follow-up, WF and FN cysts had a low 5-year PC risk. Surveillance strategies should be tailored appropriately. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  20. Is a positive history of non-anaesthetic drug allergy a predictive factor for positive allergy tests to anaesthetics?

    Science.gov (United States)

    Hagau, Natalia; Gherman-Ionica, Nadia; Hagau, Denisa; Tranca, Sebastian; Sfichi, Manuela; Longrois, Dan

    2012-03-01

    International recommendations stipulate not performing screening skin tests to a drug in the absence of a clinical history consistent with that specific drug allergy. Nevertheless, two publications showed that a positive history of non-anaesthetic drug allergy was the only predictive factor for a positive skin test when screening for allergy to anaesthetic drugs was done. We selected from a surgical population 40 volunteers with a prior history of allergy to non-anaesthetic drugs in order to analyse the prevalence of positive allergy tests to anaesthetics. The selected adult patients were tested for 11 anaesthetic drugs using in vivo tests: skin prick (SPT) and intradermal (IDT) tests and in vitro tests: the basophil activation test (BAT) and detection of drug-specific immunoglobulin E (IgE). The prevalence for the positive SPT and IDT was 1.6% and 5.8% respectively. The result of flow cytometry agreed with the SPT in five out of seven positive SPT (71%). IgEs confirmed two positive SPT with corresponding positive BAT. Ten per cent of the patients had a positive prick test to neuromuscular blocking agents (NMBA). For midazolam none of the SPT was positive, but 11 patients had positive IDT nonconfirmed by BAT. The prevalence of positive in vivo and in vitro allergy tests to NMBAs is higher in our study population. This could be an argument for pre-operative SPT to NMBAs for the surgical population with reported non-anaesthetic drug allergies. A larger prospective study is needed to validate changes in clinical practice. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

  1. How well does family history predict who will get colorectal cancer? Implications for cancer screening and counseling.

    Science.gov (United States)

    Taylor, David P; Stoddard, Gregory J; Burt, Randall W; Williams, Marc S; Mitchell, Joyce A; Haug, Peter J; Cannon-Albright, Lisa A

    2011-05-01

    Using a large, retrospective cohort from the Utah Population Database, we assess how well family history predicts who will acquire colorectal cancer during a 20-year period. Individuals were selected between ages 35 and 80 with no prior record of colorectal cancer diagnosis, as of the year 1985. Numbers of colorectal cancer-affected relatives and diagnosis ages were collected. Familial relative risk and absolute risk estimates were calculated. Colorectal cancer diagnoses in the cohort were counted between years 1986 and 2005. Cox regression and Harrell's C were used to measure the discriminatory power of resulting models. A total of 431,153 individuals were included with 5,334 colorectal cancer diagnoses. Familial relative risk ranged from 0.83 to 12.39 and 20-year absolute risk from 0.002 to 0.21. With familial relative risk as the only predictor, Harrell's C = 0.53 and with age only, Harrell's C = 0.66. Familial relative risk combined with age produced a Harrell's C = 0.67. Family history by itself is not a strong predictor of exactly who will acquire colorectal cancer within 20 years. However, stratification of risk using absolute risk probabilities may be more helpful in focusing screening on individuals who are more likely to develop the disease.

  2. Cortisol in mother's milk across lactation reflects maternal life history and predicts infant temperament.

    Science.gov (United States)

    Hinde, Katie; Skibiel, Amy L; Foster, Alison B; Del Rosso, Laura; Mendoza, Sally P; Capitanio, John P

    2015-01-01

    The maternal environment exerts important influences on offspring mass/growth, metabolism, reproduction, neurobiology, immune function, and behavior among birds, insects, reptiles, fish, and mammals. For mammals, mother's milk is an important physiological pathway for nutrient transfer and glucocorticoid signaling that potentially influences offspring growth and behavioral phenotype. Glucocorticoids in mother's milk have been associated with offspring behavioral phenotype in several mammals, but studies have been handicapped by not simultaneously evaluating milk energy density and yield. This is problematic as milk glucocorticoids and nutrients likely have simultaneous effects on offspring phenotype. We investigated mother's milk and infant temperament and growth in a cohort of rhesus macaque (Macaca mulatta) mother-infant dyads at the California National Primate Research Center (N = 108). Glucocorticoids in mother's milk, independent of available milk energy, predicted a more Nervous, less Confident temperament in both sons and daughters. We additionally found sex differences in the windows of sensitivity and the magnitude of sensitivity to maternal-origin glucocorticoids. Lower parity mothers produced milk with higher cortisol concentrations. Lastly, higher cortisol concentrations in milk were associated with greater infant weight gain across time. Taken together, these results suggest that mothers with fewer somatic resources, even in captivity, may be "programming" through cortisol signaling, behaviorally cautious offspring that prioritize growth. Glucocorticoids ingested through milk may importantly contribute to the assimilation of available milk energy, development of temperament, and orchestrate, in part, the allocation of maternal milk energy between growth and behavioral phenotype.

  3. Mortality Following Congenital Heart Surgery in Adults Can Be Predicted Accurately by Combining Expert-Based and Evidence-Based Pediatric Risk Scores.

    Science.gov (United States)

    Hörer, Jürgen; Kasnar-Samprec, Jelena; Cleuziou, Julie; Strbad, Martina; Wottke, Michael; Kaemmerer, Harald; Schreiber, Christian; Lange, Rüdiger

    2016-07-01

    Currently, there are few specific risk stratification models available to predict mortality following congenital heart surgery in adults. We sought to evaluate whether the predictive power of the common pediatric scores is applicable for adults. In addition, we evaluated a new grown-ups with congenital heart disease (GUCH) score specifically designed for adults undergoing congenital heart surgery. Data of all consecutive patients aged 18 years or more, who underwent surgery for congenital heart disease (CHD) between 2004 and 2013 at our institution, were collected. We evaluated the Aristotle Basic Complexity (ABC), the Aristotle Comprehensive Complexity (ACC), the Risk Adjustment in Congenital Heart Surgery (RACHS-1), and the Society of Thoracic Surgeons (STS)-European Association for Cardiothoracic Surgery (EACTS) scores. The proposed GUCH score consists of the STS-EACTS score, the procedure-dependent and -independent factors of the ACC score, and age. The discriminatory power of the scores was assessed using the area under the receiver-operating characteristics curve (c-index). A total of 830 operations were evaluated. Hospital mortality was 2.9%. C-indexes were 0.67, 0.80, 0.62, 0.78, and 0.84 for the ABC, ACC, RACHS-1, STS-EACTS, and GUCH mortality scores, respectively. The evidence-based EACTS-STS score outperforms the expert-based ABC score. The expert-based ACC score is superior to the evidence-based EACTS-STS score since comorbidities are considered. Our proposed GUCH score outperforms all other scores since it integrates the advantages of the evidence-based EACTS-STS score for procedures and the expert-based ACC score for comorbidities. Evidence-based scores for adults with CHD should include comorbidities and patient ages. © The Author(s) 2016.

  4. Skinfold Prediction Equations Fail to Provide an Accurate Estimate of Body Composition in Elite Rugby Union Athletes of Caucasian and Polynesian Ethnicity.

    Science.gov (United States)

    Zemski, Adam J; Broad, Elizabeth M; Slater, Gary J

    2018-01-01

    Body composition in elite rugby union athletes is routinely assessed using surface anthropometry, which can be utilized to provide estimates of absolute body composition using regression equations. This study aims to assess the ability of available skinfold equations to estimate body composition in elite rugby union athletes who have unique physique traits and divergent ethnicity. The development of sport-specific and ethnicity-sensitive equations was also pursued. Forty-three male international Australian rugby union athletes of Caucasian and Polynesian descent underwent surface anthropometry and dual-energy X-ray absorptiometry (DXA) assessment. Body fat percent (BF%) was estimated using five previously developed equations and compared to DXA measures. Novel sport and ethnicity-sensitive prediction equations were developed using forward selection multiple regression analysis. Existing skinfold equations provided unsatisfactory estimates of BF% in elite rugby union athletes, with all equations demonstrating a 95% prediction interval in excess of 5%. The equations tended to underestimate BF% at low levels of adiposity, whilst overestimating BF% at higher levels of adiposity, regardless of ethnicity. The novel equations created explained a similar amount of variance to those previously developed (Caucasians 75%, Polynesians 90%). The use of skinfold equations, including the created equations, cannot be supported to estimate absolute body composition. Until a population-specific equation is established that can be validated to precisely estimate body composition, it is advocated to use a proven method, such as DXA, when absolute measures of lean and fat mass are desired, and raw anthropometry data routinely to derive an estimate of body composition change.

  5. Anthropometric variables accurately predict dual energy x-ray absorptiometric-derived body composition and can be used to screen for diabetes.

    Directory of Open Access Journals (Sweden)

    Reza Yavari

    Full Text Available The current world-wide epidemic of obesity has stimulated interest in developing simple screening methods to identify individuals with undiagnosed diabetes mellitus type 2 (DM2 or metabolic syndrome (MS. Prior work utilizing body composition obtained by sophisticated technology has shown that the ratio of abdominal fat to total fat is a good predictor for DM2 or MS. The goals of this study were to determine how well simple anthropometric variables predict the fat mass distribution as determined by dual energy x-ray absorptometry (DXA, and whether these are useful to screen for DM2 or MS within a population. To accomplish this, the body composition of 341 females spanning a wide range of body mass indices and with a 23% prevalence of DM2 and MS was determined using DXA. Stepwise linear regression models incorporating age, weight, height, waistline, and hipline predicted DXA body composition (i.e., fat mass, trunk fat, fat free mass, and total mass with good accuracy. Using body composition as independent variables, nominal logistic regression was then performed to estimate the probability of DM2. The results show good discrimination with the receiver operating characteristic (ROC having an area under the curve (AUC of 0.78. The anthropometrically-derived body composition equations derived from the full DXA study group were then applied to a group of 1153 female patients selected from a general endocrinology practice. Similar to the smaller study group, the ROC from logistical regression using body composition had an AUC of 0.81 for the detection of DM2. These results are superior to screening based on questionnaires and compare favorably with published data derived from invasive testing, e.g., hemoglobin A1c. This anthropometric approach offers promise for the development of simple, inexpensive, non-invasive screening to identify individuals with metabolic dysfunction within large populations.

  6. Trauma history and depression predict incomplete adherence to antiretroviral therapies in a low income country.

    Directory of Open Access Journals (Sweden)

    Kathryn Whetten

    Full Text Available As antiretroviral therapy (ART for HIV becomes increasingly available in low and middle income countries (LMICs, understanding reasons for lack of adherence is critical to stemming the tide of infections and improving health. Understanding the effect of psychosocial experiences and mental health symptomatology on ART adherence can help maximize the benefit of expanded ART programs by indicating types of services, which could be offered in combination with HIV care.The Coping with HIV/AIDS in Tanzania (CHAT study is a longitudinal cohort study in the Kilimanjaro Region that included randomly selected HIV-infected (HIV+ participants from two local hospital-based HIV clinics and four free-standing voluntary HIV counselling and testing sites. Baseline data were collected in 2008 and 2009; this paper used data from 36 month follow-up interviews (N = 468. Regression analyses were used to predict factors associated with incomplete self-reported adherence to ART.Incomplete art adherence was significantly more likely to be reported amongst participants who experienced a greater number of childhood traumatic events: sexual abuse prior to puberty and the death in childhood of an immediate family member not from suicide or homicide were significantly more likely in the non-adherent group and other negative childhood events trended toward being more likely. Those with incomplete adherence had higher depressive symptom severity and post-traumatic stress disorder (PTSD. In multivariable analyses, childhood trauma, depression, and financial sacrifice remained associated with incomplete adherence.This is the first study to examine the effect of childhood trauma, depression and PTSD on HIV medication adherence in a low income country facing a significant burden of HIV. Allocating spending on HIV/AIDS toward integrating mental health services with HIV care is essential to the creation of systems that enhance medication adherence and maximize the potential of

  7. Branch Prediction based on Histories of Multi-Branch Execution Patterns for Speculative Execution

    OpenAIRE

    児島,彰; 弘中,哲夫; 高山,毅; 藤野,清次

    1997-01-01

    最近のパイプライン型プロセッサでは、条件分岐でのパイプラインの乱れによる速度低下を抑制するために、分岐予測とそれに使った投機的実行が行われている。ただし、予測失敗時にはペナルティが大きいので、分岐予測の精度向上が望まれる。これまでの分岐予測では、単独の条件分岐に対して過去に分岐したか、どうかの履歴を取り、その情報に基づいて、分岐するかしかないかを予測している。本研究では、さらに分岐予測の精度を高めるため、連続して実行される複数の条件分岐の分岐パターンに対して履歴をとり、この履歴からの分岐予測を従来の手法に組み合わせる方法を提案する。また、この手法による分岐予測の有効性を実際のプログラムを用いて評価する。 / Superscalar processors and superpipeline processors use branch prediction and speculative execution to avoid suffering pipeline bubbles at conditional branches. The costs of recovering pipe...

  8. Trauma history and depression predict incomplete adherence to antiretroviral therapies in a low income country.

    Science.gov (United States)

    Whetten, Kathryn; Shirey, Kristen; Pence, Brian Wells; Yao, Jia; Thielman, Nathan; Whetten, Rachel; Adams, Julie; Agala, Bernard; Ostermann, Jan; O'Donnell, Karen; Hobbie, Amy; Maro, Venance; Itemba, Dafrosa; Reddy, Elizabeth

    2013-01-01

    As antiretroviral therapy (ART) for HIV becomes increasingly available in low and middle income countries (LMICs), understanding reasons for lack of adherence is critical to stemming the tide of infections and improving health. Understanding the effect of psychosocial experiences and mental health symptomatology on ART adherence can help maximize the benefit of expanded ART programs by indicating types of services, which could be offered in combination with HIV care. The Coping with HIV/AIDS in Tanzania (CHAT) study is a longitudinal cohort study in the Kilimanjaro Region that included randomly selected HIV-infected (HIV+) participants from two local hospital-based HIV clinics and four free-standing voluntary HIV counselling and testing sites. Baseline data were collected in 2008 and 2009; this paper used data from 36 month follow-up interviews (N = 468). Regression analyses were used to predict factors associated with incomplete self-reported adherence to ART. Incomplete art adherence was significantly more likely to be reported amongst participants who experienced a greater number of childhood traumatic events: sexual abuse prior to puberty and the death in childhood of an immediate family member not from suicide or homicide were significantly more likely in the non-adherent group and other negative childhood events trended toward being more likely. Those with incomplete adherence had higher depressive symptom severity and post-traumatic stress disorder (PTSD). In multivariable analyses, childhood trauma, depression, and financial sacrifice remained associated with incomplete adherence. This is the first study to examine the effect of childhood trauma, depression and PTSD on HIV medication adherence in a low income country facing a significant burden of HIV. Allocating spending on HIV/AIDS toward integrating mental health services with HIV care is essential to the creation of systems that enhance medication adherence and maximize the potential of expanded

  9. N0/N1, PNL, or LNR? The effect of lymph node number on accurate survival prediction in pancreatic ductal adenocarcinoma.

    Science.gov (United States)

    Valsangkar, Nakul P; Bush, Devon M; Michaelson, James S; Ferrone, Cristina R; Wargo, Jennifer A; Lillemoe, Keith D; Fernández-del Castillo, Carlos; Warshaw, Andrew L; Thayer, Sarah P

    2013-02-01

    We evaluated the prognostic accuracy of LN variables (N0/N1), numbers of positive lymph nodes (PLN), and lymph node ratio (LNR) in the context of the total number of examined lymph nodes (ELN). Patients from SEER and a single institution (MGH) were reviewed and survival analyses performed in subgroups based on numbers of ELN to calculate excess risk of death (hazard ratio, HR). In SEER and MGH, higher numbers of ELN improved the overall survival for N0 patients. The prognostic significance (N0/N1) and PLN were too variable as the importance of a single PLN depended on the total number of LN dissected. LNR consistently correlated with survival once a certain number of lymph nodes were dissected (≥13 in SEER and ≥17 in the MGH dataset). Better survival for N0 patients with increasing ELN likely represents improved staging. PLN have some predictive value but the ELN strongly influence their impact on survival, suggesting the need for a ratio-based classification. LNR strongly correlates with outcome provided that a certain number of lymph nodes is evaluated, suggesting that the prognostic accuracy of any LN variable depends on the total number of ELN.

  10. Stress-induced impairment of a working memory task: role of spiking rate and spiking history predicted discharge.

    Science.gov (United States)

    Devilbiss, David M; Jenison, Rick L; Berridge, Craig W

    2012-01-01

    Stress, pervasive in society, contributes to over half of all work place accidents a year and over time can contribute to a variety of psychiatric disorders including depression, schizophrenia, and post-traumatic stress disorder. Stress impairs higher cognitive processes, dependent on the prefrontal cortex (PFC) and that involve maintenance and integration of information over extended periods, including working memory and attention. Substantial evidence has demonstrated a relationship between patterns of PFC neuron spiking activity (action-potential discharge) and components of delayed-response tasks used to probe PFC-dependent cognitive function in rats and monkeys. During delay periods of these tasks, persistent spiking activity is posited to be essential for the maintenance of information for working memory and attention. However, the degree to which stress-induced impairment in PFC-dependent cognition involves changes in task-related spiking rates or the ability for PFC neurons to retain information over time remains unknown. In the current study, spiking activity was recorded from the medial PFC of rats performing a delayed-response task of working memory during acute noise stress (93 db). Spike history-predicted discharge (SHPD) for PFC neurons was quantified as a measure of the degree to which ongoing neuronal discharge can be predicted by past spiking activity and reflects the degree to which past information is retained by these neurons over time. We found that PFC neuron discharge is predicted by their past spiking patterns for nearly one second. Acute stress impaired SHPD, selectively during delay intervals of the task, and simultaneously impaired task performance. Despite the reduction in delay-related SHPD, stress increased delay-related spiking rates. These findings suggest that neural codes utilizing SHPD within PFC networks likely reflects an additional important neurophysiological mechanism for maintenance of past information over time. Stress

  11. Family history and frontal lobe seizures predict long-term remission in newly diagnosed cryptogenic focal epilepsy.

    Science.gov (United States)

    Gasparini, Sara; Ferlazzo, Edoardo; Beghi, Ettore; Tripepi, Giovanni; Labate, Angelo; Mumoli, Laura; Leonardi, Cinzia G; Cianci, Vittoria; Latella, Maria Adele; Gambardella, Antonio; Aguglia, Umberto

    2013-11-01

    Cryptogenic focal epilepsy (CFE) is a heterogeneous clinical disorder including patients with severe refractory forms and patients with a fairly good prognosis. Predictors of prognosis in CFE are poorly understood. The aim of this retrospective study is to identify long-term (5-year) prognostic predictors in patients with newly diagnosed CFE. Subjects with cryptogenic focal epilepsy (CFE) seen from April 1987 to September 2011 in two twin Epilepsy Centres located in Reggio Calabria and Catanzaro, Calabria, Southern Italy, were screened. Patients were excluded if they had psychogenic seizures, major psychiatric disorders presence of brain lesions except for non-specific white matter T2-hyperintensities, short follow-up (less than five years) or for having received the diagnosis of CFE elsewhere. One hundred and eighty-six patients, firstly diagnosed in our Centres, constituted the study sample. Survival curves were generated according to the Kaplan-Meier method and compared with the log-rank test. The endpoint was the cumulative time-dependent chance of 5-year remission after treatment start. Independent predictors of remission were tested by multivariate analysis using Cox proportional hazards function models. The accuracy of the resulting model was tested with Receiver Operating Characteristics (ROC) curve analysis. The cumulative incidence of remission was 23%. At Kaplan-Meier analysis, the only factor predicting remission was family history of epilepsy or febrile seizures (FS; p=0.02). At Cox regression, family history and frontal lobe epilepsy showed to be independent predictors of outcome (p=0.02 and 0.03, respectively). The accuracy of these predictors was good (area under ROC curve 0.648, 95% CI 0.575-0.716). Interestingly, we also found a considerable (7 years) diagnostic delay that did not result in a worse prognosis. About one quarter of subjects with newly diagnosed CFE attains 5-year seizure remission during follow-up. Family history of epilepsy or FS

  12. Beyond Coronary Calcification, Family History, and C-Reactive Protein: Cholesterol Efflux Capacity and Cardiovascular Risk Prediction.

    Science.gov (United States)

    Mody, Purav; Joshi, Parag H; Khera, Amit; Ayers, Colby R; Rohatgi, Anand

    2016-05-31

    Cholesterol efflux capacity (CEC), which is a key step in the reverse cholesterol transport pathway, is independently associated with atherosclerotic cardiovascular disease (ASCVD). However, whether it predicts ASCVD beyond validated novel risk markers is unknown. This study assessed if CEC improved ACSVD risk prediction beyond using coronary artery calcium (CAC), family history (FH), and high-sensitivity C-reactive protein (hs-CRP). CEC, CAC, self-reported FH, and hs-CRP were assessed among participants without baseline ASCVD who were enrolled in the Dallas Heart Study (DHS). ASCVD was defined as a first nonfatal myocardial infarction (MI) or stroke, coronary revascularization, or cardiovascular death, assessed over a median 9.4 years. Risk prediction was assessed using various modeling techniques and improvements in the c-statistic, the integrated discrimination index (IDI), and the net reclassification index (NRI). The mean age of the population (N = 1,972) was 45 years, 52% had CAC (>0), 31% had FH, and 58% had elevated hs-CRP (≥2 mg/l). CEC greater than the median was associated with a 50% reduced incidence of ASCVD in those with CAC (5.4% vs. 10.5%; p = 0.003), FH (5.8% vs. 10%; p = 0.05), and elevated hs-CRP (3.8% vs. 7.9%; p = 0.004). CEC improved all metrics of discrimination and reclassification when added to CAC (c-statistic, p = 0.004; IDI, p = 0.02; NRI: 0.38; 95% confidence interval [CI]: 0.13 to 0.53), FH (c-statistic, p = 0.006; IDI, p = 0.008; NRI: 0.38; 95% CI: 0.13 to 0.55), or elevated hs-CRP (c-statistic p = 0.008; IDI p = 0.02; NRI: 0.36; 95% CI 0.12 to 0.52). CEC improves ASCVD risk prediction beyond using CAC, FH, and hs-CRP and warrants consideration as a novel ASCVD risk marker. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  13. MRI does not add value over and above patient history and clinical examination in predicting time to return to sport after acute hamstring injuries: a prospective cohort of 180 male athletes.

    Science.gov (United States)

    Wangensteen, Arnlaug; Almusa, Emad; Boukarroum, Sirine; Farooq, Abdulaziz; Hamilton, Bruce; Whiteley, Rodney; Bahr, Roald; Tol, Johannes L

    2015-12-01

    MRI is frequently used in addition to clinical evaluation for predicting time to return to sport (RTS) after acute hamstring injury. However, the additional value of MRI to patient history taking and clinical examination remains unknown and is debated. To prospectively investigate the predictive value of patient history and clinical examination at baseline alone and the additional predictive value of MRI findings for time to RTS using multivariate analysis while controlling for treatment confounders. Male athletes (N=180) with acute onset posterior thigh pain underwent standardised patient history, clinical and MRI examinations within 5 days, and time to RTS was registered. A general linear model was constructed to assess the associations between RTS and the potential baseline predictors. A manual backward stepwise technique was used to keep treatment variables fixed. In the first multiple regression model including only patient history and clinical examination, maximum pain score (visual analogue scale, VAS), forced to stop within 5 min, length of hamstring tenderness and painful resisted knee flexion (90°), showed independent associations with RTS and the final model explained 29% of the total variance in time to RTS. By adding MRI variables in the second multiple regression model, maximum pain score (VAS), forced to stop within 5 min, length of hamstring tenderness and overall radiological grading, showed independent associations and the adjusted R(2) increased from 0.290 to 0.318. Thus, additional MRI explained 2.8% of the variance in RTS. There was a wide variation in time to RTS and the additional predictive value of MRI was negligible compared with baseline patient history taking and clinical examinations alone. Thus, clinicians cannot provide an accurate time to RTS just after an acute hamstring injury. This study provides no rationale for routine MRI after acute hamstring injury. ClinicalTrials.gov Identifier: NCT01812564. Published by the BMJ Publishing

  14. Family history of education predicts eating disorders across multiple generations among 2 million Swedish males and females.

    Science.gov (United States)

    Goodman, Anna; Heshmati, Amy; Koupil, Ilona

    2014-01-01

    To investigate which facets of parent and grandparent socio-economic position (SEP) are associated with eating disorders (ED), and how this varies by ED subtype and over time. Total-population cohort study of 1,040,165 females and 1,098,188 males born 1973-1998 in Sweden, and followed for inpatient or outpatient ED diagnoses until 2010. Proportional hazards models estimated associations with parental education, income and social class, and with grandparental education and income. 15,747 females and 1051 males in our sample received an ED diagnosis, with rates increasing in both sexes over time. ED incidence in females was independently predicted by greater educational level among the father, mother and maternal grandparents, but parent social class and parental income showed little or no independent effect. The associations with education were equally strong for anorexia nervosa, bulimia nervosa and ED not-otherwise-specified, and had increased over time. Among males, an apparently similar pattern was seen with respect to anorexia nervosa, but non-anorexia ED showed no association with parental education and an inverse association with parental income. Family history of education predicts ED in gender- and disorder-specific ways, and in females the effect is observed across multiple generations. Particularly given that these effects may have grown stronger in more recent cohorts, these findings highlight the need for further research to clarify the underlying mechanisms and identify promising targets for prevention. Speculatively, one such mechanism may involve greater internal and external demands for academic success in highly educated families.

  15. Family history of education predicts eating disorders across multiple generations among 2 million Swedish males and females.

    Directory of Open Access Journals (Sweden)

    Anna Goodman

    Full Text Available To investigate which facets of parent and grandparent socio-economic position (SEP are associated with eating disorders (ED, and how this varies by ED subtype and over time.Total-population cohort study of 1,040,165 females and 1,098,188 males born 1973-1998 in Sweden, and followed for inpatient or outpatient ED diagnoses until 2010. Proportional hazards models estimated associations with parental education, income and social class, and with grandparental education and income.15,747 females and 1051 males in our sample received an ED diagnosis, with rates increasing in both sexes over time. ED incidence in females was independently predicted by greater educational level among the father, mother and maternal grandparents, but parent social class and parental income showed little or no independent effect. The associations with education were equally strong for anorexia nervosa, bulimia nervosa and ED not-otherwise-specified, and had increased over time. Among males, an apparently similar pattern was seen with respect to anorexia nervosa, but non-anorexia ED showed no association with parental education and an inverse association with parental income.Family history of education predicts ED in gender- and disorder-specific ways, and in females the effect is observed across multiple generations. Particularly given that these effects may have grown stronger in more recent cohorts, these findings highlight the need for further research to clarify the underlying mechanisms and identify promising targets for prevention. Speculatively, one such mechanism may involve greater internal and external demands for academic success in highly educated families.

  16. Does life history predict past and current connectivity for rocky intertidal invertebrates across a marine biogeographic barrier?

    Science.gov (United States)

    Ayre, D J; Minchinton, T E; Perrin, C

    2009-05-01

    The southeast Australian coast potentially includes a complex biogeographic barrier, largely lacking exposed rocky shore that may limit the dispersal of rocky intertidal taxa and contribute to the maintenance of two biogeographic regions. Surprisingly, within the 300-km barrier region, several species considered exposed rocky shore specialists occurred within sheltered sites. We analysed COI sequence variation for 10 rocky intertidal invertebrate species, with a range of life histories, to test the hypotheses that larval type and habitat specificity are strong predictors of gene flow between biogeographic regions. Our data revealed that the southeast corner of Australia includes a strong barrier to gene flow for six of eight species with planktonic larvae, and a coalescence analysis of sequence differentiation (IM model) suggests that a barrier has existed since the Pleistocene. In contrast, two direct developers were not affected by the barrier. Our comparative approach and data from earlier studies (reviewed here) do not support the hypothesis that larval type predicts gene flow across this barrier, instead we found that the ability to utilize sheltered habitat provides a clearer explanation of the phylogeographic break. Indeed, the species that displayed little or no evidence of a phylogeographic break across the barrier each displayed unexpectedly relaxed habitat specificity.

  17. Parasympathetic nervous system activity predicts mood repair use and its effectiveness among adolescents with and without histories of major depression

    Science.gov (United States)

    Yaroslavsky, Ilya; Rottenberg, Jonathan; Bylsma, Lauren M.; Jennings, J. Richard; George, Charles; Baji, Ildikó; Benák, István; Dochnal, Roberta; Halas, Kitti; Kapornai, Krisztina; Kiss, Enikő; Makai, Attila; Varga, Hedvig; Vetró, Ágnes; Kovacs, Maria

    2016-01-01

    Depressive disorders that onset in the juvenile years have been linked to far reaching adverse consequences, making it imperative to elucidate key mechanisms and contributory factors. Excessive use of regulatory responses that exacerbate sadness (maladaptive mood repair) or insufficient use of regulatory responses that reduce it (adaptive mood repair) may reflect behavioral mechanisms of depression risk. Cardiac vagal control, indexed by patterns of respiratory sinus arrhythmia (RSA), has received attention as a putative physiological risk factor for depression. Although mood repair and RSA are related, the nature of this relationship is not well characterized in the context of depression risk. Therefore, we tested alternative models of the relationships between RSA patterns (at rest and in response to a sad film), trait mood repair, and the effectiveness of a mood repair response in the laboratory (state mood repair) among adolescents with depression histories (n=210) and emotionally healthy peers (n=161). In our data, a mediation model best explained the association between the key constructs: Adolescents with normative RSA patterns exhibited lower levels of depression and trait maladaptive mood repair, and benefited more from instructed (state) mood repair in the laboratory. By contrast, adolescents with atypical RSA patterns exhibited higher levels of depression and dispositional maladaptive mood repair, which, in turn, mediated the relations of RSA patterns and depression symptoms. Atypical RSA patterns also predicted reduced benefits from laboratory mood repair. PMID:26950752

  18. Flavanol concentrations do not predict dipeptidyl peptidase-IV inhibitory activities of four cocoas with different processing histories.

    Science.gov (United States)

    Ryan, Caroline M; Khoo, Weslie; Stewart, Amanda C; O'Keefe, Sean F; Lambert, Joshua D; Neilson, Andrew P

    2017-02-22

    Cocoa and its constituent bioactives (particularly flavanols) have reported anti-diabetic and anti-obesity activities. One potential mechanism of action is inhibition of dipeptidyl peptidase-IV (DPP4), the enzyme that inactivates incretin hormones such as glucagon-like peptide-1 and gastric inhibitory peptide. The objective of this study was to determine the DPP4 inhibitory activities of cocoas with different processing histories, and identify processing factors and bioactive compounds that predict DPP4 inhibition. IC25 values (μg mL-1) were 4.82 for Diprotin A (positive control), 2135 for fermented bean extract, 1585 for unfermented bean extract, 2871 for unfermented liquor extract, and 1076 for fermented liquor extract This suggests mild inhibitory activity. Surprisingly, protein binding activity, total polyphenol, total flavanol, individual flavanol and complex fermentation/roasting product levels were all positively correlated to IC25 concentrations (greater levels correspond to less potent inhibition). For the representative samples studied, fermentation appeared to improve inhibition. This study suggests that cocoa may possess mild DPP4 inhibitory activity, and that processing steps such as fermentation may actually enhance activity. Furthermore, this activity and the variation between samples were not easily explainable by traditional putative bioactives in cocoa. The compounds driving this activity, and the associated mechanism(s) by which this inhibition occurs, remain to be elucidated.

  19. Incorporating Ninth-Grade PSAT/NMSQT® Scores into AP Potential™ Predictions for AP® European History and AP World History. Statistical Report 2014-1

    Science.gov (United States)

    Zhang, Xiuyuan; Patel, Priyank; Ewing, Maureen

    2015-01-01

    Historically, AP Potential™ correlations and expectancy tables have been based on 10th-and 11th-grade PSAT/NMSQT® examinees and 11th-and 12th-grade AP® examinees for all subjects (Zhang, Patel, & Ewing,2014; Ewing, Camara, & Millsap, 2006; Camara & Millsap, 1998). However, a large number of students take AP European History and AP…

  20. Monitoring and predicting the risk of violence in residential facilities. No difference between patients with history or with no history of violence.

    Science.gov (United States)

    de Girolamo, Giovanni; Buizza, Chiara; Sisti, Davide; Ferrari, Clarissa; Bulgari, Viola; Iozzino, Laura; Boero, Maria Elena; Cristiano, Giuseppe; De Francesco, Alessandra; Giobbio, Gian Marco; Maggi, Paolo; Rossi, Giuseppe; Segalini, Beatrice; Candini, Valentina

    2016-09-01

    Most people with mental disorders are not violent. However, the lack of specific studies in this area and recent radical changes in Italy, including the closure of six Forensic Mental Hospitals, has prompted a more detailed investigation of patients with aggressive behaviour. To compare socio-demographic, clinical and treatment-related characteristics of long-term inpatients with a lifetime history of serious violence with controls; to identify predictors of verbal and physical aggressive behaviour during 1-year follow-up. In a prospective cohort study, patients living in Residential Facilities (RFs) with a lifetime history of serious violence were assessed with a large set of standardized instruments and compared to patients with no violent history. Patients were evaluated bi-monthly with MOAS in order to monitor any aggressive behaviour. The sample included 139 inpatients, 82 violent and 57 control subjects; most patients were male. The bi-monthly monitoring during the 1-year follow-up did not show any statistically significant differences in aggressive behaviour rates between the two groups. The subscale explaining most of the MOAS total score was aggression against objects, although verbal aggression was the most common pattern. Furthermore, verbal aggression was significantly associated with aggression against objects and physical aggression. Patients with a history of violence in RFs, where treatment and clinical supervision are available, do not show higher rates of aggressiveness compared to patients with no lifetime history of violence. Since verbal aggression is associated with more severe forms of aggression, prompt intervention is warranted to reduce the risk of escalation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Can Selforganizing Maps Accurately Predict Photometric Redshifts?

    Science.gov (United States)

    Way, Michael J.; Klose, Christian

    2012-01-01

    We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using delta(z) = z(sub phot) - z(sub spec)) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods

  2. Predicting Attitudes toward Press- and Speech Freedom across the U.S.A.: A Test of Climato-Economic, Parasite Stress, and Life History Theories.

    Science.gov (United States)

    Zhang, Jinguang; Reid, Scott A; Xu, Jing

    2015-01-01

    National surveys reveal notable individual differences in U.S. citizens' attitudes toward freedom of expression, including freedom of the press and speech. Recent theoretical developments and empirical findings suggest that ecological factors impact censorship attitudes in addition to individual difference variables (e.g., education, conservatism), but no research has compared the explanatory power of prominent ecological theories. This study tested climato-economic, parasite stress, and life history theories using four measures of attitudes toward censoring the press and offensive speech obtained from two national surveys in the U.S.A. Neither climate demands nor its interaction with state wealth--two key variables for climato-economic theory--predicted any of the four outcome measures. Interstate parasite stress significantly predicted two, with a marginally significant effect on the third, but the effects became non-significant when the analyses were stratified for race (as a control for extrinsic risks). Teenage birth rates (a proxy of human life history) significantly predicted attitudes toward press freedom during wartime, but the effect was the opposite of what life history theory predicted. While none of the three theories provided a fully successful explanation of individual differences in attitudes toward freedom of expression, parasite stress and life history theories do show potentials. Future research should continue examining the impact of these ecological factors on human psychology by further specifying the mechanisms and developing better measures for those theories.

  3. Predicting Attitudes toward Press- and Speech Freedom across the U.S.A.: A Test of Climato-Economic, Parasite Stress, and Life History Theories.

    Directory of Open Access Journals (Sweden)

    Jinguang Zhang

    Full Text Available National surveys reveal notable individual differences in U.S. citizens' attitudes toward freedom of expression, including freedom of the press and speech. Recent theoretical developments and empirical findings suggest that ecological factors impact censorship attitudes in addition to individual difference variables (e.g., education, conservatism, but no research has compared the explanatory power of prominent ecological theories. This study tested climato-economic, parasite stress, and life history theories using four measures of attitudes toward censoring the press and offensive speech obtained from two national surveys in the U.S.A. Neither climate demands nor its interaction with state wealth--two key variables for climato-economic theory--predicted any of the four outcome measures. Interstate parasite stress significantly predicted two, with a marginally significant effect on the third, but the effects became non-significant when the analyses were stratified for race (as a control for extrinsic risks. Teenage birth rates (a proxy of human life history significantly predicted attitudes toward press freedom during wartime, but the effect was the opposite of what life history theory predicted. While none of the three theories provided a fully successful explanation of individual differences in attitudes toward freedom of expression, parasite stress and life history theories do show potentials. Future research should continue examining the impact of these ecological factors on human psychology by further specifying the mechanisms and developing better measures for those theories.

  4. Accurate ab initio calculations of O-HO and O-H(-)O proton chemical shifts: towards elucidation of the nature of the hydrogen bond and prediction of hydrogen bond distances.

    Science.gov (United States)

    Siskos, Michael G; Tzakos, Andreas G; Gerothanassis, Ioannis P

    2015-09-07

    The inability to determine precisely the location of labile protons in X-ray molecular structures has been a key barrier to progress in many areas of molecular sciences. We report an approach for predicting hydrogen bond distances beyond the limits of X-ray crystallography based on accurate ab initio calculations of O-HO proton chemical shifts, using a combination of DFT and contactor-like polarizable continuum model (PCM). Very good linear correlation between experimental and computed (at the GIAO/B3LYP/6-311++G(2d,p) level of theory) chemical shifts were obtained with a large set of 43 compounds in CHCl3 exhibiting intramolecular O-HO and intermolecular and intramolecular ionic O-H(-)O hydrogen bonds. The calculated OH chemical shifts exhibit a strong linear dependence on the computed (O)HO hydrogen bond length, in the region of 1.24 to 1.85 Å, of -19.8 ppm Å(-1) and -20.49 ppm Å(-1) with optimization of the structures at the M06-2X/6-31+G(d) and B3LYP/6-31+G(d) level of theory, respectively. A Natural Bond Orbitals (NBO) analysis demonstrates a very good linear correlation between the calculated (1)H chemical shifts and (i) the second-order perturbation stabilization energies, corresponding to charge transfer between the oxygen lone pairs and σ antibonding orbital and (ii) Wiberg bond order of the O-HO and O-H(-)O hydrogen bond. Accurate ab initio calculations of O-HO and O-H(-)O (1)H chemical shifts can provide improved structural and electronic description of hydrogen bonding and a highly accurate measure of distances of short and strong hydrogen bonds.

  5. The Relative Importance of Family History, Gender, Mode of Onset, and Age at Onsetin Predicting Clinical Features of First-Episode Psychotic Disorders.

    Science.gov (United States)

    Compton, Michael T; Berez, Chantal; Walker, Elaine F

    Family history of psychosis, gender, mode of onset, and age at onset are considered prognostic factors important to clinicians evaluating first-episode psychosis; yet, clinicians have little guidance as to how these four factors differentially predict early-course substance abuse, symptomatology, and functioning. We conducted a "head-to-head comparison" of these four factors regarding their associations with key clinical features at initial hospitalization. We also assessed potential interactions between gender and family history with regard to age at onset of psychosis and symptom severity. Consecutively admitted first-episode patients (n=334) were evaluated in two studies that rigorously assessed a number of early-course variables. Associations among variables of interest were examined using Pearson correlations, χ 2 tests, Student's t-tests, and 2×2 factorial analyses of variance. Substance (nicotine, alcohol, and cannabis) abuse and positive symptom severity were predicted only by male gender. Negative symptom severity and global functioning impairments were predicted by earlier age at onset of psychosis. General psychopathology symptom severity was predicted by both mode of onset and age at onset. Interaction effects were not observed with regard to gender and family history in predicting age at onset or symptom severity. The four prognostic features have differential associations with substance abuse, domains of symptom severity, and global functioning. Gender and age at onset of psychosis appear to be more predictive of clinical features at the time of initial evaluation (and thus presumably longer term outcomes) than the presence of a family history of psychosis and a more gradual mode of onset.

  6. Predicting regular breast cancer screening in African-American women with a family history of breast cancer.

    Science.gov (United States)

    Laing, Sharon S; Makambi, Kepher

    2008-11-01

    To evaluate the impact of socioeconomic, personal and affective factors on regular breast cancer screening in at-risk African-American women. The study was a cross-sectional analysis assessing socioeconomic and affective predictors of breast cancer screening practices. Unaffected African-American women ages 40-64 with a family history of breast cancer were recruited from community settings. The main outcome measures were recent mammography, regular mammography and regular breast self-examinations. The majority of women reported having a recent mammogram (73%) and yearly mammograms (71%). More than half (56%) reported monthly breast self-examinations (BSEs). Available health insurance and risk perception had significant independent associations with regular mammography screening so that women having a mammogram every 6-12 months were more likely to have health insurance [odds ratio (OR)=4.99, 95% confidence interval (CI): 1.05-23.52], and women not engaged in regular screenings were less likely to perceive future breast cancer risk (OR=0.10, 95% CI: 0.01-0.96). Access to regular healthcare had a significant independent association with recent mammography so that women having a mammogram in the past 12 months were more likely to have access to regular healthcare (OR=6.59, 95% CI: 1.01-42.79). A significant majority of this subset of African-American women engage in repeat mammography screenings with cognitive and economic factors predicting noncompliance. Additional research with repeat mammography users is required so that regular screening practices can be encouraged among all at-risk women.

  7. 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.

  8. The predictability and magnitude of life-history divergence to ecological agents of selection: a meta-analysis in livebearing fishes.

    Science.gov (United States)

    Moore, Michael P; Riesch, Rüdiger; Martin, Ryan A

    2016-04-01

    Environments causing variation in age-specific mortality - ecological agents of selection - mediate the evolution of reproductive life-history traits. However, the relative magnitude of life-history divergence across selective agents, whether divergence in response to specific selective agents is consistent across taxa and whether it occurs as predicted by theory, remains largely unexplored. We evaluated divergence in offspring size, offspring number, and the trade-off between these traits using a meta-analysis in livebearing fishes (Poeciliidae). Life-history divergence was consistent and predictable to some (predation, hydrogen sulphide) but not all (density, food limitation, salinity) selective agents. In contrast, magnitudes of divergence among selective agents were similar. Finally, there was a negative, asymmetric relationship between offspring-number and offspring-size divergence, suggesting greater costs of increasing offspring size than number. Ultimately, these results provide strong evidence for predictable and consistent patterns of reproductive life-history divergence and highlight the importance of comparing phenotypic divergence across species and ecological selective agents. © 2016 John Wiley & Sons Ltd/CNRS.

  9. Grading More Accurately

    Science.gov (United States)

    Rom, Mark Carl

    2011-01-01

    Grades matter. College grading systems, however, are often ad hoc and prone to mistakes. This essay focuses on one factor that contributes to high-quality grading systems: grading accuracy (or "efficiency"). I proceed in several steps. First, I discuss the elements of "efficient" (i.e., accurate) grading. Next, I present analytical results…

  10. Accurate lineshape spectroscopy and the Boltzmann constant.

    Science.gov (United States)

    Truong, G-W; Anstie, J D; May, E F; Stace, T M; Luiten, A N

    2015-10-14

    Spectroscopy has an illustrious history delivering serendipitous discoveries and providing a stringent testbed for new physical predictions, including applications from trace materials detection, to understanding the atmospheres of stars and planets, and even constraining cosmological models. Reaching fundamental-noise limits permits optimal extraction of spectroscopic information from an absorption measurement. Here, we demonstrate a quantum-limited spectrometer that delivers high-precision measurements of the absorption lineshape. These measurements yield a very accurate measurement of the excited-state (6P1/2) hyperfine splitting in Cs, and reveals a breakdown in the well-known Voigt spectral profile. We develop a theoretical model that accounts for this breakdown, explaining the observations to within the shot-noise limit. Our model enables us to infer the thermal velocity dispersion of the Cs vapour with an uncertainty of 35 p.p.m. within an hour. This allows us to determine a value for Boltzmann's constant with a precision of 6 p.p.m., and an uncertainty of 71 p.p.m.

  11. Family history of suicide and exposure to interpersonal violence in childhood predict suicide in male suicide attempters.

    Science.gov (United States)

    Rajalin, Mia; Hirvikoski, Tatja; Jokinen, Jussi

    2013-05-15

    Family studies, including twin and adoption designs, have shown familial transmission of suicidal behaviors. Early environmental risk factors have an important role in the etiology of suicidal behavior. The aim of the present study was to assess the impact of family history of suicide and childhood trauma on suicide risk and on severity of suicide attempt in suicide attempters. A total of 181 suicide attempters were included. Family history of suicide was assessed with the Karolinska Suicide History Interview or through patient records. Childhood trauma was assessed with the Karolinska Interpersonal Violence Scale (KIVS) measuring exposure to violence and expressed violent behavior in childhood (between 6 and 14 years of age) and during adult life (15 years or older). Suicide intent was measured with the Freeman scale. Male suicide attempters with a positive family history of suicide made more serious and well planned suicide attempts and had a significantly higher suicide risk. In logistic regression, family history of suicide and exposure to interpersonal violence as a child were independent predictors of suicide in male suicide attempters. The information about family history of suicide and exposure to interpersonal violence as a child derives from the patients only. In the first part of the inclusion period the information was collected from patient records. The results of this study imply that suicides among those at biological risk might be prevented with the early recognition of environmental risks. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Improving long-term prediction of first cardiovascular event: the contribution of family history of coronary heart disease and social status.

    Science.gov (United States)

    Veronesi, G; Gianfagna, F; Giampaoli, S; Chambless, L E; Mancia, G; Cesana, G; Ferrario, M M

    2014-07-01

    The aim of this study is to assess whether family history of coronary heart disease (CHD) and education as proxy of social status improve long-term cardiovascular disease risk prediction in a low-incidence European population. The 20-year risk of first coronary or ischemic stroke events was estimated using sex-specific Cox models in 3956 participants of three population-based surveys in northern Italy, aged 35-69 years and free of cardiovascular disease at enrollment. The additional contribution of education and positive family history of CHD was defined as change in discrimination and Net Reclassification Improvement (NRI) over the model including 7 traditional risk factors. Kaplan-Meier 20-year risk was 16.8% in men (254 events) and 6.4% in women (102 events). Low education (hazard ratio=1.35, 95%CI 0.98-1.85) and family history of CHD (1.55; 1.19-2.03) were associated with the endpoint in men, but not in women. In men, the addition of education and family history significantly improved discrimination by 1%; NRI was 6% (95%CI: 0.2%-15.2%), raising to 20% (0.5%-44%) in those at intermediate risk. NRI in women at intermediate risk was 7%. In low-incidence populations, family history of CHD and education, easily assessed in clinical practice, should be included in long-term cardiovascular disease risk scores, at least in men. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Development of a Prediction Model for Diagnosis of Acute Poisoning in Patients with Altered Mental Status and Absent History of Alcohol/Drug Ingestion.

    Science.gov (United States)

    Camilleri, Robert

    2017-11-01

    Diagnosis of acute poisoning in patients with altered mental status and absent history is a challenging diagnostic problem in clinical practice. The aims of the study were to develop a simple clinical tool to stratify risk of acute poisoning in patients with altered mental states and no history of alcohol/drug ingestion, and develop a prediction model using initial observations from which a simple risk score could be derived. The study was carried out on non-trauma patients aged 15 years and older admitted with altered mental states and no history of alcohol or drug ingestion. Univariate analysis and logistic regression were carried out and a score was derived and validated. There were 607 patients included, with mean age of 60.3 years and 54% were male. The regression model performed moderately well on both the training and validation sets with areas under the receiver operating characteristic curve of 0.834 and 0.844, respectively. The risk score correlated with the regression model (R2 = 0.969). At cutoff thresholds of 20% for the model and 2 for the score, sensitivity and specificity of the regression model (67.6% and 85.6%) and the score (67.6% and 85.4%) were moderate, while positive predictive values were low (43.4%) and negative predictive values were high (94.2%) for both the regression model and the score. A prediction model with a derived risk score was developed with a high negative predictive value and may have potential in assessing risk of poisoning in altered mental status and may have value in a prehospital environment or at triage. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Feedback about More Accurate versus Less Accurate Trials: Differential Effects on Self-Confidence and Activation

    Science.gov (United States)

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-01-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected by feedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On Day 1, participants performed a golf putting task under one of…

  15. Predicting Adolescents' Organized Activity Involvement: The Role of Maternal Depression History, Family Relationship Quality, and Adolescent Cognitions

    Science.gov (United States)

    Bohnert, Amy M.; Martin, Nina C.; Garber, Judy

    2007-01-01

    Although the potential benefits of organized activity involvement during high school have been documented, little is known about what familial and individual characteristics are associated with higher levels of participation. Using structural equation modeling, this longitudinal study examined the extent to which maternal depression history (i.e.,…

  16. Predicting Nitrogen Availability to Rice: II. Assessing Available Nitrogen in Silt Loams With Different Previous Year Crop History

    Science.gov (United States)

    J. L. Sims; B. G. Blackmon

    1967-01-01

    Soil test method s that measure NH4+-N in silt 100ms before and after incubation under waterlogged conditions were evaluated as predictors of N availability to 'Nato' rice (Oriza sativa L.) frown in the greenhouse. Eighteen soils for each of five previous year crop histories were utilized. An soils were from crop rotations containing rice....

  17. Pace of life, predators and parasites: predator-induced life-history evolution in Trinidadian guppies predicts decrease in parasite tolerance.

    Science.gov (United States)

    Stephenson, J F; van Oosterhout, C; Cable, J

    2015-11-01

    A common evolutionary response to predation pressure is increased investment in reproduction, ultimately resulting in a fast life history. Theory and comparative studies suggest that short-lived organisms invest less in defence against parasites than those that are longer lived (the pace of life hypothesis). Combining these tenets of evolutionary theory leads to the specific, untested prediction that within species, populations experiencing higher predation pressure invest less in defence against parasites. The Trinidadian guppy, Poecilia reticulata, presents an excellent opportunity to test this prediction: guppy populations in lower courses of rivers experience higher predation pressure, and as a consequence have evolved faster life histories, than those in upper courses. Data from a large-scale field survey showed that fish infected with Gyrodactylus parasites were of a lower body condition (quantified using the scaled mass index) than uninfected fish, but only in lower course populations. Although the evidence we present is correlational, it suggests that upper course guppies sustain lower fitness costs of infection, i.e. are more tolerant, than lower course guppies. The data are therefore consistent with the pace of life hypothesis of parasite defence allocation, and suggest that life-history traits mediate the indirect effect of predators on the parasites of their prey. © 2015 The Author(s).

  18. Factors associated with referral to mental health services among suicide attempters visiting emergency centers of general hospitals in Korea: does history of suicide attempts predict referral?

    Science.gov (United States)

    Jo, Sun-Jin; Lee, Myung-Soo; Yim, Hyeon Woo; Kim, Han Joon; Lee, Kyeongryong; Chung, Hyun Soo; Cho, Junho; Choi, Seung-Pil; Seo, Young Mi

    2011-01-01

    This study examined whether a history of past suicide attempts was a critical factor for referral to mental health services among suicide attempters visiting emergency centers of general hospitals in Korea. In this cross-sectional study, a resident of emergency medicine at each emergency center interviewed 310 suicide attempters visiting five tertiary general hospitals located in Seoul, using standardized questionnaires, during 7 months in 2007. We examined associations between suicide attempt history and referral to mental health services via multiple logistic regressions. Subjects' rate of referral to mental health services was 47.3%. When we controlled for participant age, time of arrival at the emergency center, psychiatric treatment history, use of alcohol, suicide attempt lethality and subjective expectation to suicide attempts, past suicide attempts did not predict referral to mental health services (odds ratio=1.74; 95% confidence interval .88-3.43). Psychiatric interventions for suicide reattempters visiting emergency centers are important for preventing suicide, but providers have not considered suicide attempt history as a critical factor for referral to mental health services. Therefore, we suggest that more effort is needed to systemize psychiatric interventions for suicide reattempters at emergency centers in Korea. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. Birth Weight Predicts Scores on the ADHD Self-Report Scale and Attitudes towards Casual Sex in College Men: A Short-Term Life History Strategy?

    Directory of Open Access Journals (Sweden)

    Michael J. Frederick

    2012-04-01

    Full Text Available Early development can have long-term effects on physiology and behavior. While severe disturbances predictably lead to dysfunction, recent work in humans and animals has led to a growing appreciation for the more subtle ways in which early conditions can modulate behavioral tendencies later in life. Life history theory predicts that early cues signaling a stressful or suboptimal environment might lead an organism to adopt a strategy favoring short-term gains and early reproduction. Fifty college men reported their birth weight, completed the Attention-Deficit/Hyperactivity Disorder (ADHD Self-Report Scale, and answered a series of questions about their sexual history and attitudes towards short-term sexual encounters. Lower birth weights were associated with higher scores on the ADHD scale (r = −.352; p ≤ .05 and more favorable attitudes towards casual sex (r = −.456; p ≤ 0.001. There was a significant interaction between birth weight and casual sex favorability in predicting number of sexual partners (F1,46 = 4.994; p ≤ .05. This suggests that, although men who are smaller at birth may otherwise be at a disadvantage in reproductive terms, they may offset their reduced fitness by being more willing to engage in casual sex.

  20. Histories of abuse predict stronger within-person covariation of ovarian steroids and mood symptoms in women with menstrually related mood disorder.

    Science.gov (United States)

    Eisenlohr-Moul, Tory A; Rubinow, David R; Schiller, Crystal E; Johnson, Jacqueline L; Leserman, Jane; Girdler, Susan S

    2016-05-01

    Individual differences in sensitivity to cyclical changes in ovarian steroids estradiol (E2) and progesterone (P4) have been implicated in the pathophysiology of menstrually related mood disorder (MRMD). However, no prospective studies have investigated psychosocial risk factors for sensitivity to hormone effects on mood in MRMD. Using a repeated measures approach and multilevel models, we tested the hypothesis that a history of abuse provides a context in which within-person elevations of E2 and P4 prospectively predict daily symptoms. 66 women with prospectively-confirmed MRMD recruited for a trial of oral contraceptives provided 1 month of baseline hormone and mood data prior to randomization. Lifetime physical and sexual abuse experiences were assessed. Across one cycle, women completed daily measures of symptoms and provided blood samples on 5 days across the menstrual cycle. Current E2 and P4 were centered within person (CWP) such that higher values represented cyclical elevations in hormones. Rates of physical (27%) and sexual (29%) abuse were high, consistent with previous work documenting a link between trauma and MRMD. In women with a history of physical abuse, cyclical increases in P4 predicted greater mood and interpersonal symptoms on the three days following that sample. In women with a history of sexual abuse, cyclical increases in E2 predicted greater anxiety symptoms on the three days following that sample. Results inform further inquiry into the role of severe life stressors and stress response systems in MRMD. We discuss areas for future research on the psychosocial and physiological pathways through which abuse may influence the link between hormones and symptoms. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics::a dual cohort study

    OpenAIRE

    Evans, Dafydd; Astley, Susan; Stavrinos, Paula; Harkness, Elaine; Donnelly, Louise S; Dawe, Sarah; Jacob, Ian; Harvie, Michelle; Cuzick, Jack; Brentnall, Adam R.; Wilson, Mary; Harrison, Fiona; Payne, Katherine; Howell, Anthony

    2016-01-01

    Background: In the UK, women are invited for 3-yearly mammography screening, through the NHS Breast Screening Programme (NHSBSP), from the ages of 47–50 years to the ages of 69–73 years. Women with family histories of breast cancer can, from the age of 40 years, obtain enhanced surveillance and, in exceptionally high-risk cases, magnetic resonance imaging. However, no NHSBSP risk assessment is undertaken. Risk prediction models are able to categorise women by risk using known risk factors, al...

  2. Model-based Purchase Predictions for Large Assortments

    NARCIS (Netherlands)

    B.J.D. Jacobs (Bruno); A.C.D. Donkers (Bas); D. Fok (Dennis)

    2016-01-01

    textabstractBeing able to accurately predict what a customer will purchase next is of paramount importance to successful online retailing. In practice, customer purchase history data is readily available to make such predictions, sometimes complemented with customer characteristics. Given the large

  3. Accuracy and predictive value of incarcerated adults' accounts of their self-harm histories: findings froman Australian prospective data linkage study.

    Science.gov (United States)

    Borschmann, Rohan; Young, Jesse T; Moran, Paul; Spittal, Matthew J; Snow, Kathryn; Mok, Katherine; Kinner, Stuart A

    2017-09-11

    Self-harm is prevalent in prison populations and is a well-established risk factor for suicide. Researchers typically rely on self-report to measure self-harm, yet the accuracy and predictive value of self-report in prison populations is unclear. Using a large, representative sample of incarcerated men and women, we aimed to examine the level of agreement between self-reported self-harm history and historical medical records, and investigate the association between self-harm history and medically verified self-harm after release from prison. During confidential interviews with 1315 adults conducted within 6 weeks of expected release from 1 of 7 prisons in Queensland, Australia, participants were asked about the occurrence of lifetime self-harm. Responses were compared with prison medical records and linked both retrospectively and prospectively with ambulance, emergency department and hospital records to identify instances of medically verified self-harm. Follow-up interviews roughly 1, 3 and 6 months after release covered the same domains assessed in the baseline interview as well as self-reported criminal activity and contact with health care, social and criminal justice services since release. Agreement between self-reported and medically verified history of self-harm was poor, with 64 (37.6%) of 170 participants with a history of medically verified self-harm disclosing a history of self-harm at baseline. Participants with a medically verified history of self-harm were more likely than other participants to self-harm during the follow-up period. Compared to the unconfirmed-negative group, the true-positive (adjusted hazard ratio [HR] 6.2 [95% confidence interval (CI) 3.3-10.4]), false-negative (adjusted HR 4.0 [95% CI 2.2-6.7]) and unconfirmed-positive (adjusted HR 2.2 [95% CI 1.2-3.9]) groups were at increased risk for self-harm after release from prison. Self-reported history of self-harm should not be considered a sensitive indicator of prior self-harm or of

  4. BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE ...

    Science.gov (United States)

    Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contaminated soils. Relative bioavailabilities were expressed by comparison with blood Pb concentrations in quail fed a Pb acetate reference diet. Diets containing soil from five Pb-contaminated Superfund sites had relative bioavailabilities from 33%-63%, with a mean of about 50%. Treatment of two of the soils with P significantly reduced the bioavailability of Pb. The bioaccessibility of the Pb in the test soils was then measured in six in vitro tests and regressed on bioavailability. They were: the “Relative Bioavailability Leaching Procedure” (RBALP) at pH 1.5, the same test conducted at pH 2.5, the “Ohio State University In vitro Gastrointestinal” method (OSU IVG), the “Urban Soil Bioaccessible Lead Test”, the modified “Physiologically Based Extraction Test” and the “Waterfowl Physiologically Based Extraction Test.” All regressions had positive slopes. Based on criteria of slope and coefficient of determination, the RBALP pH 2.5 and OSU IVG tests performed very well. Speciation by X-ray absorption spectroscopy demonstrated that, on average, most of the Pb in the sampled soils was sorbed to minerals (30%), bound to organic matter 24%, or present as Pb sulfate 18%. Ad

  5. The Role of Metacognitive Reading Strategies, Metacognitive Study and Learning Strategies, and Behavioral Study and Learning Strategies in Predicting Academic Success in Students with and without a History of Reading Difficulties

    Science.gov (United States)

    Chevalier, Thérèse M.; Parrila, Rauno; Ritchie, Krista C.; Deacon, S. Hélène

    2017-01-01

    We examined the self-reported use of reading, study, and learning strategies in university students with a history of reading difficulties (HRD; n = 77) and with no history of reading difficulties (NRD; n = 295). We examined both between-groups differences in strategy use and strategy use as a predictive measure of academic success. Participants…

  6. Estimating the risk of gestational diabetes mellitus : a clinical prediction model based on patient characteristics and medical history

    NARCIS (Netherlands)

    van Leeuwen, M.; Opmeer, B. C.; Zweers, E. J. K.; van Ballegooie, E.; ter Brugge, H. G.; de Valk, H. W.; Visser, G. H. A.; Mol, B. W. J.

    Objective To develop a clinical prediction rule that can help the clinician to identify women at high and low risk for gestational diabetes mellitus (GDM) early in pregnancy in order to improve the efficiency of GDM screening. Design We used data from a prospective cohort study to develop the

  7. High neuroticism at age 20 predicts history of mental disorders and low self-esteem at age 35.

    Science.gov (United States)

    Lönnqvist, Jan-Erik; Verkasalo, Markku; Mäkinen, Seppo; Henriksson, Markus

    2009-07-01

    The authors assessed whether neuroticism in emerging adulthood predicts mental disorders and self-esteem in early adulthood after controlling for possible confounding variables. A sample of 69 male military conscripts was initially assessed at age 20 and again as civilians at age 35. The initial assessment included a psychiatric interview, objective indicators of conscript competence, an intellectual performance test, and neuroticism questionnaires. The follow-up assessment included a Structured Clinical Interview for DSM-IV (SCID; First, Spitzer, Gibbon, & Williams, 1996) and the Rosenberg Self-Esteem Scale (Rosenberg, 1965). Neuroticism predicted future mental disorders and low self-esteem beyond more objective indicators of adjustment. The results support the use of neuroticism as a predictor of future mental disorders, even over periods of time when personality is subject to change.

  8. Parental history of hypertension and coping responses predict blood pressure changes in black college volunteers undergoing a speaking task about perceptions of racism.

    Science.gov (United States)

    Clark, Rodney

    2003-01-01

    This investigation explored the relationship of coping responses and parental history of hypertension to task-induced blood pressure changes. The sample consisted of 215 black college student volunteers (median age = 25.95 y). During the speaking task, participants responded to standardized questions about perceptions of intra-ethnic and inter-ethnic group racism. Systolic blood pressure and diastolic blood pressure were measured via an automated blood pressure monitor. Usual ways of coping with intra-ethnic group racism were assessed with the COPE Scale, and parental history of hypertension (PHH) was self-reported by participants. Findings from the final step of hierarchical general linear models indicated that the main effect of emotion-focused coping was negatively associated with diastolic blood pressure (p = 0.02) and systolic blood pressure (p = 0.002) changes. Further, these analyses revealed that PHH interacted: (1) with the coping responses of planning (p = 0.007) and denial (p = 0.002) to predict changes in systolic blood pressure and (2) with the planning coping response to predict diastolic blood pressure changes (p = 0.02). The direction of these effects indicated that among participants who were high in these coping responses, participants who also had a positive PHH had larger blood pressure changes. Regression analyses also revealed that PHH interacted with the cognitive coping response (p = 0.01) to predict changes in systolic blood pressure. The direction of this effect indicated that among participants who were low in this coping response, participants who also had a positive PHH had larger systolic blood pressure changes. This study highlights the importance of examining the joint contribution of biological and psychosocial parameters to blood pressure reactivity in blacks.

  9. Groundwater recharge: Accurately representing evapotranspiration

    CSIR Research Space (South Africa)

    Bugan, Richard DH

    2011-09-01

    Full Text Available Groundwater recharge is the basis for accurate estimation of groundwater resources, for determining the modes of water allocation and groundwater resource susceptibility to climate change. Accurate estimations of groundwater recharge with models...

  10. Seascape and life-history traits do not predict self-recruitment in a coral reef fish

    KAUST Repository

    Herrera Sarrias, Marcela

    2016-08-10

    The persistence and resilience of many coral reef species are dependent on rates of connectivity among sub-populations. However, despite increasing research efforts, the spatial scale of larval dispersal remains unpredictable for most marine metapopulations. Here, we assess patterns of larval dispersal in the angelfish Centropyge bicolor in Kimbe Bay, Papua New Guinea, using parentage and sibling reconstruction analyses based on 23 microsatellite DNA loci. We found that, contrary to previous findings in this system, self-recruitment (SR) was virtually absent at both the reef (0.4-0.5% at 0.15 km2) and the lagoon scale (0.6-0.8% at approx. 700 km2). While approximately 25%of the collected juveniles were identified as potential siblings, the majority of sibling pairs were sampled from separate reefs. Integrating our findings with earlier research from the same system suggests that geographical setting and life-history traits alone are not suitable predictors of SR and that high levels of localized recruitment are not universal in coral reef fishes. © 2016 The Authors.

  11. MRI does not add value over and above patient history and clinical examination in predicting time to return to sport after acute hamstring injuries: a prospective cohort of 180 male athletes

    NARCIS (Netherlands)

    Wangensteen, Arnlaug; Almusa, Emad; Boukarroum, Sirine; Farooq, Abdulaziz; Hamilton, Bruce; Whiteley, Rodney; Bahr, Roald; Tol, Johannes L.

    2015-01-01

    MRI is frequently used in addition to clinical evaluation for predicting time to return to sport (RTS) after acute hamstring injury. However, the additional value of MRI to patient history taking and clinical examination remains unknown and is debated. To prospectively investigate the predictive

  12. An Australian nationwide survey on medicinal cannabis use for epilepsy: History of antiepileptic drug treatment predicts medicinal cannabis use.

    Science.gov (United States)

    Suraev, Anastasia S; Todd, Lisa; Bowen, Michael T; Allsop, David J; McGregor, Iain S; Ireland, Carol; Lintzeris, Nicholas

    2017-05-01

    Epilepsy Action Australia conducted an Australian nationwide online survey seeking opinions on and experiences with the use of cannabis-based products for the treatment of epilepsy. The survey was promoted via the Epilepsy Action Australia's main website, on their Facebook page, and by word of mouth. The survey consisted of 39 questions assessing demographics, clinical factors, including diagnosis and seizure types, and experiences with and opinions towards cannabis use in epilepsy. A total of 976 responses met the inclusion criteria. Results show that 15% of adults with epilepsy and 13% of parents/guardians of children with epilepsy were currently using, or had previously used, cannabis products to treat epilepsy. Of those with a history of cannabis product use, 90% of adults and 71% of parents reported success in reducing seizure frequency after commencing cannabis products. The main reasons for medicinal cannabis use were to manage treatment-resistant epilepsy and to obtain a more favorable side-effect profile compared to standard antiepileptic drugs. The number of past antiepileptic drugs tried was a significant predictor of medicinal cannabis use in both adults and children with epilepsy. Fifty-six percent of adults with epilepsy and 62% of parents/guardians of children with epilepsy expressed willingness to participate in clinical trials of cannabinoids. This survey provides insight into the use of cannabis products for epilepsy, in particular some of the likely factors influencing use, as well as novel insights into the experiences of and attitudes towards medicinal cannabis in people with epilepsy in the Australian community. This article is part of a Special Issue entitled "Cannabinoids and Epilepsy". Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Accurate Calculation of Electric Fields Inside Enzymes.

    Science.gov (United States)

    Wang, X; He, X; Zhang, J Z H

    2016-01-01

    The specific electric field generated by a protease at its active site is considered as an important source of the catalytic power. Accurate calculation of electric field at the active site of an enzyme has both fundamental and practical importance. Measuring site-specific changes of electric field at internal sites of proteins due to, eg, mutation, has been realized by using molecular probes with CO or CN groups in the context of vibrational Stark effect. However, theoretical prediction of change in electric field inside a protein based on a conventional force field, such as AMBER or OPLS, is often inadequate. For such calculation, quantum chemical approach or quantum-based polarizable or polarized force field is highly preferable. Compared with the result from conventional force field, significant improvement is found in predicting experimentally measured mutation-induced electric field change using quantum-based methods, indicating that quantum effect such as polarization plays an important role in accurate description of electric field inside proteins. In comparison, the best theoretical prediction comes from fully quantum mechanical calculation in which both polarization and inter-residue charge transfer effects are included for accurate prediction of electrostatics in proteins. © 2016 Elsevier Inc. All rights reserved.

  14. Family history and body mass index predict perceived risks of diabetes and heart attack among community-dwelling Caucasian, Filipino, Korean, and Latino Americans--DiLH Survey.

    Science.gov (United States)

    Fukuoka, Yoshimi; Choi, JiWon; S Bender, Melinda; Gonzalez, Prisila; Arai, Shoshana

    2015-07-01

    The purpose of the study was to explore the perceived risk for diabetes and heart attack and associated health status of Caucasian, Filipino, Korean, and Latino Americans without diabetes. A cross-sectional survey was conducted with 904 urban adults (mean age 44.3±16.1 years; 64.3% female) in English, Spanish or Korean between August and December 2013. Perceived risk for developing diabetes was indicated by 46.5% (n=421), and 14.3% (n=129) perceived themselves to be at risk for having a heart attack in their lifetime. Significant predictors of pessimistic diabetes risk perceptions: Filipino (adjusted odds ratio [AOR]=1.7; 95% CI: 1.04-2.86) and Korean (AOR=2.4; 1.33-4.48) ethnicity, family history of diabetes (AOR=1.4; 1.00-1.84), female gender (AOR=1.4; 1.04-1.96), high cholesterol (AOR= 1.6; 1.09-2.37) and higher body mass index (BMI) (AOR=1.1; 1.08-1.15). Predictors of pessimistic heart attack risk perceptions were family history of an early heart attack (AOR=2.9; 1.69-5.02), high blood pressure (AOR=2.4; 1.45-3.84), and higher BMI (AOR=1.1; 1.04-1.12) after controlling for socio-demographic factors. Older age, physical inactivity, smoking, and low HDL levels were not associated with risk perceptions. Multiple risk factors were predictive of greater perceived diabetes risk, whereas, only family history of heart attack, high blood pressure and increases in BMI significantly contributed to perceived risk of heart attack among ethnically diverse at risk middle-aged adults. It is important that healthcare providers address the discordance between an individual's risk perceptions and the presence of actual risk factors. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  16. Latino Immigrants' Biological Parents' Histories of Substance Use Problems in Their Country of Origin Predict Their Pre- and Post-Immigration Alcohol Use Problems.

    Science.gov (United States)

    Blackson, Timothy C; De La Rosa, Mario; Sanchez, Mariana; Li, Tan

    2015-01-01

    No studies to date have assessed whether recent young adult (aged 18-34) Latino immigrants' biological parents' histories of substance use problems (BPHSUP) in their country of origin predict their alcohol use problems at pre- and post-immigration to the United States (US). BPHSUP in their country of origin were assessed via interviews conducted by bilingual Latino researchers with recent Latino immigrants primarily from Cuba and Central and South America recruited through respondent-driven sampling at the time of their immigration to southeastern US. Three waves of data were collected to document Latino immigrants' severity of alcohol use problems at pre-immigration and 2 annual post-immigration follow-up assessments. BPHSUP+/- status was used as a predictor of Latinos' (N = 452; 45.8% female, 54.2% male) Alcohol Use Disorders Identification Test (AUDIT) scores at pre- and post-immigration with age, education, and income as covariates as wells as odds ratios for AUDIT classifications of hazardous use, harmful use, and dependence. BPHSUP+ status predicted Latino immigrants' higher AUDIT scores pre- and post-immigration by gender (P immigrants of BPHSUP- status, controlling for age, education, and income. BPHSUP+ status predicted odds ratios of 3.45 and 2.91 for AUDIT alcohol dependence classification for men and women, respectively. This study documents that BPHSUP+/- status in their country of origin predict their young adult Latino offspring's severity of alcohol use problems pre- and post-immigration. These results may inform (1) community-based health care providers to screen recent young adult Latino immigrants for their BPHSUP+/- status and severity of alcohol use problems to redirect trajectories away from alcohol use disorders toward more normative post-immigration outcomes through culturally relevant prevention services and (2) future research advantages of differential susceptibility theory. Implications for future research and the need for replication

  17. The Risk Factors That Predict Chronic Hypertension After Delivery in Women With a History of Hypertensive Disorders of Pregnancy.

    Science.gov (United States)

    Hwang, Ji-Won; Park, Sung-Ji; Oh, Soo-Young; Chang, Sung-A; Lee, Sang-Chol; Park, Seung Woo; Kim, Duk-Kyung

    2015-10-01

    Hypertensive disorders of pregnancy (HDP) is one of the most important lethal complications in pregnant mothers. It is also associated with the subsequent development of chronic hypertension. The objective of this study was to identify the clinical risk factors of postpartum chronic hypertension in women diagnosed with HDP.Six hundred patients as HDP, who diagnosed and followed-up at least 6 month after delivery, were included in the study. We divided the included subjects in 2 groups based on the development of postpartum chronic hypertension: presenting with the chronic hypertension, "case group" (n = 41) and without chronic hypertension, "control group" (n = 559).Clinical and demographic factors were evaluated. By multiple regression analysis, early onset hypertension with end-organ dysfunction, smoking, higher prepregnancy body mass index (BMI), and comorbidities, systemic lupus erythematosus (SLE) or antiphospholipid syndrome (APLS), were associated with progression to chronic hypertension in the postpartum period. The value of area under the curves (AUC) for the 5 models, that generated to combine the significant factors, increased from 0.645 to 0.831, which indicated improved prediction of progression to the chronic hypertension. Additional multivariate analysis revealed significant specific risk factors.This retrospective single hospital-based study demonstrated that the clinical risk factors, that is early onset hypertension with end-organ dysfunction, smoking, and higher prepregnancy BMI, were significant independent predictors of chronic hypertension in women after delivery. Identification of risk factors allowed us to narrow the subject field for monitoring and managing high blood pressure in the postpartum period.

  18. Predicting psychosis across diagnostic boundaries: Behavioral and computational modeling evidence for impaired reinforcement learning in schizophrenia and bipolar disorder with a history of psychosis.

    Science.gov (United States)

    Strauss, Gregory P; Thaler, Nicholas S; Matveeva, Tatyana M; Vogel, Sally J; Sutton, Griffin P; Lee, Bern G; Allen, Daniel N

    2015-08-01

    There is increasing evidence that schizophrenia (SZ) and bipolar disorder (BD) share a number of cognitive, neurobiological, and genetic markers. Shared features may be most prevalent among SZ and BD with a history of psychosis. This study extended this literature by examining reinforcement learning (RL) performance in individuals with SZ (n = 29), BD with a history of psychosis (BD+; n = 24), BD without a history of psychosis (BD-; n = 23), and healthy controls (HC; n = 24). RL was assessed through a probabilistic stimulus selection task with acquisition and test phases. Computational modeling evaluated competing accounts of the data. Each participant's trial-by-trial decision-making behavior was fit to 3 computational models of RL: (a) a standard actor-critic model simulating pure basal ganglia-dependent learning, (b) a pure Q-learning model simulating action selection as a function of learned expected reward value, and (c) a hybrid model where an actor-critic is "augmented" by a Q-learning component, meant to capture the top-down influence of orbitofrontal cortex value representations on the striatum. The SZ group demonstrated greater reinforcement learning impairments at acquisition and test phases than the BD+, BD-, and HC groups. The BD+ and BD- groups displayed comparable performance at acquisition and test phases. Collapsing across diagnostic categories, greater severity of current psychosis was associated with poorer acquisition of the most rewarding stimuli as well as poor go/no-go learning at test. Model fits revealed that reinforcement learning in SZ was best characterized by a pure actor-critic model where learning is driven by prediction error signaling alone. In contrast, BD-, BD+, and HC were best fit by a hybrid model where prediction errors are influenced by top-down expected value representations that guide decision making. These findings suggest that abnormalities in the reward system are more prominent in SZ than BD; however, current psychotic

  19. The Sex, Age, Medical History, Treatment, Tobacco Use, Race Risk (SAMe TT2R2) Score Predicts Warfarin Control in a Singaporean Population.

    Science.gov (United States)

    Bernaitis, Nijole; Ching, Chi Keong; Chen, Liping; Hon, Jin Shing; Teo, Siew Chong; Davey, Andrew K; Anoopkumar-Dukie, Shailendra

    2017-01-01

    Warfarin reduces stroke risk in atrial fibrillation (AF) patients but requires ongoing monitoring. Time in therapeutic range (TTR) is used as a measure of warfarin control, with a TTR less than 60% associated with adverse patient outcomes. The Sex, Age, Medical history, Treatment, Tobacco use, Race (SAMe-TT2R2) score has been identified as a model able to predict warfarin control, but this has been tested in mainly Caucasian populations. Therefore, the aim of this study was to determine the ability of the SAMe-TT2R2 score to predict warfarin control in a Singaporean population consisting of Chinese, Malay, and Indian race. Retrospective data were collected from the National Heart Centre Singapore for AF patients receiving warfarin between January and June 2014. The TTR and the SAMe-TT2R2 score were calculated for each patient. The 1137 non-valvular AF patients had a mean TTR of 58.0 ± 34.3% and a median SAMe-TT2R2 score of 3. The categorized SAMe-TT2R2 scores (2 versus >2) showed a significant reduction in mean TTR for the entire population (63.2% versus 55.8%, P = .0004) and also when categorized according to race for Chinese (62.7% versus 56.9%, P = .0075) and Malay (68.4% versus 50.6%, P = .0131) populations. The SAMe-TT2R2 tool is effective in predicting warfarin control in a Singaporean population as patients with a score greater than 2 had poor control. The minimum score for non-Caucasian patients is 2; thus, in these patients, the presence of any additional risk factors identified in the SAMe-TT2R2 tool categorizes them as unlikely to achieve adequate warfarin control and possible candidates for alternative anticoagulants. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  20. The Role of Metacognitive Reading Strategies, Metacognitive Study and Learning Strategies, and Behavioral Study and Learning Strategies in Predicting Academic Success in Students With and Without a History of Reading Difficulties.

    Science.gov (United States)

    Chevalier, Thérèse M; Parrila, Rauno; Ritchie, Krista C; Deacon, S Hélène

    2017-01-01

    We examined the self-reported use of reading, study, and learning strategies in university students with a history of reading difficulties (HRD; n = 77) and with no history of reading difficulties (NRD; n = 295). We examined both between-groups differences in strategy use and strategy use as a predictive measure of academic success. Participants completed online questionnaires regarding reading history and strategy use. GPA and frequency of use of academic support services were also obtained for all students. University students with HRD reported a different profile of strategy use than their NRD peers, and self-reported strategy use was differentially predictive of GPA for students with HRD and NRD. For students with HRD, the use of metacognitive reading strategies and the use of study aids predicted academic success. Implications for university student services providers are discussed. © Hammill Institute on Disabilities 2015.

  1. Family history and body mass index predict perceived risks of diabetes and heart attack among community-dwelling Caucasian, Filipino, Korean, and Latino Americans—DiLH Survey

    Science.gov (United States)

    Fukuoka, Yoshimi; Choi, JiWon; Bender, Melinda S.; Gonzalez, Prisila; Arai, Shoshana

    2015-01-01

    Aim The purpose of the study was to explore the perceived risk for diabetes and heart attack and associated health status of Caucasian, Filipino, Korean, and Latino Americans without diabetes. Methods A cross-sectional survey was conducted with 904 urban adults (mean age 44.3 ± 16.1 years; 64.3% female) in English, Spanish or Korean between August and December 2013. Results Perceived risk for developing diabetes was indicated by 46.5% (n = 421), and 14.3% (n = 129) perceived themselves to be at risk for having a heart attack in their lifetime. Significant predictors of pessimistic diabetes risk perceptions: Filipino (adjusted odds ratio [AOR] = 1.7; 95% CI: 1.04–2.86) and Korean (AOR = 2.4; 1.33–4.48) ethnicity, family history of diabetes (AOR = 1.4; 1.00–1.84), female gender (AOR = 1.4; 1.04–1.96), high cholesterol (AOR= 1.6; 1.09–2.37) and higher body mass index (BMI) (AOR = 1.1; 1.08–1.15). Predictors of pessimistic heart attack risk perceptions were family history of an early heart attack (AOR = 2.9; 1.69–5.02), high blood pressure (AOR = 2.4; 1.45–3.84), and higher BMI (AOR = 1.1; 1.04–1.12) after controlling for socio-demographic factors. Older age, physical inactivity, smoking, and low HDL levels were not associated with risk perceptions. Conclusion Multiple risk factors were predictive of greater perceived diabetes risk, whereas, only family history of heart attack, high blood pressure and increases in BMI significantly contributed to perceived risk of heart attack among ethnically diverse at risk middle-aged adults. It is important that healthcare providers address the discordance between an individual’s risk perceptions and the presence of actual risk factors. PMID:25931282

  2. Latino Immigrants’ Biological Parents’ Histories Of Substance Use Problems In Their Country Of Origin Predict Their Pre- And Post-Immigration Alcohol Use Problems

    Science.gov (United States)

    Blackson, Timothy C.; De La Rosa, Mario; Sanchez, Mariana; Li, Tan

    2014-01-01

    Background No studies to date have assessed whether recent young adult (ages 18–34) Latino immigrants’ biological parents’ histories of substance use problems (BPHSUP) in their country of origin predict their alcohol use problems at pre- and post-immigration to the United States (U.S.). Methods BPHSUP in their country of origin was assessed via interviews conducted by bilingual Latino researchers with recent Latino immigrants primarily from Cuba, Central and South America recruited through respondent driven sampling at the time of their immigration to southeastern U.S. Three-waves of data were collected to document Latino immigrants’ severity of alcohol use problems at pre-immigration and two annual post-immigration follow-up assessments. BPHSUP +/− status was used as a predictor of Latinos’ (N=452; 45.8% female, 54.2% male) Alcohol Use Disorders Identification Test (AUDIT) scores at pre- and post-immigration with age, education and income as covariates as wells as odds ratios for AUDIT classifications of hazardous use, harmful use and dependence. Results BPHSUP+ status predicted Latino immigrants’ higher AUDIT scores pre- and post-immigration by gender (pLatino immigrants of BPHSUP− status controlling for age, education and income. BPHSUP+ status predicted odds ratios of 3.45 and 2.91 for alcohol dependence AUDIT classification for men and women respectively (T3). Conclusions This study documents that BPHSUP +/− status in their country of origin predict their young adult Latino offspring’s severity of alcohol use problems pre-and post-immigration. These results may inform (1) community-based health care providers to screen recent young adult Latino immigrants for their BPHSUP+/− status and severity of alcohol use problems to redirect trajectories away from alcohol use disorders toward more normative post-immigration outcomes through culturally relevant prevention services and (2) future research advantages of differential susceptibility

  3. NNLOPS accurate associated HW production

    CERN Document Server

    Astill, William; Re, Emanuele; Zanderighi, Giulia

    2016-01-01

    We present a next-to-next-to-leading order accurate description of associated HW production consistently matched to a parton shower. The method is based on reweighting events obtained with the HW plus one jet NLO accurate calculation implemented in POWHEG, extended with the MiNLO procedure, to reproduce NNLO accurate Born distributions. Since the Born kinematics is more complex than the cases treated before, we use a parametrization of the Collins-Soper angles to reduce the number of variables required for the reweighting. We present phenomenological results at 13 TeV, with cuts suggested by the Higgs Cross Section Working Group.

  4. Can risk factors, clinical history and symptoms be used to predict risk of ectopic pregnancy in women attending an early pregnancy assessment unit?

    Science.gov (United States)

    Ayim, F; Tapp, S; Guha, S; Ameye, L; Al-Memar, M; Sayasneh, A; Bottomley, C; Gould, D; Stalder, C; Timmerman, D; Bourne, T

    2016-11-01

    To examine whether risk factors and symptoms may be used to predict the likelihood of ectopic pregnancy (EP) in women attending early pregnancy assessment units in the UK. This was an observational cohort study of pregnant women under 12 weeks' gestation who were recruited from three London university hospitals between August 2012 and April 2013. One hospital continued recruitment between January and June 2015. A standardized information sheet incorporating patient demographics, medical history and symptoms was completed by patients and confirmed by examining clinicians. The outcome measure was final pregnancy location. There were 1320 eligible patients included in the analysis, with a total of 72 EPs (rate of 6%). Pelvic pain and diarrhea > three times in the previous 24 h were independent symptoms that increased the risk of EP, with relative risks of 2.4 (95% CI, 1.4-4.0; P = 0.002) and 2.2 (95% CI, 1.08-4.5; P = 0.03), respectively. The only other independent marker of risk of EP was duration of vaginal bleeding; the risk of EP increased by 20% (95% CI, 14%-27%) for every 1-day increment in duration (P three times in the previous 24 h was reported and 9% (9/103) when there was only vaginal bleeding with a duration > 3 days. Women with pelvic pain and vaginal bleeding of any severity for > 3 days had a high EP rate of 16% (23/146). In the nine women who also reported diarrhea > three times in the previous 24 h, two had EP. Only the presence of pelvic pain, diarrhea > three times in the previous 24 h and duration of bleeding were symptoms that significantly increased the risk for EP in women attending early pregnancy assessment units. Risk factors and symptoms alone could not be used to predict reliably an EP. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

  5. Transient, three-dimensional heat transfer model for the laser assisted machining of silicon nitride: 1. Comparison of predictions with measured surface temperature histories

    Energy Technology Data Exchange (ETDEWEB)

    Rozzi, J.C.; Pfefferkorn, F.E.; Shin, Y.C. [Purdue University, (United States). Laser Assisted Materials Processing Laboratory, School of Mechanical Engineering; Incropera, F.P. [University of Notre Dame, (United States). Aerospace and Mechanical Engineering Department

    2000-04-01

    Laser assisted machining (LAM), in which the material is locally heated by an intense laser source prior to material removal, provides an alternative machining process with the potential to yield higher material removal rates, as well as improved control of workpiece properties and geometry, for difficult-to-machine materials such as structural ceramics. To assess the feasibility of the LAM process and to obtain an improved understanding of governing physical phenomena, experiments have been performed to determine the thermal response of a rotating silicon nitride workpiece undergoing heating by a translating CO{sub 2} laser and material removal by a cutting tool. Using a focused laser pyrometer, surface temperature histories were measured to determine the effect of the rotational and translational speeds, the depth of cut, the laser-tool lead distance, and the laser beam diameter and power on thermal conditions. The measurements are in excellent agreement with predictions based on a transient, three-dimensional numerical solution of the heating and material removal processes. The temperature distribution within the unmachined workpiece is most strongly influenced by the laser power and laser-tool lead distance, as well as by the laser/tool translational velocity. A minimum allowable operating temperature in the material removal region corresponds to the YSiAlON glass transition temperature, below which tool fracture may occur. In a companion paper, the numerical model is used to further elucidate thermal conditions associated with laser assisted machining. (author)

  6. Accurate measurements in volume data

    NARCIS (Netherlands)

    Oliván Bescós, J.; Bosma, Marco; Smit, Jaap; Mun, S.K.

    2001-01-01

    An algorithm for very accurate visualization of an iso- surface in a 3D medical dataset has been developed in the past few years. This technique is extended in this paper to several kinds of measurements in which exact geometric information of a selected iso-surface is used to derive volume, length,

  7. Nonsurgical giant cell tumour of the tendon sheath or of the diffuse type: Are MRI or {sup 18}F-FDG PET/CT able to provide an accurate prediction of long-term outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Dercle, Laurent [IUCT-Oncopole/Institut Claudius Regaud, Department of Nuclear Medicine, Toulouse (France); Institut Gustave Roussy, Department of Radiology, Villejuif (France); Institut Gustave Roussy, Department of Nuclear Medicine, Villejuif (France); Chisin, Roland [Hebrew University Hadassah Medical Center, Department of Medical Biophysics and Nuclear Medicine, Jerusalem (Israel); Ammari, Samy [Institut Gustave Roussy, Department of Radiology, Villejuif (France); Gillebert, Quentin [Hopital tenon, Hopitaux Universitaires Est Parisien, Department of Nuclear Medicine, Paris (France); Ouali, Monia [Institut Claudius Regaud, Department of Biostatistics, Toulouse (France); Jaudet, Cyril; Dierickx, Lawrence; Zerdoud, Slimane; Courbon, Frederic [IUCT-Oncopole/Institut Claudius Regaud, Department of Nuclear Medicine, Toulouse (France); Delord, Jean-Pierre [Institut Claudius Regaud, Department of Clinical Research, Toulouse (France); Schlumberger, Martin [Institut Gustave Roussy, Department of Nuclear Medicine, Villejuif (France)

    2014-11-01

    To investigate whether MRI (RECIST 1.1, WHO criteria and the volumetric approach) or {sup 18}F-FDG PET/CT (PERCIST 1.0) are able to predict long-term outcome in nonsurgical patients with giant cell tumour of the tendon sheath or of the diffuse type (GCT-TS/DT). Fifteen ''nonsurgical'' patients with a histological diagnosis of GCT-TS/DT were divided into two groups: symptomatic patients receiving targeted therapy and asymptomatic untreated patients. All 15 patients were evaluated by MRI of whom 10 were treated, and a subgroup of 7 patients were evaluated by PET/CT of whom 4 were treated. Early evolution was assessed according to MRI and PET/CT scans at baseline and during follow-up. Cohen's kappa coefficient was used to evaluate the degree of agreement between PERCIST 1.0, RECIST 1.1, WHO criteria, volumetric approaches and the reference standard (long-term outcome, delay 505 ± 457 days). The response rate in symptomatic patients with GCT-TS/DT receiving targeted therapy was also assessed in a larger population that included additional patients obtained from a review of the literature. The kappa coefficients for agreement between RECIST/WHO/volumetric criteria and outcome (15 patients) were respectively: 0.35 (p = 0.06), 0.26 (p = 0.17) and 0.26 (p = 0.17). In the PET/CT subgroup (7 patients), PERCIST was in perfect agreement with the late symptomatic evolution (kappa = 1, p < 0.05). In the treated symptomatic group including the additional patients from the literature the response rates to targeted therapies according to late symptomatic assessment, and PERCIST and RECIST criteria were: 65 % (22/34), 77 % (10/13) and 26 % (10/39). {sup 18}F-FDG PET/CT with PERCIST is a promising approach to the prediction of the long-term outcome in GCT-TS/DT and may avoid unnecessary treatments, toxicity and costs. On MRI, WHO and volumetric approaches are not more effective than RECIST using the current thresholds. (orig.)

  8. When Is Network Lasso Accurate?

    Directory of Open Access Journals (Sweden)

    Alexander Jung

    2018-01-01

    Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.

  9. Accurate Accident Reconstruction in VANET

    OpenAIRE

    Kopylova, Yuliya; Farkas, Csilla; Xu, Wenyuan

    2011-01-01

    Part 9: Short Papers; International audience; We propose a forensic VANET application to aid an accurate accident reconstruction. Our application provides a new source of objective real-time data impossible to collect using existing methods. By leveraging inter-vehicle communications, we compile digital evidence describing events before, during, and after an accident in its entirety. In addition to sensors data and major components’ status, we provide relative positions of all vehicles involv...

  10. Accurate determination of antenna directivity

    DEFF Research Database (Denmark)

    Dich, Mikael

    1997-01-01

    The derivation of a formula for accurate estimation of the total radiated power from a transmitting antenna for which the radiated power density is known in a finite number of points on the far-field sphere is presented. The main application of the formula is determination of directivity from power......-pattern measurements. The derivation is based on the theory of spherical wave expansion of electromagnetic fields, which also establishes a simple criterion for the required number of samples of the power density. An array antenna consisting of Hertzian dipoles is used to test the accuracy and rate of convergence...

  11. Copeptin does not accurately predict disease severity in imported malaria

    NARCIS (Netherlands)

    M.E. van Wolfswinkel (Marlies); D.A. Hesselink (Dennis); E.J. Hoorn (Ewout); Y.B. de Rijke (Yolanda); R. Koelewijn (Rob); J.J. van Hellemond (Jaap); P.J.J. van Genderen (Perry)

    2012-01-01

    textabstractBackground: Copeptin has recently been identified to be a stable surrogate marker for the unstable hormone arginine vasopressin (AVP). Copeptin has been shown to correlate with disease severity in leptospirosis and bacterial sepsis. Hyponatraemia is common in severe imported malaria and

  12. WGS accurately predicts antimicrobial resistance in Escherichia coli

    National Research Council Canada - National Science Library

    Tyson, Gregory H; McDermott, Patrick F; Li, Cong; Chen, Yuansha; Tadesse, Daniel A; Mukherjee, Sampa; Bodeis-Jones, Sonya; Kabera, Claudine; Gaines, Stuart A; Loneragan, Guy H; Edrington, Tom S; Torrence, Mary; Harhay, Dayna M; Zhao, Shaohua

    2015-01-01

    The objective of this study was to determine the effectiveness of WGS in identifying resistance genotypes of MDR Escherichia coli and whether these correlate with observed phenotypes. Seventy-six E...

  13. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    NARCIS (Netherlands)

    Westhall, Erik; Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias; Saxena, Manoj; Miller, Jennene; Inskip, Deborah; Macken, Lewis; Finfer, Simon; Eatough, Noel; Hammond, Naomi; Bass, Frances; Yarad, Elizabeth; O'Connor, Anne; Bird, Simon; Jewell, Timothy; Davies, Gareth; Ng, Karl; Coward, Sharon; Stewart, Antony; Micallef, Sharon; Parker, Sharyn; Cortado, Dennis; Gould, Ann; Harward, Meg; Thompson, Kelly; Glass, Parisa; Myburgh, John; Smid, Ondrej; Belholavek, Jan; Kreckova, Marketa; Kral, Ales; Horak, Jan; Otahal, Michal; Rulisek, Jan; Malik, Jan; Prettl, Martin; Wascher, Michael; Boesgaard, Soeren; Moller, Jacob E.; Bro-Jeppesen, John; Johansen, Ane Loof; Campanile, Vincenzo; Peratoner, Alberto; Verginella, Francesca; Leone, Daniele; Pellis, Thomas; Roncarati, Andrea; Franceschino, Eliana; Sanzani, Anna; Martini, Alice; Perlin, Micol; Pelosi, Paolo; Brunetti, Iole; Insorsi, Angelo; Pezzato, Stefano; de Luca, Giorgio; Gazzano, Emanuela; Ottonello, Gian Andrea; Furgani, Andrea; Telani, Rosanna; Maiani, Simona; Werer, Christophe; Kieffer, Jaqueline; van der Veen, Annelou L.; Winters, Tineke; Juffermans, Nicole P.; Egbers, Ph; Boerma, EC; Gerritsen, R. T.; Buter, H.; de Jager, C.; de Lange, F.; Loos, M.; Koetsier, P. M.; Kingma, W. P.; Bruins, N.; de Kock, L.; Koopmans, M.; Bosch, Frank; Raaijmakers, Monique A. M.; Metz-Hermans, S. W. L.; Endeman, Henrik; Rijkenberg, Saskia; Bianchi, Addy; Bugge, Jan Frederik; Norum, Hilde; Espinoza, Andreas; Kerans, Viesturs; Brevik, Helene; Svalebjørg, Morten; Grindheim, Guro; Petersen, Arne Jan; Baratt-Due, Andreas; Laake, Jon Henrik; Spreng, Ulrik; Wallander Karlsen, Marte Marie; Langøren, Jørund; Fanebust, Rune; Holm, Marianne Sætrang; Flinterud, Stine Iren; Wickman, Carsten; Johnsson, Jesper; Ebner, Florian; Gustavsson, Nerida; Petersson, Heléne; Petersson, Jörgen; Nasiri, Faezheh; Stafilidou, Frida; Edqvist, Kristine; Uhlig, Sven; Sköld, Gunilla; Sanner, Johan; Wallskog, Jesper; Wyon, Nicholas; Golster, Martin; Samuelsson, Anders; Hildebrand, Carl; Kadowaki, Taichi; Larsson-Viksten, Jessica; de Geer, Lina; Hansson, Patrik; Appelberg, Henrik; Hellsten, Anders; Lind, Susanne; Rundgren, Malin; Kander, Thomas; Persson, Johan; Annborn, Martin; Adolfsson, Anne; Corrigan, Ingrid; Dragancea, Irina; Undén, Johan; Larsson, Marina; Chew, Michelle; Unnerbäck, Mårten; Petersen, Per; Svedung-Rudebou, Anna; Svensson, Robert; Elvenes, Hilde; Bäckman, Carl; Rylander, Christian; Martner, Patrik; Martinell, Louise; Biber, Björn; Ahlqvist, Marita; Jacobson, Caisa; Forsberg, Marie-Louise; Lindgren, Roman Desta; Bergquist, Fatma; Thorén, Anders; Fredholm, Martin; Sellgren, Johan; Hård Af Segerstad, Lisa; Löfgren, Mikael; Gustavsson, Ingvor; Henström, Christina; Andersson, Bertil; Thiringer, Karin; Rydholm, Nadja; Persson, Stefan; Jawad, Jawad; Östman, Ingela; Berglind, Ida; Bergström, Eric; Andersson, Annika; Törnqvist, Cathrine; Marques de Mello, Nubia Lafayete; Gardaz, Valérie; Kleger, Gian-Reto; Schrag, Claudia; Fässler, Edith; Zender, Hervé; Wise, Matthew; Palmer, Nicki; Fouweather, Jen; Cole, Jade M.; Cocks, Eve; Frost, Paul J.; Saayman, Anton G.; Holmes, Tom; Hingston, Christopher D.; Scholey, Gareth M.; Watkins, Helen; Fernandez, Stephen; Walden, Andrew; Atkinson, Jane; Jacques, Nicola; Brown, Abby; Cranshaw, Julius; Berridge, Peter; McCormick, Robert; Schuster-Bruce, Martin; Scott, Michelle; White, Nigel; Vickers, Emma; Glover, Guy; Ostermann, Marlies; Holmes, Paul; Koutroumanidis, Michael; Lei, Katie; Sanderson, Barnaby; Smith, John; al-Subaie, Nawaf; Moore, Matthew; Randall, Paul; Mellinghoff, Johannes; Buratti, Azul Forti; Ryan, Chris; Ball, Jonathan; Francis, Gaynor

    2016-01-01

    To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. In this cohort study, 4 EEG specialists, blinded to outcome,

  14. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    DEFF Research Database (Denmark)

    Westhall, Erik; Rossetti, Andrea O; van Rootselaar, Anne-Fleur

    2016-01-01

    with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3-5 until 180 days. RESULTS: Eight TTM sites randomized 202...

  15. Toward Accurate and Quantitative Comparative Metagenomics.

    Science.gov (United States)

    Nayfach, Stephen; Pollard, Katherine S

    2016-08-25

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Accurate renormalization group analyses in neutrino sector

    Energy Technology Data Exchange (ETDEWEB)

    Haba, Naoyuki [Graduate School of Science and Engineering, Shimane University, Matsue 690-8504 (Japan); Kaneta, Kunio [Kavli IPMU (WPI), The University of Tokyo, Kashiwa, Chiba 277-8568 (Japan); Takahashi, Ryo [Graduate School of Science and Engineering, Shimane University, Matsue 690-8504 (Japan); Yamaguchi, Yuya [Department of Physics, Faculty of Science, Hokkaido University, Sapporo 060-0810 (Japan)

    2014-08-15

    We investigate accurate renormalization group analyses in neutrino sector between ν-oscillation and seesaw energy scales. We consider decoupling effects of top quark and Higgs boson on the renormalization group equations of light neutrino mass matrix. Since the decoupling effects are given in the standard model scale and independent of high energy physics, our method can basically apply to any models beyond the standard model. We find that the decoupling effects of Higgs boson are negligible, while those of top quark are not. Particularly, the decoupling effects of top quark affect neutrino mass eigenvalues, which are important for analyzing predictions such as mass squared differences and neutrinoless double beta decay in an underlying theory existing at high energy scale.

  17. Accelerated training for accurate neural net based load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Borsje, H.J.; Ling, B. [Stone and Webster Advanced Systems Development Services, Inc., Boston, MA (United States)

    1995-10-01

    A fast, accurate, robust and reliable load forecast method was developed, tested and demonstrated. The achieved prediction accuracy, based on a practical input parameters, matches or exceeds that of currently used methods. The time required to train the system is orders of magnitude shorter than other methods. This gives utility personnel the tools to refine local forecasts by quickly evaluating the effect of user selectable parameters. The conventional back propagation method can accurately predict the adaptive one-hour ahead forecast with reasonable learning requirements.

  18. Accurate Modeling of Advanced Reflectarrays

    DEFF Research Database (Denmark)

    Zhou, Min

    of the incident field, the choice of basis functions, and the technique to calculate the far-field. Based on accurate reference measurements of two offset reflectarrays carried out at the DTU-ESA Spherical NearField Antenna Test Facility, it was concluded that the three latter factors are particularly important...... to the conventional phase-only optimization technique (POT), the geometrical parameters of the array elements are directly optimized to fulfill the far-field requirements, thus maintaining a direct relation between optimization goals and optimization variables. As a result, better designs can be obtained compared...... using the GDOT to demonstrate its capabilities. To verify the accuracy of the GDOT, two offset contoured beam reflectarrays that radiate a high-gain beam on a European coverage have been designed and manufactured, and subsequently measured at the DTU-ESA Spherical Near-Field Antenna Test Facility...

  19. The Accurate Particle Tracer Code

    CERN Document Server

    Wang, Yulei; Qin, Hong; Yu, Zhi

    2016-01-01

    The Accurate Particle Tracer (APT) code is designed for large-scale particle simulations on dynamical systems. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and non-linear problems. Under the well-designed integrated and modularized framework, APT serves as a universal platform for researchers from different fields, such as plasma physics, accelerator physics, space science, fusion energy research, computational mathematics, software engineering, and high-performance computation. The APT code consists of seven main modules, including the I/O module, the initialization module, the particle pusher module, the parallelization module, the field configuration module, the external force-field module, and the extendible module. The I/O module, supported by Lua and Hdf5 projects, provides a user-friendly interface for both numerical simulation and data analysis. A series of new geometric numerical methods...

  20. The accurate particle tracer code

    Science.gov (United States)

    Wang, Yulei; Liu, Jian; Qin, Hong; Yu, Zhi; Yao, Yicun

    2017-11-01

    The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runaway electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world's fastest computer, the Sunway TaihuLight supercomputer, by supporting master-slave architecture of Sunway many-core processors. Based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.

  1. The coronary calcium score is a more accurate predictor of significant coronary stenosis than conventional risk factors in symptomatic patients

    DEFF Research Database (Denmark)

    Nicoll, R; Wiklund, U; Zhao, Y

    2016-01-01

    AIMS: In this retrospective study we assessed the predictive value of the coronary calcium score for significant (>50%) stenosis relative to conventional risk factors. METHODS AND RESULTS: We investigated 5515 symptomatic patients from Denmark, France, Germany, Italy, Spain and the USA. All had...... predictor of significant stenosis to be male gender (B=1.07) followed by diabetes mellitus (B=0.70) smoking, hypercholesterolaemia, hypertension, family history of CAD and age but not obesity. When the log transformed CAC score was included, it became the most powerful predictor (B=1.25), followed by male...... gender (B=0.48), diabetes, smoking, family history and age but hypercholesterolaemia and hypertension lost significance. The CAC score is a more accurate predictor of >50% stenosis than risk factors regardless of the means of assessment of stenosis. The sensitivity of risk factors, CAC score...

  2. Understanding History

    OpenAIRE

    Gorman, Jonathan

    2017-01-01

    Has any question about the historical past ever been finally answered? Of course there is much disagreement among professional historians about what happened in the past and how to explain it. But this incisive study goes one step further and brings into question the very ability of historians to gather and communicate genuine knowledge about the past. Understanding History applies this general question from the philosophy of history to economic history of American slaveholders. Do we unders...

  3. Financial History

    OpenAIRE

    Cassis, Y.; Cottrell, P. L

    2017-01-01

    The considerable renewal of interest in all aspects of financial history over recent years provided one motivation for this new venture. Yet, the foundations for our specialism, which draws from both History and the Social Sciences, especially economics, have been laid by many. Some would point to continuity in our interest from the publication in the 1930s of jubilee banking history volumes, such as those written for British institutions by Gregory, and by Crick and Wadsworth. Further schola...

  4. Fast reconstruction and prediction of frozen flow turbulence based on structured Kalman filtering

    NARCIS (Netherlands)

    Fraanje, P.R.; Rice, J.; Verhaegen, M.; Doelman, N.J.

    2010-01-01

    Efficient and optimal prediction of frozen flow turbulence using the complete observation history of the wavefront sensor is an important issue in adaptive optics for large ground-based telescopes. At least for the sake of error budgeting and algorithm performance, the evaluation of an accurate

  5. Percutaneous epididymal sperm aspiration: a diagnostic tool for the prediction of complete spermatogenesis.

    NARCIS (Netherlands)

    Ramos, L.; Wetzels, A.M.M.; Hendriks, J.C.M.; Hulsbergen- van de Kaa, C.A.; Sweep, C.G.J.; Kremer, J.A.M.; Braat, D.D.M.; Meuleman, E.J.H.

    2004-01-01

    The classification of azoospermia into obstructive or non-obstructive is largely based on medical history, physical examination and biochemical markers in serum and semen. However, the most accurate parameter for diagnosis is the testicular histology. The predictive value of the percutaneous

  6. Effective and Accurate Colormap Selection

    Science.gov (United States)

    Thyng, K. M.; Greene, C. A.; Hetland, R. D.; Zimmerle, H.; DiMarco, S. F.

    2016-12-01

    Science is often communicated through plots, and design choices can elucidate or obscure the presented data. The colormap used can honestly and clearly display data in a visually-appealing way, or can falsely exaggerate data gradients and confuse viewers. Fortunately, there is a large resource of literature in color science on how color is perceived which we can use to inform our own choices. Following this literature, colormaps can be designed to be perceptually uniform; that is, so an equally-sized jump in the colormap at any location is perceived by the viewer as the same size. This ensures that gradients in the data are accurately percieved. The same colormap is often used to represent many different fields in the same paper or presentation. However, this can cause difficulty in quick interpretation of multiple plots. For example, in one plot the viewer may have trained their eye to recognize that red represents high salinity, and therefore higher density, while in the subsequent temperature plot they need to adjust their interpretation so that red represents high temperature and therefore lower density. In the same way that a single Greek letter is typically chosen to represent a field for a paper, we propose to choose a single colormap to represent a field in a paper, and use multiple colormaps for multiple fields. We have created a set of colormaps that are perceptually uniform, and follow several other design guidelines. There are 18 colormaps to give options to choose from for intuitive representation. For example, a colormap of greens may be used to represent chlorophyll concentration, or browns for turbidity. With careful consideration of human perception and design principles, colormaps may be chosen which faithfully represent the data while also engaging viewers.

  7. Conceptual History, Cultural History, Social History

    Directory of Open Access Journals (Sweden)

    Viktor Zhivov (†

    2014-10-01

    Full Text Available V. M. Zhivov’s introduction to Studies in Historical Semantics of the Russian Language in the Early Modern Period (2009, translated here for the first time, offers a critical survey of the historiography on Begriffsgeschichte, the German school of conceptual history associated with the work of Reinhart Koselleck, as well as of its application to the study of Russian culture.  By situating Begriffsgeschichte in the context of late-nineteenth and early twentieth-century European philosophy, particularly hermeneutics and phenomenology, the author points out the important, and as yet unacknowledged, role that Russian linguists have played in the development of a native school of conceptual history.  In the process of outlining this alternative history of the discipline, Zhivov provides some specific examples of the way in which the study of “historical semantics” can be used to analyze the development of Russian modernity.

  8. Intellectual History

    DEFF Research Database (Denmark)

    In the 5 Questions book series, this volume presents a range of leading scholars in Intellectual History and the History of Ideas through their answers to a brief questionnaire. Respondents include Michael Friedman, Jacques le Goff, Hans Ulrich Gumbrecht, Jonathan Israel, Phiip Pettit, John Pocock...

  9. Romerrigets historie

    DEFF Research Database (Denmark)

    Christiansen, Erik

    Romerrigets historie fra Roms legendariske grundlæggelse i 753 f.v.t. til Heraklios' tronbestigelse i 610 e.v.t.......Romerrigets historie fra Roms legendariske grundlæggelse i 753 f.v.t. til Heraklios' tronbestigelse i 610 e.v.t....

  10. The accurate definition of metabolic volumes on {sup 18}F-FDG-PET before treatment allows the response to chemoradiotherapy to be predicted in the case of oesophagus cancers; La definition precise des volumes metaboliques sur TEP au 18F-FDG avant traitement permet la prediction de la reponse a la chimioradiotherapie dans les cancers de l'oesophage

    Energy Technology Data Exchange (ETDEWEB)

    Hatt, M.; Cheze-Le Rest, C.; Visvikis, D. [Inserm U650, Brest (France); Pradier, O. [Radiotherapie, CHRU Morvan, Brest (France)

    2011-10-15

    This study aims at assessing the possibility of prediction of the response of locally advanced oesophagus cancers, even before the beginning of treatment, by using metabolic volume measurements performed on {sup 18}F-FDG PET images made before the treatment. Medical files of 50 patients have been analyzed. According to the observed responses, and to metabolic volume and Total Lesion Glycosis (TLG) values, it appears that the images allow the extraction of parameters, such as the TLG, which are criteria for the prediction of the therapeutic response. Short communication

  11. Medical History: Compiling Your Medical Family Tree

    Science.gov (United States)

    ... conditions on to your children A family medical history can't predict your future health. It only provides information ... result in a poor interpretation of your medical history. Don't worry if some details are missing. If you' ...

  12. Metabolomics and partial least square discriminant analysis to predict history of myocardial infarction of self-claimed healthy subjects: validity and feasibility for clinical practice.

    Science.gov (United States)

    Mohamad, Nornazliya; Ismet, Rose Iszati; Rofiee, MohdSalleh; Bannur, Zakaria; Hennessy, Thomas; Selvaraj, Manikandan; Ahmad, Aminuddin; Nor, FadzilahMohd; Abdul Rahman, ThuhairahHasrah; Md Isa, Kamarudzaman; Ismail, AdzroolIdzwan; Teh, Lay Kek; Salleh, Mohd Zaki

    2015-01-01

    The dynamics of metabolomics in establishing a prediction model using partial least square discriminant analysis have enabled better disease diagnosis; with emphasis on early detection of diseases. We attempted to translate the metabolomics model to predict the health status of the Orang Asli community whom we have little information. The metabolite expressions of the healthy vs. diseased patients (cardiovascular) were compared. A metabotype model was developed and validated using partial least square discriminant analysis (PLSDA). Cardiovascular risks of the Orang Asli were predicted and confirmed by biochemistry profiles conducted concurrently. Fourteen (14) metabolites were determined as potential biomarkers for cardiovascular risks with receiver operating characteristic of more than 0.7. They include 15S-HETE (AUC = 0.997) and phosphorylcholine (AUC = 0.995). Seven Orang Asli were clustered with the patients' group and may have ongoing cardiovascular risks and problems. This is supported by biochemistry tests results that showed abnormalities in cholesterol, triglyceride, HDL and LDL levels. The disease prediction model based on metabolites is a useful diagnostic alternative as compared to the current single biomarker assays. The former is believed to be more cost effective since a single sample run is able to provide a more comprehensive disease profile, whilst the latter require different types of sampling tubes and blood volumes.

  13. 38 CFR 4.46 - Accurate measurement.

    Science.gov (United States)

    2010-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect to...

  14. Approaches for the accurate definition of geological time boundaries

    Science.gov (United States)

    Schaltegger, Urs; Baresel, Björn; Ovtcharova, Maria; Goudemand, Nicolas; Bucher, Hugo

    2015-04-01

    Which strategies lead to the most precise and accurate date of a given geological boundary? Geological units are usually defined by the occurrence of characteristic taxa and hence boundaries between these geological units correspond to dramatic faunal and/or floral turnovers and they are primarily defined using first or last occurrences of index species, or ideally by the separation interval between two consecutive, characteristic associations of fossil taxa. These boundaries need to be defined in a way that enables their worldwide recognition and correlation across different stratigraphic successions, using tools as different as bio-, magneto-, and chemo-stratigraphy, and astrochronology. Sedimentary sequences can be dated in numerical terms by applying high-precision chemical-abrasion, isotope-dilution, thermal-ionization mass spectrometry (CA-ID-TIMS) U-Pb age determination to zircon (ZrSiO4) in intercalated volcanic ashes. But, though volcanic activity is common in geological history, ashes are not necessarily close to the boundary we would like to date precisely and accurately. In addition, U-Pb zircon data sets may be very complex and difficult to interpret in terms of the age of ash deposition. To overcome these difficulties we use a multi-proxy approach we applied to the precise and accurate dating of the Permo-Triassic and Early-Middle Triassic boundaries in South China. a) Dense sampling of ashes across the critical time interval and a sufficiently large number of analysed zircons per ash sample can guarantee the recognition of all system complexities. Geochronological datasets from U-Pb dating of volcanic zircon may indeed combine effects of i) post-crystallization Pb loss from percolation of hydrothermal fluids (even using chemical abrasion), with ii) age dispersion from prolonged residence of earlier crystallized zircon in the magmatic system. As a result, U-Pb dates of individual zircons are both apparently younger and older than the depositional age

  15. Range-Space Predictive Control for Optimal Robot Motion

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef

    2008-01-01

    Roč. 1, č. 1 (2008), s. 1-7 ISSN 1998-0140 R&D Projects: GA ČR GP102/06/P275 Institutional research plan: CEZ:AV0Z10750506 Keywords : Accurate manipulation * Industrial robot ics * Predictive control * Range-space control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0305644.pdf

  16. REDUCING UNCERTAINTIES IN MODEL PREDICTIONS VIA HISTORY MATCHING OF CO2 MIGRATION AND REACTIVE TRANSPORT MODELING OF CO2 FATE AT THE SLEIPNER PROJECT

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Chen

    2015-03-31

    An important question for the Carbon Capture, Storage, and Utility program is “can we adequately predict the CO2 plume migration?” For tracking CO2 plume development, the Sleipner project in the Norwegian North Sea provides more time-lapse seismic monitoring data than any other sites, but significant uncertainties still exist for some of the reservoir parameters. In Part I, we assessed model uncertainties by applying two multi-phase compositional simulators to the Sleipner Benchmark model for the uppermost layer (Layer 9) of the Utsira Sand and calibrated our model against the time-lapsed seismic monitoring data for the site from 1999 to 2010. Approximate match with the observed plume was achieved by introducing lateral permeability anisotropy, adding CH4 into the CO2 stream, and adjusting the reservoir temperatures. Model-predicted gas saturation, CO2 accumulation thickness, and CO2 solubility in brine—none were used as calibration metrics—were all comparable with the interpretations of the seismic data in the literature. In Part II & III, we evaluated the uncertainties of predicted long-term CO2 fate up to 10,000 years, due to uncertain reaction kinetics. Under four scenarios of the kinetic rate laws, the temporal and spatial evolution of CO2 partitioning into the four trapping mechanisms (hydrodynamic/structural, solubility, residual/capillary, and mineral) was simulated with ToughReact, taking into account the CO2-brine-rock reactions and the multi-phase reactive flow and mass transport. Modeling results show that different rate laws for mineral dissolution and precipitation reactions resulted in different predicted amounts of trapped CO2 by carbonate minerals, with scenarios of the conventional linear rate law for feldspar dissolution having twice as much mineral trapping (21% of the injected CO2) as scenarios with a Burch-type or Alekseyev et al.–type rate law for feldspar dissolution (11%). So far, most reactive transport modeling (RTM) studies for

  17. Atmospheric refraction: a history

    Science.gov (United States)

    Lehn, Waldemar H.; van der Werf, Siebren

    2005-09-01

    We trace the history of atmospheric refraction from the ancient Greeks up to the time of Kepler. The concept that the atmosphere could refract light entered Western science in the second century B.C. Ptolemy, 300 years later, produced the first clearly defined atmospheric model, containing air of uniform density up to a sharp upper transition to the ether, at which the refraction occurred. Alhazen and Witelo transmitted his knowledge to medieval Europe. The first accurate measurements were made by Tycho Brahe in the 16th century. Finally, Kepler, who was aware of unusually strong refractions, used the Ptolemaic model to explain the first documented and recognized mirage (the Novaya Zemlya effect).

  18. Matematikkens historie

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    2009-01-01

    Matematikkens historie i syv kapitler: 1. Matematik i støbeskeen; 2. Matematikkens græske arv; 3. Den gyldne tidsalder for hinduer og arabere; 4. Matematik i Kina; 5. Renæssancens matematik; 6. Regning med infinitesimaler ser dagens lys; 7. Matematik i det tyvende århundrede.......Matematikkens historie i syv kapitler: 1. Matematik i støbeskeen; 2. Matematikkens græske arv; 3. Den gyldne tidsalder for hinduer og arabere; 4. Matematik i Kina; 5. Renæssancens matematik; 6. Regning med infinitesimaler ser dagens lys; 7. Matematik i det tyvende århundrede....

  19. A case history of using high-resolution LiDAR data to support archaeological prediction models in a low-relief area

    Science.gov (United States)

    Pacskó, Vivien; Székely, Balázs; Stibrányi, Máté; Koma, Zsófia

    2016-04-01

    Hungary is situated in the crossroad of several large-scale infrastructural pathways like transnational pipelines and transcontinental motorways. At the same time the country is rich in known and potential archaeological sites. Archaeological prediction techniques aided by remote sensing are intended to help increase preparedness for archaeological surveying and rescue activities in response to planned new infrastructural developments (e.g., a new pipeline), as they try to estimate the number of potential archaeological sites, area to be surveyed, potential cost and time needed for these activities. In very low-relief areas microtopographic forms may indicate sites, high-resolution LiDAR DTMs are suitable for their detection. Main sources of archaeological prediction models are known archaeological sites, where optimal environmental conditions of settling down existed at historic ages. Hydrological characteristics, relief, geology, vegetation cover and soil are considered to be as most important natural factors. Sorting of the factors and accuracy of the sampling differentiate our models. Resolution of an inductive model depends on the spatial properties of the integrated data: a raster data set can be generated that contains probability values and the reliability of the estimation. The information content of the predictive model is highly influenced by the resolution of the used digital terrain model (DTM): its derivatives (slope, aspect, topographic features) are important inputs of the modelling. The quality of the DTM is even more important in low-relief areas as microtopographic features may indicate archaeological sites. The conventional digital elevation models (SRTM, ASTER GDEM) provide unsatisfying resolution (both in horizontal and vertical senses) as they are rather digital surface models containing the vegetation and the built-up structures. Processed multiecho LiDAR data can be used instead. Our study area is situated in the foothills of the

  20. Put the Family Back in Family Health History: A Multiple-Informant Approach.

    Science.gov (United States)

    Lin, Jielu; Marcum, Christopher S; Myers, Melanie F; Koehly, Laura M

    2017-05-01

    An accurate family health history is essential for individual risk assessment. This study uses a multiple-informant approach to examine whether family members have consistent perceptions of shared familial risk for four common chronic conditions (heart disease, Type 2 diabetes, high cholesterol, and hypertension) and whether accounting for inconsistency in family health history reports leads to more accurate risk assessment. In 2012-2013, individual and family health histories were collected from 127 adult informants of 45 families in the Greater Cincinnati Area. Pedigrees were linked within each family to assess inter-informant (in)consistency regarding common biological family member's health history. An adjusted risk assessment based on pooled pedigrees of multiple informants was evaluated to determine whether it could more accurately identify individuals affected by common chronic conditions, using self-reported disease diagnoses as a validation criterion. Analysis was completed in 2015-2016. Inter-informant consistency in family health history reports was 54% for heart disease, 61% for Type 2 diabetes, 43% for high cholesterol, and 41% for hypertension. Compared with the unadjusted risk assessment, the adjusted risk assessment correctly identified an additional 7%-13% of the individuals who had been diagnosed, with a ≤2% increase in cases that were predicted to be at risk but had not been diagnosed. Considerable inconsistency exists in individual knowledge of their family health history. Accounting for such inconsistency can, nevertheless, lead to a more accurate genetic risk assessment tool. A multiple-informant approach is potentially powerful when coupled with technology to support clinical decisions. Published by Elsevier Inc.

  1. Cultural history as polyphonic history

    Directory of Open Access Journals (Sweden)

    Burke, Peter

    2010-06-01

    Full Text Available This texts offers a reflection on the origins and actual development of the field of cultural history through a comparison with the term that has served as title for this seminar: “polyphonic history”. The author provides an overview of the themes that have structured the seminar (the history of representations, the history of the body and the cultural history of science with the aim of making explicit and clarifying this plurality of voices in the field of history as well as its pervasiveness in other research areas.

    En este texto se ofrece una reflexión sobre el origen y actual desarrollo del campo de la historia cultural a través de una comparación con el término que ha dado título a este seminario: “historia polifónica”. El autor propone un recorrido por las áreas temáticas que han conformado la estructura del seminario (la historia de las representaciones, la historia del cuerpo y la historia cultural de la ciencia con el objeto de explicitar y explicar esta pluralidad de voces en el campo de la historia, así como su repercusión en otras áreas del conocimiento.

  2. Analysis of K-net and Kik-net data: implications for ground motion prediction - acceleration time histories, response spectra and nonlinear site response; Analyse des donnees accelerometriques de K-net et Kik-net: implications pour la prediction du mouvement sismique - accelerogrammes et spectres de reponse - et la prise en compte des effets de site non-lineaire

    Energy Technology Data Exchange (ETDEWEB)

    Pousse, G

    2005-10-15

    This thesis intends to characterize ground motion during earthquake. This work is based on two Japanese networks. It deals with databases of shallow events, depth less than 25 km, with magnitude between 4.0 and 7.3. The analysis of K-net allows to compute a spectral ground motion prediction equation and to review the shape of the Eurocode 8 design spectra. We show the larger amplification at short period for Japanese data and bring in light the soil amplification that takes place at large period. In addition, we develop a new empirical model for simulating synthetic stochastic nonstationary acceleration time histories. By specifying magnitude, distance and site effect, this model allows to produce many time histories, that a seismic event is liable to produce at the place of interest. Furthermore, the study of near-field borehole records of the Kik-net allows to explore the validity domain of predictive equations and to explain what occurs by extrapolating ground motion predictions. Finally, we show that nonlinearity reduces the dispersion of ground motion at the surface. (author)

  3. Potted history

    NARCIS (Netherlands)

    Groot, N.; Van Dijk, T.

    2010-01-01

    The Jordan Valley was once populated by a people, now almost forgotten by historians, with whom the pharaoh of Egypt sought favour. That is the conclusion reached by Niels Groot, the first researcher to take a PhD at the Delft-Leiden Centre for Archaeology, Art History and Science.

  4. LCA History

    DEFF Research Database (Denmark)

    Bjørn, Anders; Owsianiak, Mikołaj; Molin, Christine

    2017-01-01

    The idea of LCA was conceived in the 1960s when environmental degradation and in particular the limited access to resources started becoming a concern. This chapter gives a brief summary of the history of LCA since then with a focus on the fields of methodological development, application...

  5. Prediction of Unsteady Transonic Aerodynamics Project

    Data.gov (United States)

    National Aeronautics and Space Administration — An accurate prediction of aero-elastic effects depends on an accurate prediction of the unsteady aerodynamic forces. Perhaps the most difficult speed regime is...

  6. Early, Accurate Diagnosis and Early Intervention in Cerebral Palsy: Advances in Diagnosis and Treatment.

    Science.gov (United States)

    Novak, Iona; Morgan, Cathy; Adde, Lars; Blackman, James; Boyd, Roslyn N; Brunstrom-Hernandez, Janice; Cioni, Giovanni; Damiano, Diane; Darrah, Johanna; Eliasson, Ann-Christin; de Vries, Linda S; Einspieler, Christa; Fahey, Michael; Fehlings, Darcy; Ferriero, Donna M; Fetters, Linda; Fiori, Simona; Forssberg, Hans; Gordon, Andrew M; Greaves, Susan; Guzzetta, Andrea; Hadders-Algra, Mijna; Harbourne, Regina; Kakooza-Mwesige, Angelina; Karlsson, Petra; Krumlinde-Sundholm, Lena; Latal, Beatrice; Loughran-Fowlds, Alison; Maitre, Nathalie; McIntyre, Sarah; Noritz, Garey; Pennington, Lindsay; Romeo, Domenico M; Shepherd, Roberta; Spittle, Alicia J; Thornton, Marelle; Valentine, Jane; Walker, Karen; White, Robert; Badawi, Nadia

    2017-09-01

    Cerebral palsy describes the most common physical disability in childhood and occurs in 1 in 500 live births. Historically, the diagnosis has been made between age 12 and 24 months but now can be made before 6 months' corrected age. To systematically review best available evidence for early, accurate diagnosis of cerebral palsy and to summarize best available evidence about cerebral palsy-specific early intervention that should follow early diagnosis to optimize neuroplasticity and function. This study systematically searched the literature about early diagnosis of cerebral palsy in MEDLINE (1956-2016), EMBASE (1980-2016), CINAHL (1983-2016), and the Cochrane Library (1988-2016) and by hand searching. Search terms included cerebral palsy, diagnosis, detection, prediction, identification, predictive validity, accuracy, sensitivity, and specificity. The study included systematic reviews with or without meta-analyses, criteria of diagnostic accuracy, and evidence-based clinical guidelines. Findings are reported according to the PRISMA statement, and recommendations are reported according to the Appraisal of Guidelines, Research and Evaluation (AGREE) II instrument. Six systematic reviews and 2 evidence-based clinical guidelines met inclusion criteria. All included articles had high methodological Quality Assessment of Diagnostic Accuracy Studies (QUADAS) ratings. In infants, clinical signs and symptoms of cerebral palsy emerge and evolve before age 2 years; therefore, a combination of standardized tools should be used to predict risk in conjunction with clinical history. Before 5 months' corrected age, the most predictive tools for detecting risk are term-age magnetic resonance imaging (86%-89% sensitivity), the Prechtl Qualitative Assessment of General Movements (98% sensitivity), and the Hammersmith Infant Neurological Examination (90% sensitivity). After 5 months' corrected age, the most predictive tools for detecting risk are magnetic resonance imaging (86

  7. Business History as Cultural History

    DEFF Research Database (Denmark)

    Lunde Jørgensen, Ida

    The paper engages with the larger question of how cultural heritage becomes taken for granted and offers a complimentary view to the anthropological ʻCopenhagen School’ of business history, one that draws attention to the way corporate wealth directly and indirectly influences the culture available...

  8. Sommerferiens historie

    DEFF Research Database (Denmark)

    Lützen, Karin

    2011-01-01

    Summer holiday is a pleasure which did not become available to many people until the 20th Century. The article describes the early mountain rambles of the bourgeoisie and their holidays in seaside boarding houses. Outdoor pursuits and stays in boarding houses at bathing resorts also became...... pattern. Finally, the history of the special holiday camps is told, which were established by American Jews because they were excluded from many hotels....

  9. Business History

    DEFF Research Database (Denmark)

    Hansen, Per H.

    2012-01-01

    This article argues that a cultural and narrative perspective can enrich the business history field, encourage new and different questions and answers, and provide new ways of thinking about methods and empirical material. It discusses what culture is and how it relates to narratives. Taking...... a cultural and narrative approach may affect questions, sources, and methodologies, as well as the status of our results. Finally, a narrative approach may contribute to our historical understanding of entrepreneurship and globalization....

  10. Analytical history

    OpenAIRE

    Bertrand M. Roehner

    2017-01-01

    The purpose of this note is to explain what is "analytical history", a modular and testable analysis of historical events introduced in a book published in 2002 (Roehner and Syme 2002). Broadly speaking, it is a comparative methodology for the analysis of historical events. Comparison is the keystone and hallmark of science. For instance, the extrasolar planets are crucial for understanding our own solar system. Until their discovery, astronomers could observe only one instance. Single instan...

  11. Diffusion archeology for diffusion progression history reconstruction.

    Science.gov (United States)

    Sefer, Emre; Kingsford, Carl

    2016-11-01

    Diffusion through graphs can be used to model many real-world processes, such as the spread of diseases, social network memes, computer viruses, or water contaminants. Often, a real-world diffusion cannot be directly observed while it is occurring - perhaps it is not noticed until some time has passed, continuous monitoring is too costly, or privacy concerns limit data access. This leads to the need to reconstruct how the present state of the diffusion came to be from partial diffusion data. Here, we tackle the problem of reconstructing a diffusion history from one or more snapshots of the diffusion state. This ability can be invaluable to learn when certain computer nodes are infected or which people are the initial disease spreaders to control future diffusions. We formulate this problem over discrete-time SEIRS-type diffusion models in terms of maximum likelihood. We design methods that are based on submodularity and a novel prize-collecting dominating-set vertex cover (PCDSVC) relaxation that can identify likely diffusion steps with some provable performance guarantees. Our methods are the first to be able to reconstruct complete diffusion histories accurately in real and simulated situations. As a special case, they can also identify the initial spreaders better than the existing methods for that problem. Our results for both meme and contaminant diffusion show that the partial diffusion data problem can be overcome with proper modeling and methods, and that hidden temporal characteristics of diffusion can be predicted from limited data.

  12. Diffusion archeology for diffusion progression history reconstruction

    Science.gov (United States)

    Sefer, Emre; Kingsford, Carl

    2015-01-01

    Diffusion through graphs can be used to model many real-world processes, such as the spread of diseases, social network memes, computer viruses, or water contaminants. Often, a real-world diffusion cannot be directly observed while it is occurring — perhaps it is not noticed until some time has passed, continuous monitoring is too costly, or privacy concerns limit data access. This leads to the need to reconstruct how the present state of the diffusion came to be from partial diffusion data. Here, we tackle the problem of reconstructing a diffusion history from one or more snapshots of the diffusion state. This ability can be invaluable to learn when certain computer nodes are infected or which people are the initial disease spreaders to control future diffusions. We formulate this problem over discrete-time SEIRS-type diffusion models in terms of maximum likelihood. We design methods that are based on submodularity and a novel prize-collecting dominating-set vertex cover (PCDSVC) relaxation that can identify likely diffusion steps with some provable performance guarantees. Our methods are the first to be able to reconstruct complete diffusion histories accurately in real and simulated situations. As a special case, they can also identify the initial spreaders better than the existing methods for that problem. Our results for both meme and contaminant diffusion show that the partial diffusion data problem can be overcome with proper modeling and methods, and that hidden temporal characteristics of diffusion can be predicted from limited data. PMID:27821901

  13. Prediction of outcome in patients with low back pain

    DEFF Research Database (Denmark)

    Kongsted, Alice; Andersen, Cathrine Hedegaard; Mørk Hansen, Martin

    2016-01-01

    intensity (0-10) and disability (RMDQ) after 2-weeks, 3-months, and 12-months. The course of LBP in 859 patients was predicted to be short (54%), prolonged (36%), or chronic (7%). Clinicians' expectations were most strongly associated with education, LBP history, radiating pain, and neurological signs......' expectations of outcome from a LBP episode, 2) if clinicians' expectations related to outcome, 3) how accurate clinical predictions were as compared to those of the STarT Back Screening Tool (SBT), and 4) if accuracy was improved by combining clinicians' expectations and the SBT. Outcomes were measured as LBP...

  14. Accurate test limits under prescribed consumer risk

    NARCIS (Netherlands)

    Albers, Willem/Wim; Arts, G.R.J.; Kallenberg, W.C.M.

    1997-01-01

    Measurement errors occurring during inspection of manufactured parts force producers to replace specification limits by slightly more strict test limits. Here accurate test limits are presented which maximize the yield while limiting the fraction of defectives reaching the consumer.

  15. Decoding Galactic Merger Histories

    Directory of Open Access Journals (Sweden)

    Eric F. Bell

    2017-12-01

    Full Text Available Galaxy mergers are expected to influence galaxy properties, yet measurements of individual merger histories are lacking. Models predict that merger histories can be measured using stellar halos and that these halos can be quantified using observations of resolved stars along their minor axis. Such observations reveal that Milky Way-mass galaxies have a wide range of stellar halo properties and show a correlation between their stellar halo masses and metallicities. This correlation agrees with merger-driven models where stellar halos are formed by satellite galaxy disruption. In these models, the largest accreted satellite dominates the stellar halo properties. Consequently, the observed diversity in the stellar halos of Milky Way-mass galaxies implies a large range in the masses of their largest merger partners. In particular, the Milky Way’s low mass halo implies an unusually quiet merger history. We used these measurements to seek predicted correlations between the bulge and central black hole (BH mass and the mass of the largest merger partner. We found no significant correlations: while some galaxies with large bulges and BHs have large stellar halos and thus experienced a major or minor merger, half have small stellar halos and never experienced a significant merger event. These results indicate that bulge and BH growth is not solely driven by merger-related processes.

  16. Ildens historier

    DEFF Research Database (Denmark)

    Lassen, Henrik Roesgaard

    In December 2012 a manuscript entitled "Tællelyset" ['The Tallow Candle'] was discovered in an archive. The story was subsequently presented to the world as Hans Christian Andersen's first fairy tale and rather bombastically celebrated as such. In this book it is demonstrated that the text cannot...... have been written by Andersen. In several chapters the curiously forgotten history of fire-lighting technology is outlined, and it is demonstrated that "Tællelyset" is written by a person with a modern perspective on how to light a candle - among other things. The central argument in the book springs...

  17. The FLUKA code: An accurate simulation tool for particle therapy

    CERN Document Server

    Battistoni, Giuseppe; Böhlen, Till T; Cerutti, Francesco; Chin, Mary Pik Wai; Dos Santos Augusto, Ricardo M; Ferrari, Alfredo; Garcia Ortega, Pablo; Kozlowska, Wioletta S; Magro, Giuseppe; Mairani, Andrea; Parodi, Katia; Sala, Paola R; Schoofs, Philippe; Tessonnier, Thomas; Vlachoudis, Vasilis

    2016-01-01

    Monte Carlo (MC) codes are increasingly spreading in the hadrontherapy community due to their detailed description of radiation transport and interaction with matter. The suitability of a MC code for application to hadrontherapy demands accurate and reliable physical models capable of handling all components of the expected radiation field. This becomes extremely important for correctly performing not only physical but also biologically-based dose calculations, especially in cases where ions heavier than protons are involved. In addition, accurate prediction of emerging secondary radiation is of utmost importance in innovativ