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Sample records for chemogenomic profiling predicts

  1. Chemogenomic profiling of Plasmodium falciparum as a tool to aid antimalarial drug discovery.

    Science.gov (United States)

    Pradhan, Anupam; Siwo, Geoffrey H; Singh, Naresh; Martens, Brian; Balu, Bharath; Button-Simons, Katrina A; Tan, Asako; Zhang, Min; Udenze, Kenneth O; Jiang, Rays H Y; Ferdig, Michael T; Adams, John H; Kyle, Dennis E

    2015-01-01

    The spread of Plasmodium falciparum multidrug resistance highlights the urgency to discover new targets and chemical scaffolds. Unfortunately, lack of experimentally validated functional information about most P. falciparum genes remains a strategic hurdle. Chemogenomic profiling is an established tool for classification of drugs with similar mechanisms of action by comparing drug fitness profiles in a collection of mutants. Inferences of drug mechanisms of action and targets can be obtained by associations between shifts in drug fitness and specific genetic changes in the mutants. In this screen, P. falciparum, piggyBac single insertion mutants were profiled for altered responses to antimalarial drugs and metabolic inhibitors to create chemogenomic profiles. Drugs targeting the same pathway shared similar response profiles and multiple pairwise correlations of the chemogenomic profiles revealed novel insights into drugs' mechanisms of action. A mutant of the artemisinin resistance candidate gene - "K13-propeller" gene (PF3D7_1343700) exhibited increased susceptibility to artemisinin drugs and identified a cluster of 7 mutants based on similar enhanced responses to the drugs tested. Our approach of chemogenomic profiling reveals artemisinin functional activity, linked by the unexpected drug-gene relationships of these mutants, to signal transduction and cell cycle regulation pathways.

  2. Identification of drug targets by chemogenomic and metabolomic profiling in yeast

    KAUST Repository

    Wu, Manhong

    2012-12-01

    OBJECTIVE: To advance our understanding of disease biology, the characterization of the molecular target for clinically proven or new drugs is very important. Because of its simplicity and the availability of strains with individual deletions in all of its genes, chemogenomic profiling in yeast has been used to identify drug targets. As measurement of drug-induced changes in cellular metabolites can yield considerable information about the effects of a drug, we investigated whether combining chemogenomic and metabolomic profiling in yeast could improve the characterization of drug targets. BASIC METHODS: We used chemogenomic and metabolomic profiling in yeast to characterize the target for five drugs acting on two biologically important pathways. A novel computational method that uses a curated metabolic network was also developed, and it was used to identify the genes that are likely to be responsible for the metabolomic differences found. RESULTS AND CONCLUSION: The combination of metabolomic and chemogenomic profiling, along with data analyses carried out using a novel computational method, could robustly identify the enzymes targeted by five drugs. Moreover, this novel computational method has the potential to identify genes that are causative of metabolomic differences or drug targets. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.

  3. Zebrafish whole-adult-organism chemogenomics for large-scale predictive and discovery chemical biology.

    Directory of Open Access Journals (Sweden)

    Siew Hong Lam

    2008-07-01

    Full Text Available The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly, is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated aromatic hydrocarbons [P(HAHs] and estrogenic compounds (ECs, we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR and estrogen receptor (ER agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology.

  4. Identification of cancer-cytotoxic modulators of PDE3A by predictive chemogenomics | Office of Cancer Genomics

    Science.gov (United States)

    High cancer death rates indicate the need for new anticancer therapeutic agents. Approaches to discovering new cancer drugs include target-based drug discovery and phenotypic screening. Here, we identified phosphodiesterase 3A modulators as cell-selective cancer cytotoxic compounds through phenotypic compound library screening and target deconvolution by predictive chemogenomics.

  5. Prediction of drug-drug interactions from chemogenomic and gene-gene interactions and analysis of drug-drug interactions

    OpenAIRE

    2013-01-01

    The interactions between multiple drugs administered to an organism concurrently, whether in the form of synergy or antagonism, are of clinical relevance. Moreover, un-derstanding the mechanisms and nature of drug-drug interactions is of great practical and theoretical interest. Work has previously been done on gene-gene and gene-drug interactions, but the prediction and rationalization of drug-drug interactions from this data is not straightforward. We present a strategy for attacking this p...

  6. Applications of chemogenomic library screening in drug discovery.

    Science.gov (United States)

    Jones, Lyn H; Bunnage, Mark E

    2017-01-20

    The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.

  7. Data Mining of Chemogenomics Data Using Bi-Modal PLS Methods and Chemical Interpretation for Molecular Design.

    Science.gov (United States)

    Hasegawa, Kiyoshi; Funatsu, Kimito

    2014-12-01

    Chemogenomics is a new strategy in drug discovery for interrogating all molecules capable of interacting with all biological targets. Because of the almost infinite number of drug-like organic molecules, bench-based experimental chemogenomics methods are not generally feasible. Several in silico chemogenomics models have therefore been developed for high-throughput screening of large numbers of drug candidate compounds and target proteins. In previous studies, we described two novel bi-modal PLS approaches. These methods provide a significant advantage in that they enable direct connections to be made between biological activities and ligand and protein descriptors. In this special issue, we review these two PLS-based approaches using two different chemogenomics datasets for illustration. We then compare the predictive and interpretive performance of the two methods using the same congeneric data set.

  8. A systematic study of chemogenomics of carbohydrates.

    Science.gov (United States)

    Gu, Jiangyong; Luo, Fang; Chen, Lirong; Yuan, Gu; Xu, Xiaojie

    2014-03-04

    Chemogenomics focuses on the interactions between biologically active molecules and protein targets for drug discovery. Carbohydrates are the most abundant compounds in natural products. Compared with other drugs, the carbohydrate drugs show weaker side effects. Searching for multi-target carbohydrate drugs can be regarded as a solution to improve therapeutic efficacy and safety. In this work, we collected 60 344 carbohydrates from the Universal Natural Products Database (UNPD) and explored the chemical space of carbohydrates by principal component analysis. We found that there is a large quantity of potential lead compounds among carbohydrates. Then we explored the potential of carbohydrates in drug discovery by using a network-based multi-target computational approach. All carbohydrates were docked to 2389 target proteins. The most potential carbohydrates for drug discovery and their indications were predicted based on a docking score-weighted prediction model. We also explored the interactions between carbohydrates and target proteins to find the pathological networks, potential drug candidates and new indications.

  9. Chemogenomics approaches for receptor deorphanization and extensions of the chemogenomics concept to phenotypic space

    NARCIS (Netherlands)

    Horst, E. van der; Peironcely, J.E.; Westen, G.J.P. van; Hoven, O.O. van den; Galloway, W.R.J.D.; Spring, D.R.; Wegner, J.K.; Vlijmen, H.W.T. van; Ijzerman, A.P.; Overington, J.P.; Bender, A.

    2011-01-01

    Chemogenomic approaches, which link ligand chemistry to bioactivity against targets (and, by extension, to phenotypes) are becoming more and more important due to the increasing number of bioactivity data available both in proprietary databases as well as in the public domain. In this article we rev

  10. Theoretical approaches to the prediction of the biological targets of small-molecular compounds based on chemogenomic information%应用化学基因组信息预测小分子化合物的潜在生物靶标的理论方法

    Institute of Scientific and Technical Information of China (English)

    李嫣; 王任小

    2009-01-01

    In this post-genomic era, chemogenomics can be applied in target elucidation, understanding of the effects of small-molecular compounds on biological pathways, and discovery of novel active compounds. These new techniques collectively play an important role in modern drug discovery. This article reviews the existing theoretical approaches to the prediction of biological targets of small-molecular compounds based on chemogenomic information, including chemical similarity searching, reverse docking, data mining, and bioactivity spectrum, and depicts the strength and shortcomings of these methods as well as their perspectives in the future.%在后基因组时代,化学基因组技术在药物作用靶点的确认、小分子化合物对通路的作用,以及小分子先导化合物的识别等方面都有着广泛的应用,为新药研发提供了新的技术方法.本文主要介绍了当前几种基于化学基因组信息来预测小分子化合物潜在生物靶标的理论方法(包括化学相似性搜索方法、反向分子对接方法、数据挖掘方法以及生物活性谱图分析方法),并分析了这些方法的优缺点以及应用前景.

  11. Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

    Science.gov (United States)

    Birkholtz, Lyn-Marie; Bastien, Olivier; Wells, Gordon; Grando, Delphine; Joubert, Fourie; Kasam, Vinod; Zimmermann, Marc; Ortet, Philippe; Jacq, Nicolas; Saïdani, Nadia; Roy, Sylvaine; Hofmann-Apitius, Martin; Breton, Vincent; Louw, Abraham I; Maréchal, Eric

    2006-11-17

    The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.

  12. Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

    Directory of Open Access Journals (Sweden)

    Hofmann-Apitius Martin

    2006-11-01

    Full Text Available Abstract The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1 the comparison of protein sequences including compositionally atypical malaria sequences, 2 the high throughput reconstruction of molecular phylogenies, 3 the representation of biological processes, particularly metabolic pathways, 4 the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5 the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.

  13. Bringing kinases into focus: efficient drug design through the use of chemogenomic toolkits.

    Science.gov (United States)

    Birault, Veronique; Harris, C John; Le, Joelle; Lipkin, Mike; Nerella, Ravi; Stevens, Adrian

    2006-01-01

    The study of protein target families, as opposed to single targets, has become a very powerful tool in chemogenomics-led drug discovery. By integrating comprehensive chemoinformatics and bioinformatics databases with customised analytical tools, a 'Toolkit' approach for the target family is possible, thus allowing predictions of the ligand class, affinity, selectivity and likely off-target issues to be made for the guidance of the medicinal chemist. In this review, we highlight the development and application of the Toolkit approach to the protein kinase superfamily, drawing on examples from lead optimisation studies and the design of focused libraries for lead discovery.

  14. Chemogenomics knowledgebase and systems pharmacology for hallucinogen target identification-Salvinorin A as a case study.

    Science.gov (United States)

    Xu, Xiaomeng; Ma, Shifan; Feng, Zhiwei; Hu, Guanxing; Wang, Lirong; Xie, Xiang-Qun

    2016-11-01

    Drug abuse is a serious problem worldwide. Recently, hallucinogens have been reported as a potential preventative and auxiliary therapy for substance abuse. However, the use of hallucinogens as a drug abuse treatment has potential risks, as the fundamental mechanisms of hallucinogens are not clear. So far, no scientific database is available for the mechanism research of hallucinogens. We constructed a hallucinogen-specific chemogenomics database by collecting chemicals, protein targets and pathways closely related to hallucinogens. This information, together with our established computational chemogenomics tools, such as TargetHunter and HTDocking, provided a one-step solution for the mechanism study of hallucinogens. We chose salvinorin A, a potent hallucinogen extracted from the plant Salvia divinorum, as an example to demonstrate the usability of our platform. With the help of HTDocking program, we predicted four novel targets for salvinorin A, including muscarinic acetylcholine receptor 2, cannabinoid receptor 1, cannabinoid receptor 2 and dopamine receptor 2. We looked into the interactions between salvinorin A and the predicted targets. The binding modes, pose and docking scores indicate that salvinorin A may interact with some of these predicted targets. Overall, our database enriched the information of systems pharmacological analysis, target identification and drug discovery for hallucinogens.

  15. Predicted profiles of ultraviolet interstellar absorption lines

    Energy Technology Data Exchange (ETDEWEB)

    Welty, D.E.; Hobbs, L.M.; York, D.G. (Chicago, University, IL (USA))

    1991-02-01

    In this paper, values of the column density, line width parameter, and velocity are determined for as many components derived from optical interstellar absorption-line profiles of Na I and K I as needed to reproduce the observed high-resolution optical profiles of the D lines of Na I toward eight lightly reddened stars and of the 7698 A line of K I toward six moderately reddened stars. The derived component structures are then used to predict UV absorption-line profiles due to C I, Mg I, S I, Si I, and Fe I along the same lines of sight. Comparison of the predicted profiles with existing lower resolution line profiles and equivalent width data suggests that this simple scaling procedure can in many cases fairly reliably predict the UV profiles from the observed optical ones. 64 refs.

  16. A predictable Java profile - rationale and implementations

    DEFF Research Database (Denmark)

    Søndergaard, Hans; Bøgholm, Thomas; Hansen, Rene Rydhof;

    2009-01-01

    , and is directly inspired by interactions with the Open Group on their on-going work on a safety critical Java profile (JSR-302). The main contribution is an arrangement of the class hierarchy such that the proposal is a generalization of Real-Time Specification for Java (RTSJ). A further contribution......A Java profile suitable for development of high integrity embedded systems is presented. It is based on event handlers which are grouped in missions and equipped with respectively private handler memory and shared mission memory. This is a result of our previous work on developing a Java profile...

  17. A predictable Java profile - rationale and implementations

    DEFF Research Database (Denmark)

    Søndergaard, Hans; Bøgholm, Thomas; Hansen, Rene Rydhof;

    2009-01-01

    , and is directly inspired by interactions with the Open Group on their on-going work on a safety critical Java profile (JSR-302). The main contribution is an arrangement of the class hierarchy such that the proposal is a generalization of Real-Time Specification for Java (RTSJ). A further contribution...

  18. Expression profiling predicts outcome in breast cancer

    NARCIS (Netherlands)

    Bernards, R.A.; Veer, L.J. van ’t; Dai, H.; Vijver, M.J. van de; He, Y.D.; Hart, A.A.M.; Friend, S.H.

    2003-01-01

    Gruvberger et al. postulate, in their commentary published in this issue of Breast Cancer Research, that our “prognostic gene set may not be broadly applicable to other breast tumor cohorts”, and they suggest that “it may be important to define prognostic expression profiles separately in estrogen r

  19. Chemogenomic identification of Ref-1/AP-1 as a therapeutic target for asthma

    OpenAIRE

    Nguyen, Cu; Teo, Jia-Ling; Matsuda, Akihisa; Eguchi, Masakatsu; Emil Y Chi; William R Henderson; Kahn, Michael

    2003-01-01

    Asthma is characterized by an oxidant/antioxidant imbalance in the lungs leading to activation of redox-sensitive transcription factors, nuclear factor κB (NF-κB), and activator protein-1 (AP-1). To develop therapeutic strategies for asthma, we used a chemogenomics approach to screen for small molecule inhibitor(s) of AP-1 transcription. We developed a β-strand mimetic template that acts as a reversible inhibitor (pseudosubstrate) of redox proteins. This template incorporates an enedione moie...

  20. The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics.

    Science.gov (United States)

    Gianoulis, Tara A; Agarwal, Ashish; Snyder, Michael; Gerstein, Mark B

    2011-01-01

    Biological data is often tabular but finding statistically valid connections between entities in a sequence of tables can be problematic--for example, connecting particular entities in a drug property table to gene properties in a second table, using a third table associating genes with drugs. Here we present an approach (CRIT) to find connections such as these and show how it can be applied in a variety of genomic contexts including chemogenomics data.

  1. In silico repositioning-chemogenomics strategy identifies new drugs with potential activity against multiple life stages of Schistosoma mansoni.

    Science.gov (United States)

    Neves, Bruno J; Braga, Rodolpho C; Bezerra, José C B; Cravo, Pedro V L; Andrade, Carolina H

    2015-01-01

    Morbidity and mortality caused by schistosomiasis are serious public health problems in developing countries. Because praziquantel is the only drug in therapeutic use, the risk of drug resistance is a concern. In the search for new schistosomicidal drugs, we performed a target-based chemogenomics screen of a dataset of 2,114 proteins to identify drugs that are approved for clinical use in humans that may be active against multiple life stages of Schistosoma mansoni. Each of these proteins was treated as a potential drug target, and its amino acid sequence was used to interrogate three databases: Therapeutic Target Database (TTD), DrugBank and STITCH. Predicted drug-target interactions were refined using a combination of approaches, including pairwise alignment, conservation state of functional regions and chemical space analysis. To validate our strategy, several drugs previously shown to be active against Schistosoma species were correctly predicted, such as clonazepam, auranofin, nifedipine, and artesunate. We were also able to identify 115 drugs that have not yet been experimentally tested against schistosomes and that require further assessment. Some examples are aprindine, gentamicin, clotrimazole, tetrabenazine, griseofulvin, and cinnarizine. In conclusion, we have developed a systematic and focused computer-aided approach to propose approved drugs that may warrant testing and/or serve as lead compounds for the design of new drugs against schistosomes.

  2. The power profile predicts road cycling MMP.

    Science.gov (United States)

    Quod, M J; Martin, D T; Martin, J C; Laursen, P B

    2010-06-01

    Laboratory tests of fitness variables have previously been shown to be valid predictors of cycling time-trial performance. However, due to the influence of drafting, tactics and the variability of power output in mass-start road races, comparisons between laboratory tests and competition performance are limited. The purpose of this study was to compare the power produced in the laboratory Power Profile (PP) test and Maximum Mean Power (MMP) analysis of competition data. Ten male cyclists (mean+/-SD: 20.8+/-1.5 y, 67.3+/-5.5 kg, V O (2 max) 72.7+/-5.1 mL x kg (-1) x min (-1)) completed a PP test within 14 days of competing in a series of road races. No differences were found between PP results and MMP analysis of competition data for durations of 60-600 s, total work or estimates of critical power and the fixed amount of work that can be completed above critical power (W'). Self-selected cadence was 15+/-7 rpm higher in the lab. These results indicate that the PP test is an ecologically valid assessment of power producing capacity over cycling specific durations. In combination with MMP analysis, this may be a useful tool for quantifying elements of cycling specific performance in competitive cyclists.

  3. Identification of yeast genes that confer resistance to chitosan oligosaccharide (COS using chemogenomics

    Directory of Open Access Journals (Sweden)

    Jaime Maria DLA

    2012-06-01

    Full Text Available Abstract Background Chitosan oligosaccharide (COS, a deacetylated derivative of chitin, is an abundant, and renewable natural polymer. COS has higher antimicrobial properties than chitosan and is presumed to act by disrupting/permeabilizing the cell membranes of bacteria, yeast and fungi. COS is relatively non-toxic to mammals. By identifying the molecular and genetic targets of COS, we hope to gain a better understanding of the antifungal mode of action of COS. Results Three different chemogenomic fitness assays, haploinsufficiency (HIP, homozygous deletion (HOP, and multicopy suppression (MSP profiling were combined with a transcriptomic analysis to gain insight in to the mode of action and mechanisms of resistance to chitosan oligosaccharides. The fitness assays identified 39 yeast deletion strains sensitive to COS and 21 suppressors of COS sensitivity. The genes identified are involved in processes such as RNA biology (transcription, translation and regulatory mechanisms, membrane functions (e.g. signalling, transport and targeting, membrane structural components, cell division, and proteasome processes. The transcriptomes of control wild type and 5 suppressor strains overexpressing ARL1, BCK2, ERG24, MSG5, or RBA50, were analyzed in the presence and absence of COS. Some of the up-regulated transcripts in the suppressor overexpressing strains exposed to COS included genes involved in transcription, cell cycle, stress response and the Ras signal transduction pathway. Down-regulated transcripts included those encoding protein folding components and respiratory chain proteins. The COS-induced transcriptional response is distinct from previously described environmental stress responses (i.e. thermal, salt, osmotic and oxidative stress and pre-treatment with these well characterized environmental stressors provided little or any resistance to COS. Conclusions Overexpression of the ARL1 gene, a member of the Ras superfamily that regulates membrane

  4. Profiled support vector machines for antisense oligonucleotide efficacy prediction

    Directory of Open Access Journals (Sweden)

    Martín-Guerrero José D

    2004-09-01

    Full Text Available Abstract Background This paper presents the use of Support Vector Machines (SVMs for prediction and analysis of antisense oligonucleotide (AO efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1 feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE, and (2 AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions. Results In the first stage, the SVM-RFE technique was most efficient and robust in the presence of low number of samples and high input space dimension. This method yielded an optimal subset of 14 representative features, which were all related to energy and sequence motifs. The second stage evaluated the performance of the predictors (overall correlation coefficient between observed and predicted efficacy, r; mean error, ME; and root-mean-square-error, RMSE using 8-fold and minus-one-RNA cross-validation methods. The profiled SVM produced the best results (r = 0.44, ME = 0.022, and RMSE= 0.278 and predicted high (>75% inhibition of gene expression and low efficacy (http://aosvm.cgb.ki.se/. Conclusions The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well.

  5. Prediction of Protein-Protein Interactions Using Protein Signature Profiling

    Institute of Scientific and Technical Information of China (English)

    Mahmood A. Mahdavi; Yen-Han Lin

    2007-01-01

    Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain inter- actions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis ele- gans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area un- der the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs in- creased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on aver- age 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.

  6. Chemogenomic discovery of allosteric antagonists at the GPRC6A receptor

    DEFF Research Database (Denmark)

    Gloriam, David E.; Wellendorph, Petrine; Johansen, Lars Dan;

    2011-01-01

    and pharmacological character: (1) chemogenomic lead identification through the first, to our knowledge, ligand inference between two different GPCR families, Families A and C; and (2) the discovery of the most selective GPRC6A allosteric antagonists discovered to date. The unprecedented inference of...... pharmacological activity across GPCR families provides proof-of-concept for in silico approaches against Family C targets based on Family A templates, greatly expanding the prospects of successful drug design and discovery. The antagonists were tested against a panel of seven Family A and C G protein-coupled receptors...

  7. A lifetime prediction method for LEDs considering mission profiles

    DEFF Research Database (Denmark)

    Qu, Xiaohui; Wang, Huai; Zhan, Xiaoqing

    2016-01-01

    and to benchmark the cost-competitiveness of different lighting technologies. The existing lifetime data released by LED manufacturers or standard organizations are usually applicable only for specific temperature and current levels. Significant lifetime discrepancies may be observed in field operations due...... to the varying operational and environmental conditions during the entire service time (i.e., mission profiles). To overcome the challenge, this paper proposes an advanced lifetime prediction method, which takes into account the field operation mission profiles and the statistical properties of the life data...

  8. DSP: a protein shape string and its profile prediction server.

    Science.gov (United States)

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

    2012-07-01

    Many studies have demonstrated that shape string is an extremely important structure representation, since it is more complete than the classical secondary structure. The shape string provides detailed information also in the regions denoted random coil. But few services are provided for systematic analysis of protein shape string. To fill this gap, we have developed an accurate shape string predictor based on two innovative technologies: a knowledge-driven sequence alignment and a sequence shape string profile method. The performance on blind test data demonstrates that the proposed method can be used for accurate prediction of protein shape string. The DSP server provides both predicted shape string and sequence shape string profile for each query sequence. Using this information, the users can compare protein structure or display protein evolution in shape string space. The DSP server is available at both http://cheminfo.tongji.edu.cn/dsp/ and its main mirror http://chemcenter.tongji.edu.cn/dsp/.

  9. Metabolomic profiling predicts outcome of rituximab therapy in rheumatoid arthritis

    OpenAIRE

    Sweeney, Shannon R; Kavanaugh, Arthur; Lodi, Alessia; Wang, Bo; Boyle, David; Tiziani, Stefano; Guma, Monica

    2016-01-01

    Objective: To determine whether characterisation of patients' metabolic profiles, utilising nuclear magnetic resonance (NMR) and mass spectrometry (MS), could predict response to rituximab therapy. 23 patients with active, seropositive rheumatoid arthritis (RA) on concomitant methotrexate were treated with rituximab. Patients were grouped into responders and non-responders according to the American College of Rheumatology improvement criteria, at a 20% level at 6 months. A Bruker Avance 700 M...

  10. Comparison of Cluster Lensing Profiles with Lambda CDM Predictions

    CERN Document Server

    Broadhurst, Tom; Medezinski, Elinor; Oguri, Masamune; Rephaeli, Yoel

    2008-01-01

    We derive lens distortion and magnification profiles of four well known clusters observed with Subaru. Each cluster is very well fitted by the general form predicted for Cold Dark Matter (CDM) dominated halos, with good consistency found between the independent distortion and magnification measurements. The inferred level of mass concentration is surprisingly high, 8 = 10.39 \\pm 0.91), compared to the relatively shallow profiles predicted by the LCDM model, c_{vir} = 5.06 \\pm 1.10 (for =1.25\\times 10^{15} M_{\\odot}/h). This represents a 4\\sigma discrepancy, and includes the relatively modest effects of projection bias and profile evolution derived from N-body simulations, which oppose each other with little residual effect. In the context of CDM based cosmologies, this discrepancy implies some modification of the widely assumed spectrum of initial density perturbations, so clusters collapse earlier (z > 1) than predicted (z<0.5) when the Universe was correspondingly denser.

  11. A Lifetime Prediction Method for LEDs Considering Real Mission Profiles

    DEFF Research Database (Denmark)

    Qu, Xiaohui; Wang, Huai; Zhan, Xiaoqing

    2017-01-01

    The Light-Emitting Diode (LED) has become a very promising alternative lighting source with the advantages of longer lifetime and higher efficiency than traditional ones. The lifetime prediction of LEDs is important to guide the LED system designers to fulfill the design specifications and to ben......The Light-Emitting Diode (LED) has become a very promising alternative lighting source with the advantages of longer lifetime and higher efficiency than traditional ones. The lifetime prediction of LEDs is important to guide the LED system designers to fulfill the design specifications...... operations due to the varying operational and environmental conditions during the entire service time (i.e., mission profiles). To overcome the challenge, this paper proposes an advanced lifetime prediction method, which takes into account the field operation mission profiles and also the statistical...... properties of the life data available from accelerated degradation testing. The electrical and thermal characteristics of LEDs are measured by a T3Ster system, used for the electro-thermal modeling. It also identifies key variables (e.g., heat sink parameters) that can be designed to achieve a specified...

  12. Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction*

    Science.gov (United States)

    Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

    2017-01-01

    Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. PMID

  13. Predicting Post-Editor Profiles from the Translation Process

    DEFF Research Database (Denmark)

    Singla, Karan; Orrego-Carmona, David; Gonzales, Ashleigh Rhea

    2014-01-01

    The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT...... of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities....

  14. Prediction of the endocrine disruption profile of pesticides.

    Science.gov (United States)

    Devillers, J; Bro, E; Millot, F

    2015-01-01

    Numerous manmade chemicals released into the environment can interfere with normal, hormonally regulated biological processes to adversely affect the development and reproductive functions of living species. Various in vivo and in vitro tests have been designed for detecting endocrine disruptors, but the number of chemicals to test is so high that to save time and money, (quantitative) structure-activity relationship ((Q)SAR) models are increasingly used as a surrogate for these laboratory assays. However, most of them focus only on a specific target (e.g. estrogenic or androgenic receptor) while, to be more efficient, endocrine disruption modelling should preferentially consider profiles of activities to better gauge this complex phenomenon. In this context, an attempt was made to evaluate the endocrine disruption profile of 220 structurally diverse pesticides using the Endocrine Disruptome simulation (EDS) tool, which simultaneously predicts the probability of binding of chemicals on 12 nuclear receptors. In a first step, the EDS web-based system was successfully applied to 16 pharmaceutical compounds known to target at least one of the studied receptors. About 13% of the studied pesticides were estimated to be potential disruptors of the endocrine system due to their high predicted affinity for at least one receptor. In contrast, about 55% of them were unlikely to be endocrine disruptors. The simulation results are discussed and some comments on the use of the EDS tool are made.

  15. Computational lipidology: predicting lipoprotein density profiles in human blood plasma.

    Directory of Open Access Journals (Sweden)

    Katrin Hübner

    2008-05-01

    Full Text Available Monitoring cholesterol levels is strongly recommended to identify patients at risk for myocardial infarction. However, clinical markers beyond "bad" and "good" cholesterol are needed to precisely predict individual lipid disorders. Our work contributes to this aim by bringing together experiment and theory. We developed a novel computer-based model of the human plasma lipoprotein metabolism in order to simulate the blood lipid levels in high resolution. Instead of focusing on a few conventionally used predefined lipoprotein density classes (LDL, HDL, we consider the entire protein and lipid composition spectrum of individual lipoprotein complexes. Subsequently, their distribution over density (which equals the lipoprotein profile is calculated. As our main results, we (i successfully reproduced clinically measured lipoprotein profiles of healthy subjects; (ii assigned lipoproteins to narrow density classes, named high-resolution density sub-fractions (hrDS, revealing heterogeneous lipoprotein distributions within the major lipoprotein classes; and (iii present model-based predictions of changes in the lipoprotein distribution elicited by disorders in underlying molecular processes. In its present state, the model offers a platform for many future applications aimed at understanding the reasons for inter-individual variability, identifying new sub-fractions of potential clinical relevance and a patient-oriented diagnosis of the potential molecular causes for individual dyslipidemia.

  16. Chemogenomics: a discipline at the crossroad of high throughput technologies, biomarker research, combinatorial chemistry, genomics, cheminformatics, bioinformatics and artificial intelligence.

    Science.gov (United States)

    Maréchal, Eric

    2008-09-01

    Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry

  17. Chem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology data

    OpenAIRE

    Wang Huijun; Jiao Dazhi; Dong Xiao; Chen Bin; Zhu Qian; Ding Ying; Wild David J

    2010-01-01

    Abstract Background Recently there has been an explosion of new data sources about genes, proteins, genetic variations, chemical compounds, diseases and drugs. Integration of these data sources and the identification of patterns that go across them is of critical interest. Initiatives such as Bio2RDF and LODD have tackled the problem of linking biological data and drug data respectively using RDF. Thus far, the inclusion of chemogenomic and systems chemical biology information that crosses th...

  18. Assist feature printability prediction by 3-D resist profile reconstruction

    Science.gov (United States)

    Zheng, Xin; Huang, Jensheng; Chin, Fook; Kazarian, Aram; Kuo, Chun-Chieh

    2012-06-01

    properties may then be used to optimize the printability vs. efficacy of an SRAF either prior to or during an Optical Proximity Correction (OPC) run. The process models that are used during OPC have never been able to reliably predict which SRAFs will print. This appears to be due to the fact that OPC process models are generally created using data that does not include printed subresolution patterns. An enhancement to compact modeling capability to predict Assist Features (AF) printability is developed and discussed. A hypsometric map representing 3-D resist profile was built by applying a first principle approximation to estimate the "energy loss" from the resist top to bottom. Such a 3-D resist profile is an extrapolation of a well calibrated traditional OPC model without any additional information. Assist features are detected at either top of resist (dark field) or bottom of resist (bright field). Such detection can be done by just extracting top or bottom resist models from our 3-D resist model. There is no measurement of assist features needed when we build AF but it can be included if interested but focusing on resist calibration to account for both exposure dosage and focus change sensitivities. This approach significantly increases resist model's capability for predicting printed SRAF accuracy. And we don't need to calibrate an SRAF model in addition to the OPC model. Without increase in computation time, this compact model can draw assist feature contour with real placement and size at any vertical plane. The result is compared and validated with 3-D rigorous modeling as well as SEM images. Since this method does not change any form of compact modeling, it can be integrated into current MBAF solutions without any additional work.

  19. Chemogenomics driven discovery of endogenous polyketide anti-infective compounds from endosymbiotic Emericella variecolor CLB38 and their RNA secondary structure analysis

    Science.gov (United States)

    Yashavantha Rao, H. C.; Rakshith, Devaraju; Harini, Ballagere Puttaraju; Gurudatt, Doddahosuru Mahadevappa; Satish, Sreedharamurthy

    2017-01-01

    In the postgenomic era, a new strategy for chemical dereplication of polyketide anti-infective drugs requires novel genomics and chromatographic strategies. An endosymbiotic fungal strain CLB38 was isolated from the root tissue of Combretum latifolium Blume (Combretaceae) which was collected from the Western Ghats of India. The isolate CLB38 was then identified as Emericella variecolor by its characteristic stellate ascospores culture morphology and molecular analysis of ITS nuclear rDNA and intervening 5.8S rRNA gene sequence. ITS2 RNA secondary structure modeling clearly distinguished fungal endosymbiont E. variecolor CLB38 with other lifestyles in the same monophyletic clade. Ethyl acetate fraction of CLB38 explored a broad spectrum of antimicrobial activity against multidrug resistant pathogens. Biosynthetic PKS type-I gene and chromatographic approach afford two polyketide antimicrobial compounds which identified as evariquinone and isoindolones derivative emerimidine A. MIC of purified compounds against test microorganisms ranged between 3.12 μg/ml and 12.5 μg/ml. This research highlights the utility of E. variecolor CLB38 as an anticipate source for anti-infective polyketide metabolites evariquinone and emerimidine A to combat multidrug resistant microorganisms. Here we demonstrates a chemogenomics strategy via the feasibility of PKS type-I gene and chromatographic approach as a proficient method for the rapid prediction and discovery of new polyketides compounds from fungal endosymbionts. PMID:28245269

  20. Urine Metabolite Profiles Predictive of Human Kidney Allograft Status.

    Science.gov (United States)

    Suhre, Karsten; Schwartz, Joseph E; Sharma, Vijay K; Chen, Qiuying; Lee, John R; Muthukumar, Thangamani; Dadhania, Darshana M; Ding, Ruchuang; Ikle, David N; Bridges, Nancy D; Williams, Nikki M; Kastenmüller, Gabi; Karoly, Edward D; Mohney, Robert P; Abecassis, Michael; Friedewald, John; Knechtle, Stuart J; Becker, Yolanda T; Samstein, Benjamin; Shaked, Abraham; Gross, Steven S; Suthanthiran, Manikkam

    2016-02-01

    Noninvasive diagnosis and prognostication of acute cellular rejection in the kidney allograft may help realize the full benefits of kidney transplantation. To investigate whether urine metabolites predict kidney allograft status, we determined levels of 749 metabolites in 1516 urine samples from 241 kidney graft recipients enrolled in the prospective multicenter Clinical Trials in Organ Transplantation-04 study. A metabolite signature of the ratio of 3-sialyllactose to xanthosine in biopsy specimen-matched urine supernatants best discriminated acute cellular rejection biopsy specimens from specimens without rejection. For clinical application, we developed a high-throughput mass spectrometry-based assay that enabled absolute and rapid quantification of the 3-sialyllactose-to-xanthosine ratio in urine samples. A composite signature of ratios of 3-sialyllactose to xanthosine and quinolinate to X-16397 and our previously reported urinary cell mRNA signature of 18S ribosomal RNA, CD3ε mRNA, and interferon-inducible protein-10 mRNA outperformed the metabolite signatures and the mRNA signature. The area under the receiver operating characteristics curve for the composite metabolite-mRNA signature was 0.93, and the signature was diagnostic of acute cellular rejection with a specificity of 84% and a sensitivity of 90%. The composite signature, developed using solely biopsy specimen-matched urine samples, predicted future acute cellular rejection when applied to pristine samples taken days to weeks before biopsy. We conclude that metabolite profiling of urine offers a noninvasive means of diagnosing and prognosticating acute cellular rejection in the human kidney allograft, and that the combined metabolite and mRNA signature is diagnostic and prognostic of acute cellular rejection with very high accuracy.

  1. Prediction of transposable element derived enhancers using chromatin modification profiles.

    Directory of Open Access Journals (Sweden)

    Ahsan Huda

    Full Text Available Experimentally characterized enhancer regions have previously been shown to display specific patterns of enrichment for several different histone modifications. We modelled these enhancer chromatin profiles in the human genome and used them to guide the search for novel enhancers derived from transposable element (TE sequences. To do this, a computational approach was taken to analyze the genome-wide histone modification landscape characterized by the ENCODE project in two human hematopoietic cell types, GM12878 and K562. We predicted the locations of 2,107 and 1,448 TE-derived enhancers in the GM12878 and K562 cell lines respectively. A vast majority of these putative enhancers are unique to each cell line; only 3.5% of the TE-derived enhancers are shared between the two. We evaluated the functional effect of TE-derived enhancers by associating them with the cell-type specific expression of nearby genes, and found that the number of TE-derived enhancers is strongly positively correlated with the expression of nearby genes in each cell line. Furthermore, genes that are differentially expressed between the two cell lines also possess a divergent number of TE-derived enhancers in their vicinity. As such, genes that are up-regulated in the GM12878 cell line and down-regulated in K562 have significantly more TE-derived enhancers in their vicinity in the GM12878 cell line and vice versa. These data indicate that human TE-derived sequences are likely to be involved in regulating cell-type specific gene expression on a broad scale and suggest that the enhancer activity of TE-derived sequences is mediated by epigenetic regulatory mechanisms.

  2. A comparison on radar range profiles between in-flight measurements and RCS-predictions

    NARCIS (Netherlands)

    Heiden, R. van der; Ewijk, L.J. van; Groen, F.C.A.

    1998-01-01

    The validation of Radar Cross Section (RCS) prediction techniques against real measurements is crucial to acquire confidence in predictions when measurements are nut available. In this paper we present the results of a comparison on one-dimensional signatures, i.e. radar range profiles. The profiles

  3. Psoriasis prediction from genome-wide SNP profiles

    Directory of Open Access Journals (Sweden)

    Fang Xiangzhong

    2011-01-01

    Full Text Available Abstract Background With the availability of large-scale genome-wide association study (GWAS data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs to predict psoriasis from searching GWAS data. Methods Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB method was compared with classical linear discriminant analysis(LDA for classification performance. Results The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698, while only 0.520(95% CI: 0.472-0.524 was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study. Conclusions The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.

  4. Chemogenomic identification of Ref-1/AP-1 as a therapeutic target for asthma.

    Science.gov (United States)

    Nguyen, Cu; Teo, Jia-Ling; Matsuda, Akihisa; Eguchi, Masakatsu; Chi, Emil Y; Henderson, William R; Kahn, Michael

    2003-02-04

    Asthma is characterized by an oxidantantioxidant imbalance in the lungs leading to activation of redox-sensitive transcription factors, nuclear factor kappaB (NF-kappaB), and activator protein-1 (AP-1). To develop therapeutic strategies for asthma, we used a chemogenomics approach to screen for small molecule inhibitor(s) of AP-1 transcription. We developed a beta-strand mimetic template that acts as a reversible inhibitor (pseudosubstrate) of redox proteins. This template incorporates an enedione moiety to trap reactive cysteine nucleophiles in the active sites of redox proteins. Specificity for individual redox factors was achieved through variations in X and Y functionality by using a combinatorial library approach. A limited array (2 x 6) was constructed where X was either NHCH(3) or NHCH(2) Ph and Y was methyl, phenyl, m-cyanophenyl, m-nitrophenyl, m-acetylaniline, or m-methylbenzoate. These analogs were evaluated for their ability to inhibit transcription in transiently transfected human lung epithelial A549 cells from either an AP-1 or NF-kappaB reporter. A small-molecule inhibitor, PNRI-299, was identified that selectively inhibited AP-1 transcription (IC(50) of 20 microM) without affecting NF-kappaB transcription (up to 200 microM) or thioredoxin (up to 200 microM). The molecular target of PNRI-299 was determined to be the oxidoreductase, redox effector factor-1 by an affinity chromatography approach. The selective redox effector factor-1 inhibitor, PNRI-299, significantly reduced airway eosinophil infiltration, mucus hypersecretion, edema, and IL-4 levels in a mouse asthma model. These data validate AP-1 as an important therapeutic target in allergic airway inflammation.

  5. Chem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology data

    Directory of Open Access Journals (Sweden)

    Wang Huijun

    2010-05-01

    Full Text Available Abstract Background Recently there has been an explosion of new data sources about genes, proteins, genetic variations, chemical compounds, diseases and drugs. Integration of these data sources and the identification of patterns that go across them is of critical interest. Initiatives such as Bio2RDF and LODD have tackled the problem of linking biological data and drug data respectively using RDF. Thus far, the inclusion of chemogenomic and systems chemical biology information that crosses the domains of chemistry and biology has been very limited Results We have created a single repository called Chem2Bio2RDF by aggregating data from multiple chemogenomics repositories that is cross-linked into Bio2RDF and LODD. We have also created a linked-path generation tool to facilitate SPARQL query generation, and have created extended SPARQL functions to address specific chemical/biological search needs. We demonstrate the utility of Chem2Bio2RDF in investigating polypharmacology, identification of potential multiple pathway inhibitors, and the association of pathways with adverse drug reactions. Conclusions We have created a new semantic systems chemical biology resource, and have demonstrated its potential usefulness in specific examples of polypharmacology, multiple pathway inhibition and adverse drug reaction - pathway mapping. We have also demonstrated the usefulness of extending SPARQL with cheminformatics and bioinformatics functionality.

  6. Influence of mRNA decay rates on the computational prediction of transcription rate profiles from gene expression profiles

    Indian Academy of Sciences (India)

    Chi-Fang Chin; Arthur Chun-Chieh Shih; Kuo-Chin Fan

    2007-12-01

    The abundance of an mRNA species depends not only on the transcription rate at which it is produced, but also on its decay rate, which determines how quickly it is degraded. Both transcription rate and decay rate are important factors in regulating gene expression. With the advance of the age of genomics, there are a considerable number of gene expression datasets, in which the expression profiles of tens of thousands of genes are often non-uniformly sampled. Recently, numerous studies have proposed to infer the regulatory networks from expression profiles. Nevertheless, how mRNA decay rates affect the computational prediction of transcription rate profiles from expression profiles has not been well studied. To understand the influences, we present a systematic method based on a gene dynamic regulation model by taking mRNA decay rates, expression profiles and transcription profiles into account. Generally speaking, an expression profile can be regarded as a representation of a biological condition. The rationale behind the concept is that the biological condition is reflected in the changing of gene expression profile. Basically, the biological condition is either associated to the cell cycle or associated to the environmental stresses. The expression profiles of genes that belong to the former, so-called cell cycle data, are characterized by periodicity, whereas the expression profiles of genes that belong to the latter, so-called condition-specific data, are characterized by a steep change after a specific time without periodicity. In this paper, we examine the systematic method on the simulated expression data as well as the real expression data including yeast cell cycle data and condition-specific data (glucose-limitation data). The results indicate that mRNA decay rates do not significantly influence the computational prediction of transcription-rate profiles for cell cycle data. On the contrary, the magnitudes and shapes of transcription-rate profiles for

  7. Early pharmaceutical profiling to predict oral drug absorption

    DEFF Research Database (Denmark)

    Bergström, Christel A S; Holm, René; Jørgensen, Søren Astrup

    2014-01-01

    of the pharmaceutical profiling methods available, with focus on in silico and in vitro models typically used to forecast active pharmaceutical ingredient's (APIs) in vivo performance after oral administration. An overview of the composition of human, animal and simulated gastrointestinal (GI) fluids is provided...... are discussed in detail and future demands on pharmaceutical profiling are identified. It is expected that innovative computational and experimental methods that better describe molecular processes involved in vivo during dissolution and absorption of APIs will be developed in the OrBiTo. These methods...... will provide early insights into successful pathways (medicinal chemistry or formulation strategy) and are anticipated to increase the number of new APIs with good oral absorption being discovered....

  8. Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling

    NARCIS (Netherlands)

    R.G.W. Verhaak (Roel); B.J. Wouters (Bas); C.A.J. Erpelinck (Claudia); S. Abbas (Saman); H.B. Beverloo (Berna); S. Lugthart (Sanne); B. Löwenberg (Bob); H.R. Delwel (Ruud); P.J.M. Valk (Peter)

    2009-01-01

    textabstractWe examined the gene expression profiles of two independent cohorts of patients with acute myeloid leukemia [n=247 and n=214 (younger than or equal to 60 years)] to study the applicability of gene expression profiling as a single assay in prediction of acute myeloid leukemia-specific mol

  9. On the influence of the gas velocity profile on the theoretically predicted opposed flow flame spread

    Energy Technology Data Exchange (ETDEWEB)

    DiBlasi, C.; Crescitelli, S.; Russo, G. (Dipartimento di Ingegneria Chimica, Universita de Napoli, Piazzale v Tecchio, Naples (IT)); FernandezPello, A.C. (California Univ., Berkeley, CA (USA). Dept. of Mechanical Engineering)

    1989-01-01

    A numerical analysis is presented of the effect on the predicted flame spread rate and flame structure of a prescribed gas velocity field opposing the direction of flame propagation. The calculations are made for two limiting cases of oxygen mass fraction and with Oseen and Hagen-Poiseuille velocity profiles. It is shown that the selected gas velocity profile has a significant influence on the flame spread predictions.

  10. A Lifetime Prediction Method for LEDs Considering Real Mission Profiles

    OpenAIRE

    Qu, Xiaohui; Wang, Huai; Zhan, Xiaoqing; Blaabjerg, Frede; Chung, Henry Shu-Hung

    2017-01-01

    The Light-Emitting Diode (LED) has become a very promising alternative lighting source with the advantages of longer lifetime and higher efficiency than traditional ones. The lifetime prediction of LEDs is important to guide the LED system designers to fulfill the design specifications and to benchmark the cost-competitiveness of different lighting technologies. However, the existing lifetime data released by LED manufacturers or standard organizations are usually applicable only for some spe...

  11. Compact Web browsing profiles for click-through rate prediction

    DEFF Research Database (Denmark)

    Fruergaard, Bjarne Ørum; Hansen, Lars Kai

    2014-01-01

    with varying degrees of sparsity in the representations. The decompositions that we consider are SVD, NMF, and IRM. To quantify the utility, we measure the performances of these representations when used as features in a sparse logistic regression model for click-through rate prediction. We recommend the IRM...... bipartite clustering features as they provide the most compact representation of browsing patterns and yield the best performance....

  12. Predicting lower third molar eruption on panoramic radiographs after cephalometric comparison of profile and panoramic radiographs

    DEFF Research Database (Denmark)

    Begtrup, Anders; Grønastøð, Halldis Á; Christensen, Ib Jarle;

    2012-01-01

    Previous studies have suggested methods for predicting third molar tooth eruption radiographically. Still, this prediction is associated with uncertainty. The aim of the present study was to elucidate the association between cephalometric measurements on profile and panoramic radiographs and to f...

  13. Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling.

    Science.gov (United States)

    Verhaak, Roel G W; Wouters, Bas J; Erpelinck, Claudia A J; Abbas, Saman; Beverloo, H Berna; Lugthart, Sanne; Löwenberg, Bob; Delwel, Ruud; Valk, Peter J M

    2009-01-01

    We examined the gene expression profiles of two independent cohorts of patients with acute myeloid leukemia [n=247 and n=214 (younger than or equal to 60 years)] to study the applicability of gene expression profiling as a single assay in prediction of acute myeloid leukemia-specific molecular subtypes. The favorable cytogenetic acute myeloid leukemia subtypes, i.e., acute myeloid leukemia with t(8;21), t(15;17) or inv(16), were predicted with maximum accuracy (positive and negative predictive value: 100%). Mutations in NPM1 and CEBPA were predicted less accurately (positive predictive value: 66% and 100%, and negative predictive value: 99% and 97% respectively). Various other characteristic molecular acute myeloid leukemia subtypes, i.e., mutant FLT3 and RAS, abnormalities involving 11q23, -5/5q-, -7/7q-, abnormalities involving 3q (abn3q) and t(9;22), could not be correctly predicted using gene expression profiling. In conclusion, gene expression profiling allows accurate prediction of certain acute myeloid leukemia subtypes, e.g. those characterized by expression of chimeric transcription factors. However, detection of mutations affecting signaling molecules and numerical abnormalities still requires alternative molecular methods.

  14. Profiling - Predicting Long-Term Unemployment at the Individual Level

    Directory of Open Access Journals (Sweden)

    Tomáš Soukup

    2011-03-01

    Full Text Available Labour market policy encourages both the preventive and proactive approaches in order to avoid negative impacts. Unfortunately, a large number of evaluation studies show that active intervention is helpful only if it is targeted according to the prevailing situation and needs of claimants. The first step in the targeting process is to determine in advance which claimant has a significant probability of becoming long-term unemployed and just how high the risk is.
    This paper deals with the predicting of long-term unemployment at the individual level. In contrast with research carried out elsewhere, the paper stresses the theory behind the statistical model. As far as the Czech Republic is concerned it has been shown that a model computed using only data from the official unemployment register is correct in 78% of cases, i.e. 20 percentage points more than the result obtained by means of the constant or risk group approaches.

  15. Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction.

    Science.gov (United States)

    Chu, Wei; Ghahramani, Zoubin; Podtelezhnikov, Alexei; Wild, David L

    2006-01-01

    In this paper, we develop a segmental semi-Markov model (SSMM) for protein secondary structure prediction which incorporates multiple sequence alignment profiles with the purpose of improving the predictive performance. The segmental model is a generalization of the hidden Markov model where a hidden state generates segments of various length and secondary structure type. A novel parameterized model is proposed for the likelihood function that explicitly represents multiple sequence alignment profiles to capture the segmental conformation. Numerical results on benchmark data sets show that incorporating the profiles results in substantial improvements and the generalization performance is promising. By incorporating the information from long range interactions in beta-sheets, this model is also capable of carrying out inference on contact maps. This is an important advantage of probabilistic generative models over the traditional discriminative approach to protein secondary structure prediction. The Web server of our algorithm and supplementary materials are available at http://public.kgi.edu/-wild/bsm.html.

  16. Predicting lower third molar eruption on panoramic radiographs after cephalometric comparison of profile and panoramic radiographs.

    Science.gov (United States)

    Begtrup, Anders; Grønastøð, Halldis Á; Christensen, Ib Jarle; Kjær, Inger

    2013-08-01

    Previous studies have suggested methods for predicting third molar tooth eruption radiographically. Still, this prediction is associated with uncertainty. The aim of the present study was to elucidate the association between cephalometric measurements on profile and panoramic radiographs and to find a simple and reliable method for predicting the eruption of the mandibular third molar by measurements on panoramic radiographs. The material consisted of profile and panoramic radiographs, taken before orthodontic treatment, of 30 males and 23 females (median age 22, range 18-48 years), with no known diseases. Cephalometric measurements on panoramic and profile radiographs were performed and compared, i.e. the size of the gonial angle and sagittal distance from the alveolar margin between the mandibular central incisors to the anterior border of the mandibular ramus. Furthermore, the mesiodistal width of the second molar was measured. Statistical methods included analysis of method error. The probability of eruption was modelled using logistic regression analysis. Correlation was observed between all measurements on profile and panoramic radiographs. The skeletal variable expressing the length from the ramus to the incisors (olr-id) showed a statistically significant correlation. By combining this length with the mesiodistal width of the lower second molar, the prediction of eruption of the lower third molar was strengthened. A new formula for calculating the probability of eruption of the mandibular third molar was made and a graph constructed for easy assessment. In conclusion, a simple method for predicting the eruption of the third molar is presented.

  17. Comparison of gene sets for expression profiling: prediction of metastasis from low-malignant breast cancer

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja;

    2007-01-01

    -six tumors from low-risk patients and 34 low-malignant T2 tumors from patients with slightly higher risk have been examined by genome-wide gene expression analysis. Nine prognostic gene sets were tested in this data set. RESULTS: A 32-gene profile (HUMAC32) that accurately predicts metastasis has previously...... sets, mainly developed in high-risk cancers, predict metastasis from low-malignant cancer....

  18. A biomarker profile for predicting efficacy of cisplatin-vinorelbine therapy in malignant pleural mesothelioma

    DEFF Research Database (Denmark)

    Zimling, Zarah Glad; Sørensen, Jens Benn; Gerds, Thomas Alexander;

    2012-01-01

    Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated with cispl...... with cisplatin-vinorelbine. We further explored the possibility of combining markers into a treatment-response profile to increase the predictive power....

  19. Prediction of insecticidal activity of Bacillus thuringiensis strains by polymerase chain reaction product profiles.

    OpenAIRE

    Carozzi, N B; Kramer, V C; Warren, G W; Evola, S; Koziel, M G

    1991-01-01

    A rapid analysis of Bacillus thuringiensis strains predictive of insecticidal activity was established by using polymerase chain reaction (PCR) technology. Primers specific to regions of high homology within genes encoding three major classes of B. thuringiensis crystal proteins were used to generate a PCR product profile characteristic of each insecticidal class. Predictions of insecticidal activity were made on the basis of the electrophoretic patterns of the PCR products. Included in the s...

  20. Profiling healthy eaters: determining factors that predict healthy eating practices among Dutch adults

    NARCIS (Netherlands)

    Swan, E.; Bouwman, L.; Hiddink, G.J.; Aarts, N.; Koelen, M.

    2015-01-01

    Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's sa

  1. Chemosensitivity profile assay of circulating cancer cells: prognostic and predictive value in epithelial tumors.

    Science.gov (United States)

    Gazzaniga, Paola; Naso, Giuseppe; Gradilone, Angela; Cortesi, Enrico; Gandini, Orietta; Gianni, Walter; Fabbri, Maria Agnese; Vincenzi, Bruno; di Silverio, Franco; Frati, Luigi; Aglianò, Anna Maria; Cristofanilli, Massimo

    2010-05-15

    The prognostic value associated with the detection of circulating tumor cells (CTCs) in metastatic breast cancer by the CellSearch technology raise additional issues regarding the biological value of this information. We postulated that a drug-resistance profile of CTCs may predict response to chemotherapy in cancer patients and therefore could be used for patient selection. One hundred 5 patients with diagnosis of carcinoma were enrolled in a prospective trial. CTCs were isolated from peripheral blood, and positive samples were evaluated for the expression of a panel of genes involved in anticancer drugs resistance. The drug-resistance profile was correlated with disease-free survival (DFS; patients in adjuvant setting) and time to progression (TTP; metastatic patients) in a 24-months follow-up. Objective response correlation was a secondary end point. Fifty-one percent of patients were found positive for CTCs while all blood samples from healthy donors were negative. The drug-resistance profile correlates with DFS and TTP (p < 0.001 in both). Sensitivity of the test: able to predict treatment response in 98% of patients. Specificity of the test: 100%; no sample from healthy subject was positive for the presence of CTCs. Positive and negative predictive values were found to be 96.5 and 100%, respectively. We identified a drug-resistance profile of CTCs, which is predictive of response to chemotherapy, independent of tumor type and stage of disease. This approach may represent a first step toward the individualization of chemotherapy in cancer patients.

  2. Prediction of Stratified Flow Temperature Profiles in a Fully Insulated Environment

    Directory of Open Access Journals (Sweden)

    Ahmad S. Awad

    2014-07-01

    Full Text Available The aim of the study is to present an analytical model to predict the temperature profiles in thermal stratified environment. Thermal stratification is encountered in many situations. The flow of contaminants and hydrocarbons in environment often get stratified. The prediction of temperature profiles and flow characteristics are essential for HVAC applications, environment and energy management. The temperature profiles in the stratified region are successfully obtained, in terms of flow-operating functions. The analytical model agrees well with the published experimental data as well as the related closed-form solutions, which is helpful for HVAC applications. The model will be further developed and incorporated within a numerical model in order to investigate the flow field characteristics and establish correlations for a wide range of parameters.

  3. Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling

    DEFF Research Database (Denmark)

    Simonsen, Martin; Maetschke, S.R.; Ragan, M.A.

    2012-01-01

    Motivation: Phylogenetic profiling methods can achieve good accuracy in predicting protein–protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly......: We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...

  4. Wear characteristics and prediction of wheel profiles in high-speed trains

    Institute of Scientific and Technical Information of China (English)

    韩鹏; 张卫华; 李艳

    2015-01-01

    Wheel/rail relationship is a fundamental problem of railway system. Wear of wheel profiles has great effect on vehicle performance. Thus, it is important not just for the analysis of wear characteristics but for its prediction. Actual wheel profiles of the high-speed trains on service were measured in the high-speed line and the wear characteristics were analyzed which came to the following results. The wear location was centralized from−15 mm to 25 mm. The maximum wear value appeared at the area of 5 mm from tread center far from wheel flange and it was less than 1.5 mm. Then, wheel wear was fitted to get the polynomial functions on different locations and operation mileages. A binary numerical prediction model was raised to predict wheel wear. The prediction model was proved by vehicle system dynamics and wheel/rail contact geometry. The results show that the prediction model can reflect wear characteristics of measured profiles and vehicle performances.

  5. Predicting disordered regions in proteins using the profiles of amino acid indices

    Science.gov (United States)

    Han, Pengfei; Zhang, Xiuzhen; Feng, Zhi-Ping

    2009-01-01

    Background Intrinsically unstructured or disordered proteins are common and functionally important. Prediction of disordered regions in proteins can provide useful information for understanding protein function and for high-throughput determination of protein structures. Results In this paper, algorithms are presented to predict long and short disordered regions in proteins, namely the long disordered region prediction algorithm DRaai-L and the short disordered region prediction algorithm DRaai-S. These algorithms are developed based on the Random Forest machine learning model and the profiles of amino acid indices representing various physiochemical and biochemical properties of the 20 amino acids. Conclusion Experiments on DisProt3.6 and CASP7 demonstrate that some sets of the amino acid indices have strong association with the ordered and disordered status of residues. Our algorithms based on the profiles of these amino acid indices as input features to predict disordered regions in proteins outperform that based on amino acid composition and reduced amino acid composition, and also outperform many existing algorithms. Our studies suggest that the profiles of amino acid indices combined with the Random Forest learning model is an important complementary method for pinpointing disordered regions in proteins. PMID:19208144

  6. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

    Directory of Open Access Journals (Sweden)

    Liao Li

    2010-10-01

    Full Text Available Abstract Background Protein-protein interaction (PPI plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs, based on domains represented as interaction profile hidden Markov models (ipHMM where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB. Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD. Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure, an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on

  7. Predicting Drug Combination Index and Simulating the Network-Regulation Dynamics by Mathematical Modeling of Drug-Targeted EGFR-ERK Signaling Pathway

    Science.gov (United States)

    Huang, Lu; Jiang, Yuyang; Chen, Yuzong

    2017-01-01

    Synergistic drug combinations enable enhanced therapeutics. Their discovery typically involves the measurement and assessment of drug combination index (CI), which can be facilitated by the development and applications of in-silico CI predictive tools. In this work, we developed and tested the ability of a mathematical model of drug-targeted EGFR-ERK pathway in predicting CIs and in analyzing multiple synergistic drug combinations against observations. Our mathematical model was validated against the literature reported signaling, drug response dynamics, and EGFR-MEK drug combination effect. The predicted CIs and combination therapeutic effects of the EGFR-BRaf, BRaf-MEK, FTI-MEK, and FTI-BRaf inhibitor combinations showed consistent synergism. Our results suggest that existing pathway models may be potentially extended for developing drug-targeted pathway models to predict drug combination CI values, isobolograms, and drug-response surfaces as well as to analyze the dynamics of individual and combinations of drugs. With our model, the efficacy of potential drug combinations can be predicted. Our method complements the developed in-silico methods (e.g. the chemogenomic profile and the statistically-inferenced network models) by predicting drug combination effects from the perspectives of pathway dynamics using experimental or validated molecular kinetic constants, thereby facilitating the collective prediction of drug combination effects in diverse ranges of disease systems.

  8. Longitudinal prediction and concurrent functioning of adolescent girls demonstrating various profiles of dating violence and victimization.

    Science.gov (United States)

    Chiodo, Debbie; Crooks, Claire V; Wolfe, David A; McIsaac, Caroline; Hughes, Ray; Jaffe, Peter G

    2012-08-01

    Adolescent girls are involved in physical dating violence as both perpetrators and victims, and there are negative consequences associated with each of these behaviors. This article used a prospective design with 519 girls dating in grade 9 to predict profiles of dating violence in grade 11 based on relationships with families of origin (child maltreatment experiences, harsh parenting), and peers (harassment, delinquency, relational aggression). In addition, dating violence profiles were compared on numerous indices of adjustment (school connectedness, grades, self-efficacy and community connectedness) and maladjustment (suicide attempts, distress, delinquency, sexual behavior) for descriptive purposes. The most common profile was no dating violence (n = 367) followed by mutual violence (n = 81). Smaller numbers of girls reported victimization or perpetration only (ns = 39 and 32, respectively). Predicting grade 11 dating violence profile membership from grade 9 relationships was limited, although delinquency, parental rejection, and sexual harassment perpetration predicted membership to the mutually violent group, and delinquency predicted the perpetrator-only group. Compared to the non-violent group, the mutually violent girls in grade 11 had lower grades, poorer self-efficacy, and lower school connectedness and community involvement. Furthermore, they had higher rates of peer aggression and delinquency, were less likely to use condoms and were much more likely to have considered suicide. There were fewer differences among the profiles for girls involved with dating violence. In addition, the victims-only group reported higher rates of sexual intercourse, comparable to the mutually violent group and those involved in nonviolent relationships. Implications for prevention and intervention are highlighted.

  9. Prediction of crank torque and pedal angle profiles during pedaling movements by biomechanical optimization

    DEFF Research Database (Denmark)

    Farahani, Saeed Davoudabadi; Bertucci, William; Andersen, Michael Skipper;

    2015-01-01

    to predict the motion pattern and crank torque was used. An experiment was conducted on a group of eight highly trained male cyclists to compare experimental observations to the simulation results. The proposed performance criterion predicts realistic crank torque profiles and ankle movement patterns.......This paper introduces the inverse-inverse dynamics method for prediction of human movement and applies it to prediction of cycling motions. Inverse-inverse dynamics optimizes a performance criterion by variation of a parameterized movement. First, a musculoskeletal model of cycling is built...... and constraints. The cost function and the constraints typically express performance, comfort, injury risk, fatigue, muscle load, joint forces and other physiological properties derived from the detailed musculoskeletal analysis. A physiology-based cost function that expresses the integral effort over a cycle...

  10. Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence.

    Science.gov (United States)

    Nikoloudis, Dimitris; Pitts, Jim E; Saldanha, José W

    2014-01-01

    The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs) is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP) is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.

  11. Disjoint combinations profiling (DCP: a new method for the prediction of antibody CDR conformation from sequence

    Directory of Open Access Journals (Sweden)

    Dimitris Nikoloudis

    2014-07-01

    Full Text Available The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.

  12. Prediction of metastasis from low-malignant breast cancer by gene expression profiling

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja;

    2007-01-01

    Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...... examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... demonstrated high cross-platform consistency of the classifiers. Higher performance of HUMAC32 was demonstrated among the low-malignant cancers compared with the 70-gene classifier. This suggests that although the metastatic potential to some extend is determined by the same genes in groups of tumors...

  13. Prediction of Clinically Relevant Safety Signals of Nephrotoxicity through Plasma Metabolite Profiling

    Directory of Open Access Journals (Sweden)

    W. B. Mattes

    2013-01-01

    Full Text Available Addressing safety concerns such as drug-induced kidney injury (DIKI early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC. The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound’s well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity, not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

  14. Body Composition Indices and Predicted Cardiovascular Disease Risk Profile among Urban Dwellers in Malaysia

    Directory of Open Access Journals (Sweden)

    Tin Tin Su

    2015-01-01

    Full Text Available Objectives. This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD risk profile in an urban population in Kuala Lumpur, Malaysia. Methods. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Results. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. Conclusions. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

  15. Latent profiles of nonresidential father engagement six years after divorce predict long-term offspring outcomes.

    Science.gov (United States)

    Modecki, Kathryn Lynn; Hagan, Melissa J; Sandler, Irwin; Wolchik, Sharlene A

    2015-01-01

    This study examined profiles of nonresidential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) 6 to 8 years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, 9 years later. Parental divorce occurred during late childhood to early adolescence; indicators of nonresidential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed 9 years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes 9 years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother's remarriage, mother's income, and gender, age, and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems 9 years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long term. Implications of findings for policy and intervention are discussed.

  16. Factors predicting sensory profile of 4 to 18 month old infants

    Directory of Open Access Journals (Sweden)

    Carina Pedrosa

    2015-06-01

    Full Text Available OBJECTIVE: To identify environment factors predicting sensory profile of infants between 4 and 18 months old. METHODS: This cross-sectional study evaluated 97 infants (40 females e 57 males, with a mean age of 1.05±0.32 years with the Test of Sensory Functions in Infants (TSFI and also asked 97 parents and 11 kindergarten teachers of seven daycare centers to answer the Affordances in the Home Environment for Motor Development-Infant Scale (AHEMD-IS. The AHEMD-IS is a questionnaire that characterizes the opportunities in the home environment for infants between 3 and 18 months of age. We tested the association between affordances and the sensory profile of infants. Significant variables were entered into a regression model to determine predictors of sensory profile. RESULTS: The majority of infants (66% had a normal sensory profile and 34% were at risk or deficit. Affordances in the home were classified as adequate and they were good in the studied daycare centers. The results of the regression revealed that only daily hours in daycare center and daycare outside space influenced the sensory profile of infants, in particular the Ocular-Motor Control component. CONCLUSIONS: The sensory profile of infants was between normal and at risk. While the family home offered adequate affordances for motor development, the daycare centers of the infants involved demonstrated a good quantity and quality of affordances. Overall, we conclude that daily hours in the daycare center and daycare outside space were predictors of the sensory profile, particular on Ocular-Motor Control component.

  17. Predicting RNA Secondary Structure Using Profile Stochastic Context-Free Grammars and Phylogenic Analysis

    Institute of Scientific and Technical Information of China (English)

    Xiao-Yong Fang; Zhi-Gang Luo; Zheng-Hua Wang

    2008-01-01

    Stochastic context-free grammars (SCFGs) have been applied to predicting RNA secondary structure. The prediction of RNA secondary structure can be facilitated by incorporating with comparative sequence analysis. However,most of existing SCFG-based methods lack explicit phylogenic analysis of homologous RNA sequences, which is probably the reason why these methods are not ideal in practical application. Hence, we present a new SCFG-based method by integrating phylogenic analysis with the newly defined profile SCFG. The method can be summarized as: 1) we define a new profile SCFG, M, to depict consensus secondary structure of multiple RNA sequence alignment; 2) we introduce two distinct hidden Markov models, λ and λ', to perform phylogenic analysis of homologous RNA sequences. Here, λ is for non-structural regions of the sequence and λ' is for structural regions of the sequence; 3) we mergeλ and λ' in to M todevise a combined model for prediction of RNA secondary structure. We tested our method on data sets constructed from the Rfam database. The sensitivity and specificity of our method are more accurate than those of the predictions by Pfold.

  18. Classification of Phylogenetic Profiles for Protein Function Prediction: An SVM Approach

    Science.gov (United States)

    Kotaru, Appala Raju; Joshi, Ramesh C.

    Predicting the function of an uncharacterized protein is a major challenge in post-genomic era due to problems complexity and scale. Having knowledge of protein function is a crucial link in the development of new drugs, better crops, and even the development of biochemicals such as biofuels. Recently numerous high-throughput experimental procedures have been invented to investigate the mechanisms leading to the accomplishment of a protein’s function and Phylogenetic profile is one of them. Phylogenetic profile is a way of representing a protein which encodes evolutionary history of proteins. In this paper we proposed a method for classification of phylogenetic profiles using supervised machine learning method, support vector machine classification along with radial basis function as kernel for identifying functionally linked proteins. We experimentally evaluated the performance of the classifier with the linear kernel, polynomial kernel and compared the results with the existing tree kernel. In our study we have used proteins of the budding yeast saccharomyces cerevisiae genome. We generated the phylogenetic profiles of 2465 yeast genes and for our study we used the functional annotations that are available in the MIPS database. Our experiments show that the performance of the radial basis kernel is similar to polynomial kernel is some functional classes together are better than linear, tree kernel and over all radial basis kernel outperformed the polynomial kernel, linear kernel and tree kernel. In analyzing these results we show that it will be feasible to make use of SVM classifier with radial basis function as kernel to predict the gene functionality using phylogenetic profiles.

  19. Widely predicting specific protein functions based on protein-protein interaction data and gene expression profile

    Institute of Scientific and Technical Information of China (English)

    GAO Lei; LI Xia; GUO Zheng; ZHU MingZhu; LI YanHui; RAO ShaoQi

    2007-01-01

    GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interaction data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automatically selects the most appropriate functional classes as specific as possible during the learning process, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to "biology process" by three measures particularly designed for functional classes organized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.

  20. Widely predicting specific protein functions based on protein-protein interaction data and gene expression profile

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interac-tion data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automati-cally selects the most appropriate functional classes as specific as possible during the learning proc-ess, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to “biology process” by three measures particularly designed for functional classes organ-ized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.

  1. SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

    Science.gov (United States)

    Suresh, V; Parthasarathy, S

    2014-01-01

    We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

  2. A new metric of inclusive fitness predicts the human mortality profile.

    Directory of Open Access Journals (Sweden)

    Saul J Newman

    Full Text Available Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.

  3. ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

    Science.gov (United States)

    Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

    2016-06-20

    Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

  4. Factors influencing the predictability of soft tissue profile changes following mandibular setback surgery.

    Science.gov (United States)

    Mobarak, K A; Krogstad, O; Espeland, L; Lyberg, T

    2001-06-01

    The objective of this cephalometric study was to assess long-term changes in the soft tissue profile following mandibular setback surgery and investigate the presence of factors that may influence the soft tissue response to skeletal repositioning. The subjects enrolled were 80 consecutive mandibular prognathism patients operated with bilateral sagittal split osteotomy and rigid fixation. Lateral cephalograms were taken at 6 occasions: immediate presurgical, immediate postsurgical, 2 and 6 months postsurgical, and 1 and 3 years postsurgical. The subjects were grouped according to gender and magnitude of setback. Ratios of soft tissue to hard tissue movements were calculated for the subgroups. Females generally demonstrated greater ratios than males with a statistically significant difference for the upper lip and chin (P < .05). Postsurgical alterations in the profiles were more predictable in patients with larger setbacks compared to patients with smaller ones. Skeletal relapse had a profound influence on long-term profile changes. Based on these findings, it is proposed that the database used in prediction software be adjusted to account for such factors in an attempt to improve the accuracy of computerized treatment simulations.

  5. Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment-based local and energy-based nonlocal profiles.

    Science.gov (United States)

    Li, Zhixiu; Yang, Yuedong; Faraggi, Eshel; Zhan, Jian; Zhou, Yaoqi

    2014-10-01

    Locating sequences compatible with a protein structural fold is the well-known inverse protein-folding problem. While significant progress has been made, the success rate of protein design remains low. As a result, a library of designed sequences or profile of sequences is currently employed for guiding experimental screening or directed evolution. Sequence profiles can be computationally predicted by iterative mutations of a random sequence to produce energy-optimized sequences, or by combining sequences of structurally similar fragments in a template library. The latter approach is computationally more efficient but yields less accurate profiles than the former because of lacking tertiary structural information. Here we present a method called SPIN that predicts Sequence Profiles by Integrated Neural network based on fragment-derived sequence profiles and structure-derived energy profiles. SPIN improves over the fragment-derived profile by 6.7% (from 23.6 to 30.3%) in sequence identity between predicted and wild-type sequences. The method also reduces the number of residues in low complex regions by 15.7% and has a significantly better balance of hydrophilic and hydrophobic residues at protein surface. The accuracy of sequence profiles obtained is comparable to those generated from the protein design program RosettaDesign 3.5. This highly efficient method for predicting sequence profiles from structures will be useful as a single-body scoring term for improving scoring functions used in protein design and fold recognition. It also complements protein design programs in guiding experimental design of the sequence library for screening and directed evolution of designed sequences. The SPIN server is available at http://sparks-lab.org.

  6. Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake.

    Science.gov (United States)

    Mimura, Natsuki; Isogai, Atsuko; Iwashita, Kazuhiro; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-10-01

    Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake.

  7. Model Predictive Control with Integral Action for Current Density Profile Tracking in NSTX-U

    Science.gov (United States)

    Ilhan, Z. O.; Wehner, W. P.; Schuster, E.; Boyer, M. D.

    2016-10-01

    Active control of the toroidal current density profile may play a critical role in non-inductively sustained long-pulse, high-beta scenarios in a spherical torus (ST) configuration, which is among the missions of the NSTX-U facility. In this work, a previously developed physics-based control-oriented model is embedded in a feedback control scheme based on a model predictive control (MPC) strategy to track a desired current density profile evolution specified indirectly by a desired rotational transform profile. An integrator is embedded into the standard MPC formulation to reject various modeling uncertainties and external disturbances. Neutral beam powers, electron density, and total plasma current are used as actuators. The proposed MPC strategy incorporates various state and actuator constraints directly into the control design process by solving a constrained optimization problem in real-time to determine the optimal actuator requests. The effectiveness of the proposed controller in regulating the current density profile in NSTX-U is demonstrated in closed-loop nonlinear simulations. Supported by the US DOE under DE-AC02-09CH11466.

  8. Cytokine Profiles during Invasive Nontyphoidal Salmonella Disease Predict Outcome in African Children.

    Science.gov (United States)

    Gilchrist, James J; Heath, Jennifer N; Msefula, Chisomo L; Gondwe, Esther N; Naranbhai, Vivek; Mandala, Wilson; MacLennan, Jenny M; Molyneux, Elizabeth M; Graham, Stephen M; Drayson, Mark T; Molyneux, Malcolm E; MacLennan, Calman A

    2016-07-01

    Nontyphoidal Salmonella is a leading cause of sepsis in African children. Cytokine responses are central to the pathophysiology of sepsis and predict sepsis outcome in other settings. In this study, we investigated cytokine responses to invasive nontyphoidal Salmonella (iNTS) disease in Malawian children. We determined serum concentrations of 48 cytokines with multiplexed immunoassays in Malawian children during acute iNTS disease (n = 111) and in convalescence (n = 77). Principal component analysis and logistic regression were used to identify cytokine signatures of acute iNTS disease. We further investigated whether these responses are altered by HIV coinfection or severe malnutrition and whether cytokine responses predict inpatient mortality. Cytokine changes in acute iNTS disease were associated with two distinct cytokine signatures. The first is characterized by increased concentrations of mediators known to be associated with macrophage function, and the second is characterized by raised pro- and anti-inflammatory cytokines typical of responses reported in sepsis secondary to diverse pathogens. These cytokine responses were largely unaltered by either severe malnutrition or HIV coinfection. Children with fatal disease had a distinctive cytokine profile, characterized by raised mediators known to be associated with neutrophil function. In conclusion, cytokine responses to acute iNTS infection in Malawian children are reflective of both the cytokine storm typical of sepsis secondary to diverse pathogens and the intramacrophage replicative niche of NTS. The cytokine profile predictive of fatal disease supports a key role of neutrophils in the pathogenesis of NTS sepsis.

  9. Response-predictive gene expression profiling of glioma progenitor cells in vitro.

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    Sylvia Moeckel

    Full Text Available BACKGROUND: High-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist. METHODS: In this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a to enrich specimens for brain tumor initiating cells and (b to confront cells with a therapeutic agent before expression profiling. RESULTS: As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro. CONCLUSION: For the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

  10. Development of Fuzzy Logic System to Predict the SAW Weldment Shape Profiles

    Institute of Scientific and Technical Information of China (English)

    H.K.Narang; M.M.Mahapatra; P.K.Jha; P.Biswas

    2012-01-01

    A fuzzy model was presented to predict the weldment shape profile of submerged arc welds (SAW)including the shape of heat affected zone (HAZ).The SAW bead-on-plates were welded by following a full factorial design matrix.The design marx consisted of three levels of input welding process parameters.The welds were cross-sectioned and etched,and the zones were measured.A mapping technique was used to measure the various segments of the weld zones.These mapped zones were used to build a fuzzy logic model.The membership functions of the fuzzy model were chosen for the accurate prediction of the weld zone.The fuzzy model was further tested for a set of test case data.The weld zone predicted by the fuzzy logic model was compared with the experimentally obtained shape profiles and close agreement between the two was noted.The mapping technique developed for the weld zones and the fuzzy logic model can be used for on-line control of the SAW process.From the SAW fuzzy logic model an estimation of the fusion and HAZ can also be developed.

  11. Predicting suspended sand concentration profiles on a macro-tidal beach

    Science.gov (United States)

    Vincent, C. E.; Osborne, P. D.

    1995-11-01

    Suspended sand concentration profiles were measured using acoustic backscatter on a macro-tidal beach at Whitsand Bay, Cornwall, U.K. over a period of 9 days when wave heights were generally between 0.75 m and 0.25 m and wave periods from 5 to 7 s. Average profiles over periods of 6 or 14 min were dominantly of the vortex type, reflecting the importance of steep bedforms in maintaining the suspended sand profile. Bedform dimensions spanned the range between those occurring under regular laboratory waves and those observed under field conditions [ Nielsen, 1981 ( Journal of Geophysical Research, 86, 6467-6472)]. The concentration profiles can be defined by a mixing height zh and a near-bed concentration C0, in this case the concentration at 2 cm above the sea bed. There was considerable variability in zh resulting from the irregular spacing of the bedforms [Osborne and Vincent, 1994 ( Marine Geology, 115, 207-226)], but zh showed a significant dependence on the bed friction defined through the Shields number θ' max based on the skin friction. The variation in the near bed concentration was observed to be only weakly dependent on the excess skin friction at the bed, supporting earlier observations that the resuspension parameter γ 0 [ Smith and McLean, 1977 (in: Bottom turbulence, Elsevier, New York, pp. 123-152)] decreased rapidly as the excess skin friction increased. We conclude that a mixing height given by zh = 2.2 exp (3.05θ' max) and a reference concentration at 2 cm defined using γ 0 = 5.25 × 10 -6 (θ' max) -1.64 was appropriate to predict the mean vertical suspension profile on this macro-tidal beach for a wide range of low wave conditions.

  12. Prediction of pharmacological and xenobiotic responses to drugs based on time course gene expression profiles.

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    Tao Huang

    Full Text Available More and more people are concerned by the risk of unexpected side effects observed in the later steps of the development of new drugs, either in late clinical development or after marketing approval. In order to reduce the risk of the side effects, it is important to look out for the possible xenobiotic responses at an early stage. We attempt such an effort through a prediction by assuming that similarities in microarray profiles indicate shared mechanisms of action and/or toxicological responses among the chemicals being compared. A large time course microarray database derived from livers of compound-treated rats with thirty-four distinct pharmacological and toxicological responses were studied. The mRMR (Minimum-Redundancy-Maximum-Relevance method and IFS (Incremental Feature Selection were used to select a compact feature set (141 features for the reduction of feature dimension and improvement of prediction performance. With these 141 features, the Leave-one-out cross-validation prediction accuracy of first order response using NNA (Nearest Neighbor Algorithm was 63.9%. Our method can be used for pharmacological and xenobiotic responses prediction of new compounds and accelerate drug development.

  13. Soft tissue profile changes following mandibular advancement surgery: predictability and long-term outcome.

    Science.gov (United States)

    Mobarak, K A; Espeland, L; Krogstad, O; Lyberg, T

    2001-04-01

    The objectives of this cephalometric study were to assess long-term changes in the soft tissue profile following mandibular advancement surgery and to investigate the relationship between soft tissue and hard tissue movements. The sample consisted of 61 patients treated consecutively for mandibular retrognathism with orthodontic therapy combined with bilateral sagittal split osteotomy and rigid fixation. Lateral cephalograms were taken on 6 occasions: immediately before surgery, immediately after surgery, 2 and 6 months after surgery, and 1 and 3 years after surgery. Postsurgical changes in the upper and the lower lips and the mentolabial fold were more pronounced among low-angle cases compared with high-angle cases. In accordance with other studies, the soft tissue chin and the mentolabial fold were generally found to follow their underlying skeletal structures in a 1:1 ratio. Because of the strong influence skeletal relapse has on soft tissue profile changes, alternative ratios of soft tissue-to-hard tissue movement that accounted for mean relapse were also generated. It is suggested that if a more realistic long-term prediction of the postsurgical soft tissue profile is desirable, then ratios incorporating mean relapse should be used rather than estimates based on a 1:1 relationship.

  14. Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors.

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    Andrew J Olaharski

    2009-07-01

    Full Text Available Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases, yielding a 113x290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT. Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity. This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing

  15. Multimarker proteomic profiling for the prediction of cardiovascular mortality in patients with chronic heart failure.

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    Gilles Lemesle

    Full Text Available Risk stratification of patients with systolic chronic heart failure (HF is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was performed in a case/control discovery population of 198 patients with systolic HF (left ventricular ejection fraction <45%: 99 patients who died from cardiovascular cause within 3 years and 99 patients alive at 3 years. Proteomic scores predicting cardiovascular death were developed using 3 regression methods: support vector machine, sparse partial least square discriminant analysis, and lasso logistic regression. Forty two ion m/z peaks were differentially intense between cases and controls in the discovery population and were used to develop proteomic scores. In the validation population, score levels were higher in patients who subsequently died within 3 years. Similar areas under the curves (0.66 - 0.68 were observed for the 3 methods. After adjustment on confounders, proteomic scores remained significantly associated with cardiovascular mortality. Use of the proteomic scores allowed a significant improvement in discrimination of HF patients as determined by integrated discrimination improvement and net reclassification improvement indexes. In conclusion, proteomic analysis of plasma proteins may help to improve risk prediction in HF patients.

  16. Antigen profiling analysis of vaccinia virus injected canine tumors: oncolytic virus efficiency predicted by boolean models.

    Science.gov (United States)

    Cecil, Alexander; Gentschev, Ivaylo; Adelfinger, Marion; Nolte, Ingo; Dandekar, Thomas; Szalay, Aladar A

    2014-01-01

    Virotherapy on the basis of oncolytic vaccinia virus (VACV) strains is a novel approach for cancer therapy. In this study we describe for the first time the use of dynamic boolean modeling for tumor growth prediction of vaccinia virus GLV-1h68-injected canine tumors including canine mammary adenoma (ZMTH3), canine mammary carcinoma (MTH52c), canine prostate carcinoma (CT1258), and canine soft tissue sarcoma (STSA-1). Additionally, the STSA-1 xenografted mice were injected with either LIVP 1.1.1 or LIVP 5.1.1 vaccinia virus strains.   Antigen profiling data of the four different vaccinia virus-injected canine tumors were obtained, analyzed and used to calculate differences in the tumor growth signaling network by type and tumor type. Our model combines networks for apoptosis, MAPK, p53, WNT, Hedgehog, TK cell, Interferon, and Interleukin signaling networks. The in silico findings conform with in vivo findings of tumor growth. Boolean modeling describes tumor growth and remission semi-quantitatively with a good fit to the data obtained for all cancer type variants. At the same time it monitors all signaling activities as a basis for treatment planning according to antigen levels. Mitigation and elimination of VACV- susceptible tumor types as well as effects on the non-susceptible type CT1258 are predicted correctly. Thus the combination of Antigen profiling and semi-quantitative modeling optimizes the therapy already before its start.

  17. Predicting multiple ecotoxicological profiles in agrochemical fungicides: a multi-species chemoinformatic approach.

    Science.gov (United States)

    Speck-Planche, Alejandro; Kleandrova, Valeria V; Luan, Feng; Cordeiro, M Natália D S

    2012-06-01

    Agriculture is needed to deal with crop losses caused by biotic stresses like pests. The use of pesticides has played a vital role, contributing to improve crop production and harvest productivity, providing a better crop quality and supply, and consequently contributing with the improvement of the human health. An important group of these pesticides is fungicides. However, the use of these agrochemical fungicides is an important source of contamination, damaging the ecosystems. Several studies have been realized for the assessment of the toxicity in agrochemical fungicides, but the principal limitation is the use of structurally related compounds against usually one indicator species. In order to overcome this problem, we explore the quantitative structure-toxicity relationships (QSTR) in agrochemical fungicides. Here, we developed the first multi-species (ms) chemoinformatic approach for the prediction multiple ecotoxicological profiles of fungicides against 20 indicators species and their classifications in toxic or nontoxic. The ms-QSTR discriminant model was based on substructural descriptors and a heterogeneous database of compounds. The percentages of correct classification were higher than 90% for both, training and prediction series. Also, substructural alerts responsible for the toxicity/no toxicity in fungicides respect all ecotoxicological profiles, were extracted and analyzed.

  18. Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization.

    Science.gov (United States)

    Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P; Simeonov, Anton

    2016-01-26

    Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼ 10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure-activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing.

  19. Prediction of Non-Genotoxic Carcinogenicity Based on Genetic Profiles of Short Term Exposure Assays

    Science.gov (United States)

    Pérez, Luis Orlando; González-José, Rolando; García, Pilar Peral

    2016-01-01

    Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points. PMID:27818731

  20. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

    Science.gov (United States)

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

  1. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

    Science.gov (United States)

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

  2. Dynamic Profiling: Modeling the Dynamics of Inflammation and Predicting Outcomes in Traumatic Brain Injury Patients

    Directory of Open Access Journals (Sweden)

    Gregory Constantine

    2016-11-01

    Full Text Available Inflammation induced by traumatic brain injury (TBI is complex, individual-specific, and associated with morbidity and mortality. We sought to develop dynamic, data-driven, predictive computational models of TBI-induced inflammation based on cerebrospinal fluid (CSF biomarkers. Thirteen inflammatory mediators were determined in serial CSF samples from 27 severe TBI patients. The Glasgow Coma Scale (GCS score quantifies the initial severity of the neurological status of the patient on a numerical scale from 3 to 15. The 6-month Glasgow Outcome Scale (GOS score, the outcome variable, was taken as the variable to express and predict as a function of the other input variables. Data on each subject consisting of ten clinical (one-dimensional variables, such as age, gender, and presence of infection, along with inflammatory biomarker time series were used to generate both multinomial logistic as well as probit models that predict low (poor outcome or high (favorable outcome levels of the GOS score. To determine if CSF inflammation biomarkers could predict TBI outcome, a logistic model for low (≤3; poor neurological outcome or high levels (≥4; favorable neurological outcome of the GOS score involving a full effect of the pro-inflammatory cytokine tumor necrosis factor- and both linear and quadratic effects of the anti-inflammatory cytokine interleukin-10 was obtained. To better stratify patients as their pathology progresses over time, a technique called Dynamic Profiling was developed in which patients were clustered, using the spectral Laplacian and Hartigan's k-means method, into disjoint groups at different stages. Initial clustering was based on GCS score; subsequent clustering was performed based on clinical and demographic information and then further, sequential clustering based on the levels of individual inflammatory mediators over time. These clusters assess the risk of mortality of a new patient after each inflammatory mediator

  3. Development and Validation of Predictive Indices for a Continuous Outcome Using Gene Expression Profiles

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    Yingdong Zhao

    2010-05-01

    Full Text Available There have been relatively few publications using linear regression models to predict a continuous response based on microarray expression profiles. Standard linear regression methods are problematic when the number of predictor variables exceeds the number of cases. We have evaluated three linear regression algorithms that can be used for the prediction of a continuous response based on high dimensional gene expression data. The three algorithms are the least angle regression (LAR, the least absolute shrinkage and selection operator (LASSO, and the averaged linear regression method (ALM. All methods are tested using simulations based on a real gene expression dataset and analyses of two sets of real gene expression data and using an unbiased complete cross validation approach. Our results show that the LASSO algorithm often provides a model with somewhat lower prediction error than the LAR method, but both of them perform more efficiently than the ALM predictor. We have developed a plug-in for BRB-ArrayTools that implements the LAR and the LASSO algorithms with complete cross-validation.

  4. Metabolomics profiling for identification of novel potential markers in early prediction of preeclampsia.

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    Sylwia Kuc

    Full Text Available OBJECTIVE: The first aim was to investigate specific signature patterns of metabolites that are significantly altered in first-trimester serum of women who subsequently developed preeclampsia (PE compared to healthy pregnancies. The second aim of this study was to examine the predictive performance of the selected metabolites for both early onset [EO-PE] and late onset PE [LO-PE]. METHODS: This was a case-control study of maternal serum samples collected between 8+0 and 13+6 weeks of gestation from 167 women who subsequently developed EO-PE n = 68; LO-PE n = 99 and 500 controls with uncomplicated pregnancies. Metabolomics profiling analysis was performed using two methods. One has been optimized to target eicosanoids/oxylipins, which are known inflammation markers and the other targets compounds containing a primary or secondary biogenic amine group. Logistic regression analyses were performed to predict the development of PE using metabolites alone and in combination with first trimester mean arterial pressure (MAP measurements. RESULTS: Two metabolites were significantly different between EO-PE and controls (taurine and asparagine and one in case of LO-PE (glycylglycine. Taurine appeared the most discriminative biomarker and in combination with MAP predicted EO-PE with a detection rate (DR of 55%, at a false-positive rate (FPR of 10%. CONCLUSION: Our findings suggest a potential role of taurine in both PE pathophysiology and first trimester screening for EO-PE.

  5. Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile.

    Science.gov (United States)

    Faraggi, Eshel; Kouza, Maksim; Zhou, Yaoqi; Kloczkowski, Andrzej

    2017-01-01

    A fast accessible surface area (ASA) predictor is presented. In this new approach no residue mutation profiles generated by multiple sequence alignments are used as inputs. Instead, we use only single sequence information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for ASAquick are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org .

  6. Profile Prediction and Fabrication of Wet-Etched Gold Nanostructures for Localized Surface Plasmon Resonance

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    Zhou Xiaodong

    2009-01-01

    Full Text Available Abstract Dispersed nanosphere lithography can be employed to fabricate gold nanostructures for localized surface plasmon resonance, in which the gold film evaporated on the nanospheres is anisotropically dry etched to obtain gold nanostructures. This paper reports that by wet etching of the gold film, various kinds of gold nanostructures can be fabricated in a cost-effective way. The shape of the nanostructures is predicted by profile simulation, and the localized surface plasmon resonance spectrum is observed to be shifting its extinction peak with the etching time. (See supplementary material 1 Electronic supplementary material The online version of this article (doi:10.1007/s11671-009-9486-4 contains supplementary material, which is available to authorized users. Click here for file

  7. Liver protein profiling in chronic hepatitis C: identification of potential predictive markers for interferon therapy outcome.

    Science.gov (United States)

    Perdomo, Ariel Basulto; Ciccosanti, Fabiola; Iacono, Oreste Lo; Angeletti, Claudio; Corazzari, Marco; Daniele, Nicola; Testa, Angela; Pisa, Roberto; Ippolito, Giuseppe; Antonucci, Giorgio; Fimia, Gian Maria; Piacentini, Mauro

    2012-02-01

    The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks.

  8. Professional choice self-efficacy: predicting traits and personality profiles in high school students

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    Rodolfo Augusto Matteo Ambiel

    2016-01-01

    Full Text Available Abstract This study aimed to verify the predictive capacity of the Big Five personality factors related to professional choice self-efficacy, as well as to draw a personality profile of people with diverse self-efficacy levels. There were 308 high school students participating, from three different grades (57.5 % women, from public and private schools, average 26.64 years of age. Students completed two instruments, Escala de Autoeficácia para Escolha Profissional (Professional Choice Self-efficacy Scale and Bateria Fatorial de Personalidade (Factorial Personality Battery. Results were obtained using multiple regression analysis, analysis of variance with repeated measures profile and Cohen’s d to estimate the effect size of differences. Results showed that Extraversion, Agreeableness and Conscientiousness were the main predictors of self-efficacy. Differences from medium to large were observed between extreme groups, and Extraversion and Conscientiousness were the personality factors that better distinguish people with low and high levels of self-efficacy. Theses results partially corroborate with the hypothesis. Results were discussed based on literature and on the practical implications of the results. New studies are proposed.

  9. Profiling healthy eaters. Determining factors that predict healthy eating practices among Dutch adults.

    Science.gov (United States)

    Swan, Emily; Bouwman, Laura; Hiddink, Gerrit Jan; Aarts, Noelle; Koelen, Maria

    2015-06-01

    Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's salutogenic framework for health development to examine a set of factors that predict healthy eating in a cross-sectional study of Dutch adults. Data were analyzed from participants (n = 703) who completed the study's survey in January 2013. Logistic regression analysis was performed to test the association of survey factors on the outcome variable high dietary score. In the multivariate logistic regression model, five factors contributed significantly (p eating, and self-efficacy for healthy eating. Findings complement what is already known of the factors that relate to poor eating practices. This can provide nutrition promotion with a more comprehensive picture of the factors that both support and hinder healthy eating practices. Future research should explore these factors to better understand their origins and mechanisms in relation to healthy eating practices.

  10. Soil profile organic carbon prediction with Visible Near Infrared Reflec-tance spectroscopy based on a national database

    DEFF Research Database (Denmark)

    Deng, Fan; Knadel, Maria; Peng, Yi

    (ele-vation, slope, profile curvature). All the soil profile cores were taken by a 1 m long hydraulic auger with plastic liners inside. A Labspec 5100 equipped with a contact probe was used to acquire spectra at (350-2500 nm) in each 5 cm depth interval. The results show that after the removal......This study focuses on the application of the Danish national soil Visible Near Infrared Re-flectance spectroscopy (NIRs) database for predicting SOC in a field. The Conditioned Latin hypercube sam-pling (cLHS) method was used for the selection of 120 soil profiles based on DualEM21s and DEM data...

  11. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

    Directory of Open Access Journals (Sweden)

    Thomas Efferth

    2012-05-01

    Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.

  12. Metastatic Tissue Proteomic Profiling Predicts 5-Year Outcomes in Patients with Colorectal Liver Metastases

    Directory of Open Access Journals (Sweden)

    Santiago Marfà

    2016-10-01

    Full Text Available Colorectal cancer (CRC is one of the most common cancers in the developed countries, and nearly 70% of patients with CRC develop colorectal liver metastases (CRLMs. During the last decades, several scores have been proposed to predict recurrence after CRLM resection. However, these risk scoring systems do not accurately reflect the prognosis of these patients. Therefore, this investigation was designed to identify a proteomic profile in human hepatic tumor samples to classify patients with CRLM as “mild” or “severe” based on the 5-year survival. The study was performed on 85 CRLM tumor samples. Firstly, to evaluate any distinct tumor proteomic signatures between mild and severe CRLM patients, a training group of 57 CRLM tumor samples was characterized by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, and a classification and regression tree (CART analysis was subsequently performed. Finally, 28 CRLM tumor samples were used to confirm and validate the results obtained. Based on all the protein peaks detected in the training group, the CART analysis was generated, and four peaks were considered to be the most relevant to construct a diagnostic algorithm. Indeed, the multivariate model yielded a sensitivity of 85.7% and a specificity of 86.1%, respectively. In addition, the receiver operating characteristic (ROC curve showed an excellent diagnostic accuracy to discriminate mild from severe CRLM patients (area under the ROC: 0.903. Finally, the validation process yielded a sensitivity and specificity of 68.8% and 83.3%, respectively. We identified a proteomic profile potentially useful to determine the prognosis of CRLM patients based on the 5-year survival.

  13. Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis.

    Science.gov (United States)

    Cuppen, Bart V J; Fu, Junzeng; van Wietmarschen, Herman A; Harms, Amy C; Koval, Slavik; Marijnissen, Anne C A; Peeters, Judith J W; Bijlsma, Johannes W J; Tekstra, Janneke; van Laar, Jacob M; Hankemeier, Thomas; Lafeber, Floris P J G; van der Greef, Jan

    2016-01-01

    In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124). The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI). The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28), erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6), sn1-LPC(15:0), ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01). The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23) and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05). Our study established an accurate prediction model

  14. An atmospheric general circulation model for Pluto with predictions for New Horizons temperature profiles

    Science.gov (United States)

    Zalucha, Angela M.

    2016-06-01

    Results are presented from a 3D Pluto general circulation model (GCM) that includes conductive heating and cooling, non-local thermodynamic equilibrium (non-LTE) heating by methane at 2.3 and 3.3 μm, non-LTE cooling by cooling by methane at 7.6 μm, and LTE CO rotational line cooling. The GCM also includes a treatment of the subsurface temperature and surface-atmosphere mass exchange. An initially 1 m thick layer of surface nitrogen frost was assumed such that it was large enough to act as a large heat sink (compared with the solar heating term) but small enough that the water ice subsurface properties were also significant. Structure was found in all three directions of the 3D wind field (with a maximum magnitude of the order of 10 m s-1 in the horizontal directions and 10-5 microbar s-1 in the vertical direction). Prograde jets were found at several altitudes. The direction of flow over the poles was found to very with altitude. Broad regions of up-welling and down-welling were also found. Predictions of vertical temperature profiles are provided for the Alice and Radio science Experiment instruments on New Horizons, while predictions of light curves are provided for ground-based stellar occultation observations. With this model methane concentrations of 0.2 per cent and 1.0 per cent and 8 and 24 microbar surface pressures are distinguishable. For ground-based stellar occultations, a detectable difference exists between light curves with the different methane concentrations, but not for different initial global mean surface pressures.

  15. Predicting miRNA Targets by Integrating Gene Regulatory Knowledge with Expression Profiles.

    Directory of Open Access Journals (Sweden)

    Weijia Zhang

    Full Text Available microRNAs (miRNAs play crucial roles in post-transcriptional gene regulation of both plants and mammals, and dysfunctions of miRNAs are often associated with tumorigenesis and development through the effects on their target messenger RNAs (mRNAs. Identifying miRNA functions is critical for understanding cancer mechanisms and determining the efficacy of drugs. Computational methods analyzing high-throughput data offer great assistance in understanding the diverse and complex relationships between miRNAs and mRNAs. However, most of the existing methods do not fully utilise the available knowledge in biology to reduce the uncertainty in the modeling process. Therefore it is desirable to develop a method that can seamlessly integrate existing biological knowledge and high-throughput data into the process of discovering miRNA regulation mechanisms.In this article we present an integrative framework, CIDER (Causal miRNA target Discovery with Expression profile and Regulatory knowledge, to predict miRNA targets. CIDER is able to utilise a variety of gene regulation knowledge, including transcriptional and post-transcriptional knowledge, and to exploit gene expression data for the discovery of miRNA-mRNA regulatory relationships. The benefits of our framework is demonstrated by both simulation study and the analysis of the epithelial-to-mesenchymal transition (EMT and the breast cancer (BRCA datasets. Our results reveal that even a limited amount of either Transcription Factor (TF-miRNA or miRNA-mRNA regulatory knowledge improves the performance of miRNA target prediction, and the combination of the two types of knowledge enhances the improvement further. Another useful property of the framework is that its performance increases monotonically with the increase of regulatory knowledge.

  16. Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

    CERN Document Server

    Birkholtz, L -M; Wells, G; Grando, D; Joubert, F; Kasam, V; Zimmermann, M; Ortet, P; Jacq, N; Roy, S; Hoffmann-Apitius, M; Breton, V; Louw, A I; Maréchal, E

    2006-01-01

    The organization and mining of malaria genomic and post-genomic data is highly motivated by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should therefore be as reliable and versatile as possible. In this context, we examined five aspects of the organization and mining of malaria genomic and post-genomic data: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained fro...

  17. Gene expression profiles predictive of outcome and age in infant acute lymphoblastic leukemia: A Children's Oncology Group study

    NARCIS (Netherlands)

    H. Kang; C.S. Wilson (Carla); R. Harvey (R.); I.-M. Chen (I.-Ming); M.H. Murphy (Maurice); S.R. Atlas (Susan); E.J. Bedrick (Edward); M. Devidas (Meenakshi); A.J. Carroll; B.W. Robinson (Blaine); R.W. Stam (Ronald); M.G. Valsecchi (Maria Grazia); R. Pieters (Rob); N.A. Heerema (Nyla); J.M. Hilden (Joanne); C.A. Felix (Carolyn); G.H. Reaman (Gregory); B. Camitta (Bruce); N.J. Winick (Naomi); W.L. Carroll (William); S.D. Dreyer; S.P. Hunger (Stephen); S.F. Willman (Sami )

    2012-01-01

    textabstractGene expression profiling was performed on 97 cases of infant ALL from Children's Oncology Group Trial P9407. Statistical modeling of an outcome predictor revealed 3 genes highly predictive of event-free survival (EFS), beyond age and MLL status: FLT3, IRX2, and TACC2. Low FLT3 expressio

  18. Scalable prediction of compound-protein interactions using minwise hashing.

    Science.gov (United States)

    Tabei, Yasuo; Yamanishi, Yoshihiro

    2013-01-01

    The identification of compound-protein interactions plays key roles in the drug development toward discovery of new drug leads and new therapeutic protein targets. There is therefore a strong incentive to develop new efficient methods for predicting compound-protein interactions on a genome-wide scale. In this paper we develop a novel chemogenomic method to make a scalable prediction of compound-protein interactions from heterogeneous biological data using minwise hashing. The proposed method mainly consists of two steps: 1) construction of new compact fingerprints for compound-protein pairs by an improved minwise hashing algorithm, and 2) application of a sparsity-induced classifier to the compact fingerprints. We test the proposed method on its ability to make a large-scale prediction of compound-protein interactions from compound substructure fingerprints and protein domain fingerprints, and show superior performance of the proposed method compared with the previous chemogenomic methods in terms of prediction accuracy, computational efficiency, and interpretability of the predictive model. All the previously developed methods are not computationally feasible for the full dataset consisting of about 200 millions of compound-protein pairs. The proposed method is expected to be useful for virtual screening of a huge number of compounds against many protein targets.

  19. Urinary MicroRNA Profiling Predicts the Development of Microalbuminuria in Patients with Type 1 Diabetes

    Directory of Open Access Journals (Sweden)

    Christos Argyropoulos

    2015-07-01

    Full Text Available Microalbuminuria provides the earliest clinical marker of diabetic nephropathy among patients with Type 1 diabetes, yet it lacks sensitivity and specificity for early histological manifestations of disease. In recent years microRNAs have emerged as potential mediators in the pathogenesis of diabetes complications, suggesting a possible role in the diagnosis of early stage disease. We used quantiative polymerase chain reaction (qPCR to evaluate the expression profile of 723 unique microRNAs in the normoalbuminuric urine of patients who did not develop nephropathy (n = 10 relative to patients who subsequently developed microalbuminuria (n = 17. Eighteen microRNAs were strongly associated with the subsequent development of microalbuminuria, while 15 microRNAs exhibited gender-related differences in expression. The predicted targets of these microRNAs map to biological pathways known to be involved in the pathogenesis and progression of diabetic renal disease. A microRNA signature (miR-105-3p, miR-1972, miR-28-3p, miR-30b-3p, miR-363-3p, miR-424-5p, miR-486-5p, miR-495, miR-548o-3p and for women miR-192-5p, miR-720 achieved high internal validity (cross-validated misclassification rate of 11.1% for the future development of microalbuminuria in this dataset. Weighting microRNA measurements by their number of kidney-relevant targets improved the prognostic performance of the miRNA signature (cross-validated misclassification rate of 7.4%. Future studies are needed to corroborate these early observations in larger cohorts.

  20. Urinary MicroRNA Profiling Predicts the Development of Microalbuminuria in Patients with Type 1 Diabetes.

    Science.gov (United States)

    Argyropoulos, Christos; Wang, Kai; Bernardo, Jose; Ellis, Demetrius; Orchard, Trevor; Galas, David; Johnson, John P

    2015-07-17

    Microalbuminuria provides the earliest clinical marker of diabetic nephropathy among patients with Type 1 diabetes, yet it lacks sensitivity and specificity for early histological manifestations of disease. In recent years microRNAs have emerged as potential mediators in the pathogenesis of diabetes complications, suggesting a possible role in the diagnosis of early stage disease. We used quantiative polymerase chain reaction (qPCR) to evaluate the expression profile of 723 unique microRNAs in the normoalbuminuric urine of patients who did not develop nephropathy (n = 10) relative to patients who subsequently developed microalbuminuria (n = 17). Eighteen microRNAs were strongly associated with the subsequent development of microalbuminuria, while 15 microRNAs exhibited gender-related differences in expression. The predicted targets of these microRNAs map to biological pathways known to be involved in the pathogenesis and progression of diabetic renal disease. A microRNA signature (miR-105-3p, miR-1972, miR-28-3p, miR-30b-3p, miR-363-3p, miR-424-5p, miR-486-5p, miR-495, miR-548o-3p and for women miR-192-5p, miR-720) achieved high internal validity (cross-validated misclassification rate of 11.1%) for the future development of microalbuminuria in this dataset. Weighting microRNA measurements by their number of kidney-relevant targets improved the prognostic performance of the miRNA signature (cross-validated misclassification rate of 7.4%). Future studies are needed to corroborate these early observations in larger cohorts.

  1. A brain region-specific predictive gene map for autism derived by profiling a reference gene set.

    Directory of Open Access Journals (Sweden)

    Ajay Kumar

    Full Text Available Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84, we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO enrichment analysis which encompassed three main areas: 1 neurogenesis/projection, 2 cell adhesion, and 3 ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe, executive function (prefrontal cortex, and hormone secretion (pituitary. Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research.

  2. Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles.

    Science.gov (United States)

    Brender, Jeffrey R; Zhang, Yang

    2015-10-01

    The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies.

  3. Predicting nicotine dependence profiles among adolescent smokers: the roles of personal and social-environmental factors in a longitudinal framework

    Directory of Open Access Journals (Sweden)

    Kleinjan Marloes

    2012-03-01

    Full Text Available Abstract Background Although several studies have reported that symptoms of nicotine dependence can occur after limited exposure to smoking, the majority of research on nicotine dependence has focused on adult smokers. Insufficient knowledge exists regarding the epidemiology and aetiology of nicotine dependence among adolescent smokers. The objective of the present study is to identify the effects of theoretically driven social and individual predictors of nicotine dependence symptom profiles in a population-based sample of adolescent smokers. Method A longitudinal study among 6,783 adolescents (12 to 14 years old at baseline was conducted. In the first and second year of secondary education, personality traits and exposure to smoking in the social environment were assessed. Two and a half years later, adolescents' smoking status and nicotine dependence symptom profiles were assessed. A total of 796 adolescents were identified as smokers and included in the analyses. Results At follow-up, four distinct dependence symptom profiles were identified: low cravings only, high cravings and withdrawal, high cravings and behavioural dependence, and overall highly dependent. Personality traits of neuroticism and extraversion did not independently predict nicotine dependence profiles, whereas exposure to smoking in the social environment posed a risk for the initial development of nicotine dependence symptoms. However, in combination with environmental exposure to smoking, extraversion and neuroticism increased the risk of developing more severe dependence symptom profiles. Conclusions Nicotine dependence profiles are predicted by interactions between personal and environmental factors. These insights offer important directions for tailoring interventions to prevent the onset and escalation of nicotine dependence. Opportunities for intervention programs that target individuals with a high risk of developing more severe dependence symptom profiles are

  4. Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

    Directory of Open Access Journals (Sweden)

    Banjanovic-Mehmedovic Lejla

    2016-01-01

    Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

  5. Prediction of Process-Induced Distortions in L-Shaped Composite Profiles Using Path-Dependent Constitutive Law

    Science.gov (United States)

    Ding, Anxin; Li, Shuxin; Wang, Jihui; Ni, Aiqing; Sun, Liangliang; Chang, Lei

    2016-10-01

    In this paper, the corner spring-in angles of AS4/8552 L-shaped composite profiles with different thicknesses are predicted using path-dependent constitutive law with the consideration of material properties variation due to phase change during curing. The prediction accuracy mainly depends on the properties in the rubbery and glassy states obtained by homogenization method rather than experimental measurements. Both analytical and finite element (FE) homogenization methods are applied to predict the overall properties of AS4/8552 composite. The effect of fiber volume fraction on the properties is investigated for both rubbery and glassy states using both methods. And the predicted results are compared with experimental measurements for the glassy state. Good agreement is achieved between the predicted results and available experimental data, showing the reliability of the homogenization method. Furthermore, the corner spring-in angles of L-shaped composite profiles are measured experimentally and the reliability of path-dependent constitutive law is validated as well as the properties prediction by FE homogenization method.

  6. Cocaine profiling: Implementation of a predictive model by ATR-FTIR coupled with chemometrics in forensic chemistry.

    Science.gov (United States)

    Materazzi, Stefano; Gregori, Adolfo; Ripani, Luigi; Apriceno, Azzurra; Risoluti, Roberta

    2017-05-01

    In this study, a strategy based on Infrared Spectroscopy with Fourier Transformed and Attenuated Total Reflectance associated with chemometrics (ATR-FTIR) is proposed to identify the chemical "fingerprint" of cocaine samples. To this end, standard mixtures of cocaine and cuttings at differents ratio were investigated in order to develop a multivariate classification model to simultaneously predict the composition of the samples and to obtain a profile of adulteration of cocaine seizures. In addition, the application of a Partial Least Squares (PLS) and Principal Component Regression (PCR) calibration approaches were found to be a useful tool to predict the content of cocaine, caffeine, procaine, lidocaine and phenacetin in drug seizures. The achieved results on real confiscated samples, in cooperation with the Italian Scientific Investigation Department (Carabinieri-RIS) of Rome, allow to consider ATR-FTIR followed to chemometrics as a promising forensic tool in such situations involving profile comparisons and supporting forensic investigations.

  7. Predicting chronic copper and nickel reproductive toxicity to Daphnia pulex-pulicaria from whole-animal metabolic profiles.

    Science.gov (United States)

    Taylor, Nadine S; Kirwan, Jennifer A; Johnson, Craig; Yan, Norman D; Viant, Mark R; Gunn, John M; McGeer, James C

    2016-05-01

    The emergence of omics approaches in environmental research has enhanced our understanding of the mechanisms underlying toxicity; however, extrapolation from molecular effects to whole-organism and population level outcomes remains a considerable challenge. Using environmentally relevant, sublethal, concentrations of two metals (Cu and Ni), both singly and in binary mixtures, we integrated data from traditional chronic, partial life-cycle toxicity testing and metabolomics to generate a statistical model that was predictive of reproductive impairment in a Daphnia pulex-pulicaria hybrid that was isolated from an historically metal-stressed lake. Furthermore, we determined that the metabolic profiles of organisms exposed in a separate acute assay were also predictive of impaired reproduction following metal exposure. Thus we were able to directly associate molecular profiles to a key population response - reproduction, a key step towards improving environmental risk assessment and management.

  8. Predictive molecular profiling in blood of healthy vasospastic individuals: clue to targeted prevention as personalised medicine to effective costs.

    Science.gov (United States)

    Yeghiazaryan, Kristina; Flammer, Josef; Golubnitschaja, Olga

    2010-06-01

    Paradigm change from late interventional approach to predictive diagnostics followed by targeted prevention before manifest pathology, presents innovative concept for advanced healthcare. Preselection of healthy but pathology-predisposed individuals is the primary task in the overall action. Vasospasm is a frequent syndrome defined as an inappropriate constriction or insufficient dilatation in microcirculation. Vasospastic individuals are considered as healthy subpopulation predisposed to several pathologies including neurodegeneration. Clinical observations, subcellular imaging and "gene hunting"-investigations provide evidence for vasospasm as predisposition to glaucoma; development of further related pathologies cannot be excluded. Predictive molecular-profiling in blood can specify individual predisposition for effective prevention.

  9. Method to predict the bandwidth of elution profile under the linear gradient elution in reversed-phase HPLC.

    Science.gov (United States)

    Lee, Ju Weon; Row, Kyung Ho

    2009-01-01

    Solute migration in a chromatographic column is an important consideration when designing batch or continuous chromatographic separation processes. Most design methods for the chromatographic processes are based on the equilibrium theory which concerns only the migration velocity of the solute. However, in real cases, it is important to predict the zone spreading which occurs by axial dispersion and mass transfer resistance. To predict the actual solute profiles in the column or effluent stream, numerical methods to solve nonlinear partial differential equations have been used. However, these methods involve much time and expense. In this work, two different rate factors are considered to predict the characteristics of the solute profiles. The first is solute migration velocity and the second is the zone spreading rate. The zone spreading rate can be estimated by the apparent axial dispersion coefficient which is obtained from the height of the equivalent theoretical plate in particular. Four benzene derivatives (benzene, toluene, p-xylene, and acetophenone) were used as model solutes, and two mobile phase systems, water/methanol and water/ACN, were used in RP-HPLC. The bandwidths and retention times of the solutes were predicted under several linear gradient conditions. The predicted and experimental bandwidths and retention times showed good agreement.

  10. Magnetic resonance metabolic profiling of breast cancer tissue obtained with core needle biopsy for predicting pathologic response to neoadjuvant chemotherapy.

    Directory of Open Access Journals (Sweden)

    Ji Soo Choi

    Full Text Available The purpose of this study was to determine whether metabolic profiling of core needle biopsy (CNB samples using high-resolution magic angle spinning (HR-MAS magnetic resonance spectroscopy (MRS could be used for predicting pathologic response to neoadjuvant chemotherapy (NAC in patients with locally advanced breast cancer. After institutional review board approval and informed consent were obtained, CNB tissue samples were collected from 37 malignant lesions in 37 patients before NAC treatment. The metabolic profiling of CNB samples were performed by HR-MAS MRS. Metabolic profiles were compared according to pathologic response to NAC using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA. Various metabolites including choline-containing compounds were identified and quantified by HR-MAS MRS in all 37 breast cancer tissue samples obtained by CNB. In univariate analysis, the metabolite concentrations and metabolic ratios of CNB samples obtained with HR-MAS MRS were not significantly different between different pathologic response groups. However, there was a trend of lower levels of phosphocholine/creatine ratio and choline-containing metabolite concentrations in the pathologic complete response group compared to the non-pathologic complete response group. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the pathologic response groups. This study showed OPLS-DA multivariate analysis using metabolic profiles of pretreatment CNB samples assessed by HR- MAS MRS may be used to predict pathologic response before NAC, although we did not identify the metabolite showing statistical significance in univariate analysis. Therefore, our preliminary results raise the necessity of further study on HR-MAS MR metabolic profiling of CNB samples for a large number of cancers.

  11. Cathode design investigation based on iterative correction of predicted profile errors in electrochemical machining of compressor blades

    Institute of Scientific and Technical Information of China (English)

    Zhu Dong; Liu Cheng; Xu Zhengyang; Liu Jia

    2016-01-01

    Electrochemical machining (ECM) is an effective and economical manufacturing method for machining hard-to-cut metal materials that are often used in the aerospace field. Cathode design is very complicated in ECM and is a core problem influencing machining accuracy, especially for complex profiles such as compressor blades in aero engines. A new cathode design method based on iterative correction of predicted profile errors in blade ECM is proposed in this paper. A math-ematical model is first built according to the ECM shaping law, and a simulation is then carried out using ANSYS software. A dynamic forming process is obtained and machining gap distributions at different stages are analyzed. Additionally, the simulation deviation between the prediction profile and model is improved by the new method through correcting the initial cathode profile. Further-more, validation experiments are conducted using cathodes designed before and after the simulation correction. Machining accuracy for the optimal cathode is improved markedly compared with that for the initial cathode. The experimental results illustrate the suitability of the new method and that it can also be applied to other complex engine components such as diffusers.

  12. Cathode design investigation based on iterative correction of predicted profile errors in electrochemical machining of compressor blades

    Directory of Open Access Journals (Sweden)

    Zhu Dong

    2016-08-01

    Full Text Available Electrochemical machining (ECM is an effective and economical manufacturing method for machining hard-to-cut metal materials that are often used in the aerospace field. Cathode design is very complicated in ECM and is a core problem influencing machining accuracy, especially for complex profiles such as compressor blades in aero engines. A new cathode design method based on iterative correction of predicted profile errors in blade ECM is proposed in this paper. A mathematical model is first built according to the ECM shaping law, and a simulation is then carried out using ANSYS software. A dynamic forming process is obtained and machining gap distributions at different stages are analyzed. Additionally, the simulation deviation between the prediction profile and model is improved by the new method through correcting the initial cathode profile. Furthermore, validation experiments are conducted using cathodes designed before and after the simulation correction. Machining accuracy for the optimal cathode is improved markedly compared with that for the initial cathode. The experimental results illustrate the suitability of the new method and that it can also be applied to other complex engine components such as diffusers.

  13. Injury Profile SIMulator, a qualitative aggregative modelling framework to predict crop injury profile as a function of cropping practices, and the abiotic and biotic environment. I. Conceptual bases.

    Science.gov (United States)

    Aubertot, Jean-Noël; Robin, Marie-Hélène

    2013-01-01

    The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop.

  14. Injury Profile SIMulator, a qualitative aggregative modelling framework to predict crop injury profile as a function of cropping practices, and the abiotic and biotic environment. I. Conceptual bases.

    Directory of Open Access Journals (Sweden)

    Jean-Noël Aubertot

    Full Text Available The limitation of damage caused by pests (plant pathogens, weeds, and animal pests in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i develop, and to a lesser extent ii combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM strategies (vertical integration, there is a need for tools to help manage Injury Profiles (horizontal integration. Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator, a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat. In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop.

  15. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Crop Injury Profile as a Function of Cropping Practices, and the Abiotic and Biotic Environment. I. Conceptual Bases

    Science.gov (United States)

    Aubertot, Jean-Noël; Robin, Marie-Hélène

    2013-01-01

    The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop. PMID:24019908

  16. Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

    Directory of Open Access Journals (Sweden)

    Nina Melzer

    Full Text Available In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach. To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317 SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype.

  17. Applying geographic profiling used in the field of criminology for predicting the nest locations of bumble bees.

    Science.gov (United States)

    Suzuki-Ohno, Yukari; Inoue, Maki N; Ohno, Kazunori

    2010-07-21

    We tested whether geographic profiling (GP) can predict multiple nest locations of bumble bees. GP was originally developed in the field of criminology for predicting the area where an offender most likely resides on the basis of the actual crime sites and the predefined probability of crime interaction. The predefined probability of crime interaction in the GP model depends on the distance of a site from an offender's residence. We applied GP for predicting nest locations, assuming that foraging and nest sites were the crime sites and the offenders' residences, respectively. We identified the foraging and nest sites of the invasive species Bombus terrestris in 2004, 2005, and 2006. We fitted GP model coefficients to the field data of the foraging and nest sites, and used GP with the fitting coefficients. GP succeeded in predicting about 10-30% of actual nests. Sensitivity analysis showed that the predictability of the GP model mainly depended on the coefficient value of buffer zone, the distance at the mode of the foraging probability. GP will be able to predict the nest locations of bumble bees in other area by using the fitting coefficient values measured in this study. It will be possible to further improve the predictability of the GP model by considering food site preference and nest density.

  18. Robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection.

    Science.gov (United States)

    Pan, Xiao-Yong; Shen, Hong-Bin

    2009-01-01

    B-factor is highly correlated with protein internal motion, which is used to measure the uncertainty in the position of an atom within a crystal structure. Although the rapid progress of structural biology in recent years makes more accurate protein structures available than ever, with the avalanche of new protein sequences emerging during the post-genomic Era, the gap between the known protein sequences and the known protein structures becomes wider and wider. It is urgent to develop automated methods to predict B-factor profile from the amino acid sequences directly, so as to be able to timely utilize them for basic research. In this article, we propose a novel approach, called PredBF, to predict the real value of B-factor. We firstly extract both global and local features from the protein sequences as well as their evolution information, then the random forests feature selection is applied to rank their importance and the most important features are inputted to a two-stage support vector regression (SVR) for prediction, where the initial predicted outputs from the 1(st) SVR are further inputted to the 2nd layer SVR for final refinement. Our results have revealed that a systematic analysis of the importance of different features makes us have deep insights into the different contributions of features and is very necessary for developing effective B-factor prediction tools. The two-layer SVR prediction model designed in this study further enhanced the robustness of predicting the B-factor profile. As a web server, PredBF is freely available at: http://www.csbio.sjtu.edu.cn/bioinf/PredBF for academic use.

  19. Predicting the Mean Liquid Film Thickness and Profile along the Annular Length of a Uniformly Heated Channel at Dryout

    Directory of Open Access Journals (Sweden)

    V.Y. Agbodemegbe

    2011-03-01

    Full Text Available The objective of this study was to predict the mean liquid film thickness and profile at high shear stress using a mechanistic approach. Knowledge of the liquid film thickness and its variation with two-phase flow parameters is critical for the estimation of safety parameters in the annular flow regime. The mean liquid film thickness and profile were predicted by the PLIFT code designed in Fortran 95 programming language using the PLATO FTN95 compiler. The film thickness was predicted within the annular flow regime for a flow boiling quality ranging from 40 to 80 % at high interfacial shear stress. Results obtained for a laminar liquid film flow were dumped into an excel file when the ratio of the actual predicted film thickness to the critical liquid film thickness lied within the range of 0.9 to unity. The film thickness was observed to decrease towards the exit of the annular regime at high flow boiling qualities and void fractions. The observation confirmed the effect of evaporation in decreasing the film thickness as quality is increased towards the exit of the annular regime.

  20. Development of Integrated Magnetic and Kinetic Control-oriented Transport Model for q-profile Response Prediction in EAST Discharges

    Science.gov (United States)

    Wang, Hexiang; Schuster, Eugenio; Rafiq, Tariq; Kritz, Arnold; Ding, Siye

    2016-10-01

    Extensive research has been conducted to find high-performance operating scenarios characterized by high fusion gain, good confinement, plasma stability and possible steady-state operation. A key plasma property that is related to both the stability and performance of these advanced plasma scenarios is the safety factor profile. A key component of the EAST research program is the exploration of non-inductively driven steady-state plasmas with the recently upgraded heating and current drive capabilities that include lower hybrid current drive and neutral beam injection. Anticipating the need for tight regulation of the safety factor profile in these plasma scenarios, a first-principles-driven (FPD)control-oriented model is proposed to describe the safety factor profile evolution in EAST in response to the different actuators. The TRANSP simulation code is employed to tailor the FPD model to the EAST tokamak geometry and to convert it into a form suitable for control design. The FPD control-oriented model's prediction capabilities are demonstrated by comparing predictions with experimental data from EAST. Supported by the US DOE under DE-SC0010537,DE-FG02-92ER54141 and DE-SC0013977.

  1. Profiles of Observed Infant Anger Predict Preschool Behavior Problems: Moderation by Life Stress

    Science.gov (United States)

    Brooker, Rebecca J.; Buss, Kristin A.; Lemery-Chalfant, Kathryn; Aksan, Nazan; Davidson, Richard J.; Goldsmith, H. Hill

    2014-01-01

    Using both traditional composites and novel profiles of anger, we examined associations between infant anger and preschool behavior problems in a large, longitudinal data set (N = 966). We also tested the role of life stress as a moderator of the link between early anger and the development of behavior problems. Although traditional measures of…

  2. Early Childhood Profiles of Sleep Problems and Self-Regulation Predict Later School Adjustment

    Science.gov (United States)

    Williams, Kate E.; Nicholson, Jan M.; Walker, Sue; Berthelsen, Donna

    2016-01-01

    Background: Children's sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. Aims: This study explores the normative developmental pathway for sleep problems and self-regulation…

  3. Predicting Educational Outcomes and Psychological Well-Being in Adolescents Using Time Attitude Profiles

    Science.gov (United States)

    Andretta, James R.; Worrell, Frank C.; Mello, Zena R.

    2014-01-01

    Using cluster analysis of Adolescent Time Attitude Scale (ATAS) scores in a sample of 300 adolescents ("M" age = 16 years; "SD" = 1.25; 60% male; 41% European American; 25.3% Asian American; 11% African American; 10.3% Latino), the authors identified five time attitude profiles based on positive and negative attitudes toward…

  4. Distinct neurohumoral biomarker profiles in children with hemodynamically defined orthostatic intolerance may predict treatment options.

    Science.gov (United States)

    Wagoner, Ashley L; Shaltout, Hossam A; Fortunato, John E; Diz, Debra I

    2016-02-01

    Studies of adults with orthostatic intolerance (OI) have revealed altered neurohumoral responses to orthostasis, which provide mechanistic insights into the dysregulation of blood pressure control. Similar studies in children with OI providing a thorough neurohumoral profile are lacking. The objective of the present study was to determine the cardiovascular and neurohumoral profile in adolescent subjects presenting with OI. Subjects at 10-18 yr of age were prospectively recruited if they exhibited two or more traditional OI symptoms and were referred for head-up tilt (HUT) testing. Circulating catecholamines, vasopressin, aldosterone, renin, and angiotensins were measured in the supine position and after 15 min of 70° tilt. Heart rate and blood pressure were continuously measured. Of the 48 patients, 30 patients had an abnormal tilt. Subjects with an abnormal tilt had lower systolic, diastolic, and mean arterial blood pressures during tilt, significantly higher levels of vasopressin during HUT, and relatively higher catecholamines and ANG II during HUT than subjects with a normal tilt. Distinct neurohumoral profiles were observed when OI subjects were placed into the following groups defined by the hemodynamic response: postural orthostatic tachycardia syndrome (POTS), orthostatic hypotension (OH), syncope, and POTS/syncope. Key characteristics included higher HUT-induced norepinephrine in POTS subjects, higher vasopressin in OH and syncope subjects, and higher supine and HUT aldosterone in OH subjects. In conclusion, children with OI and an abnormal response to tilt exhibit distinct neurohumoral profiles associated with the type of the hemodynamic response during orthostatic challenge. Elevated arginine vasopressin levels in syncope and OH groups are likely an exaggerated response to decreased blood flow not compensated by higher norepinephrine levels, as observed in POTS subjects. These different compensatory mechanisms support the role of measuring neurohumoral

  5. Use of the maximum entropy method to retrieve the vertical atmospheric ozone profile and predict atmospheric ozone content

    Science.gov (United States)

    Turner, B. Curtis

    1992-01-01

    A method is developed for prediction of ozone levels in planetary atmospheres. This method is formulated in terms of error covariance matrices, and is associated with both direct measurements, a priori first guess profiles, and a weighting function matrix. This is described by the following linearized equation: y = A(matrix) x X + eta, where A is the weighting matrix and eta is noise. The problems to this approach are: (1) the A matrix is near singularity; (2) the number of unknowns in the profile exceeds the number of data points, therefore, the solution may not be unique; and (3) even if a unique solution exists, eta may cause the solution to be ill conditioned.

  6. Gene Expression Profiles Can Predict Panitumumab Monotherapy Responsiveness in Human Tumor Xenograft Models

    Directory of Open Access Journals (Sweden)

    Michael J. Boedigheimer

    2013-02-01

    Conclusion A model was constructed from microarray data that prospectively predict responsiveness to panitumumab in xenograft models. This approach may help identify patients, independent of disease origin, likely to benefit from panitumumab.

  7. Urinary MicroRNA Profiling Predicts the Development of Microalbuminuria in Patients with Type 1 Diabetes

    OpenAIRE

    Christos Argyropoulos; Kai Wang; Jose Bernardo; Demetrius Ellis; Trevor Orchard; David Galas; Johnson, John P.

    2015-01-01

    Microalbuminuria provides the earliest clinical marker of diabetic nephropathy among patients with Type 1 diabetes, yet it lacks sensitivity and specificity for early histological manifestations of disease. In recent years microRNAs have emerged as potential mediators in the pathogenesis of diabetes complications, suggesting a possible role in the diagnosis of early stage disease. We used quantiative polymerase chain reaction (qPCR) to evaluate the expression profile of 723 unique microRNAs i...

  8. Coconut oil predicts a beneficial lipid profile in pre-menopausal women in the Philippines

    Science.gov (United States)

    Feranil, Alan B.; Duazo, Paulita L.; Kuzawa, Christopher W.; Adair, Linda S.

    2011-01-01

    Coconut oil is a common edible oil in many countries, and there is mixed evidence for its effects on lipid profiles and cardiovascular disease risk. Here we examine the association between coconut oil consumption and lipid profiles in a cohort of 1,839 Filipino women (age 35–69 years) participating in the Cebu Longitudinal Health and Nutrition Survey, a community based study in Metropolitan Cebu City. Coconut oil intake was measured as individual coconut oil intake calculated using two 24-hour dietary recalls (9.54 ± 8.92 grams). Cholesterol profiles were measured in plasma samples collected after an overnight fast. Mean lipid values in this sample were total cholesterol (TC) (186.52 ± 38.86 mg/dL), high density lipoprotein cholesterol (HDL-c) (40.85 ± 10.30 mg/dL), low density lipoprotein cholesterol (LDL-c) (119.42 ± 33.21 mg/dL), triglycerides (130.75 ± 85.29 mg/dL) and the TC/HDL ratio (4.80 ± 1.41). Linear regression models were used to estimate the association between coconut oil intake and each plasma lipid outcome after adjusting for total energy intake, age, body mass index (BMI), number of pregnancies, education, menopausal status, household assets and urban residency. Dietary coconut oil intake was positively associated with HDL-c levels. PMID:21669587

  9. Acute Lethality of Inhaled Hydrogen Cyanide in the Laboratory Rat: Impact of Concentration x Time Profile and Evaluation of the Predictivity of Toxic Load Models

    Science.gov (United States)

    2013-05-03

    Naval Medical Research Unit Dayton Acute Lethality of Inhaled Hydrogen Cyanide in the Laboratory Rat : Impact of Concentration × Time Profile and...Cyanide in the Laboratory Rat : Impact of Concentration x Time Profile and Evaluation of the Predictivity of “Toxic Load” Models. 5a. Contract

  10. An FE Based On-line Model for the Prediction of Work Roll Thermal Profile in Hot Strip Rolling

    Science.gov (United States)

    Choi, Ji Won; Lee, Jung Hyeung; Sun, Cheng Gang; Hwang, Sang Moo

    2010-06-01

    Prediction and control of the thermal deformation of the work roll is vital for enhancing product quality in hot strip and plate rolling. In this paper, we present an on-line model for the prediction of the work roll thermal profile. The model is developed on the basis of an integrated finite element model for the coupled analysis of heat transfer and deformation occurring at the bite zone, to rigorously take into account the effect of various rolling parameters on the thermal behavior of the work roll. The validity of the model is demonstrated through comparison with measurements made in an industrial hot strip mill. Also, an emphasis is given to the examination the effect of some selected rolling parameters in an actual production environment.

  11. A new model for the prediction of the steepness profile across the strip in flat rolling

    Science.gov (United States)

    Kim, Jinseok; Hwang, Sangmoo

    2010-06-01

    In flat rolling, wavy surfaces are easily formed in the strip, causing the problem of poor flatness. The wavy surfaces may not only reduce the commercial value of the product but also lead to the breakage of the strip while passing through the roll gap. Therefore, it is necessary to strictly control the wave formation. In this paper, we present a new approach to the prediction of the wavy shape of the strip. The approach is based on minimization of the potential energy and adopts Ritz method as a solution technique. The approach is described in detail, with emphasis on the procedure to treat the effect of the total tension on the shape of the formed waves. The prediction accuracy of the proposed model is examined through comparison with predictions from the finite element method. Then, demonstrated is the model's capability of reproducing various wavy surfaces that may be observed in the flat rolling mill.

  12. Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

    Science.gov (United States)

    Chapman, Robert W; Reading, Benjamin J; Sullivan, Craig V

    2014-01-01

    Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing 90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

  13. Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

    Directory of Open Access Journals (Sweden)

    Robert W Chapman

    Full Text Available Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis, a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs and supervised machine learning, collective changes in the expression of a limited suite of genes (233 representing 90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold, with most individual transcripts making a small contribution (<1% to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

  14. Ovary Transcriptome Profiling via Artificial Intelligence Reveals a Transcriptomic Fingerprint Predicting Egg Quality in Striped Bass, Morone saxatilis

    Science.gov (United States)

    2014-01-01

    Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing 90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic “fingerprint”. Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness. PMID:24820964

  15. Prediction of dissolution profiles by non-destructive near infrared spectroscopy in tablets subjected to different levels of strain.

    Science.gov (United States)

    Hernandez, Eduardo; Pawar, Pallavi; Keyvan, Golshid; Wang, Yifan; Velez, Natasha; Callegari, Gerardo; Cuitino, Alberto; Michniak-Kohn, Bozena; Muzzio, Fernando J; Romañach, Rodolfo J

    2016-01-01

    This study describes how the strain on formulation components affects dissolution and how near infrared spectroscopy can be used to predict dissolution. Strain (exposure to shear stress) applied during powder mixing affects the interaction between formulation components. Particles experience shear strain when they move relative to each other in a process affecting the properties of the final product. This stress affects the dissolution of oral solid dosages forms. However, dissolution testing destroys the entire tablet, making it impossible to further evaluate tablet properties when an out of specification result is obtained. Thus, a nondestructive technique such as near infrared spectroscopy is desirable to predict dissolution. The aim of this study was to predict dissolution on tablets with different levels of strain (shear) using near infrared spectroscopy in combination with multivariate data analysis. Shear was induced using a modified Couette cell on the powder mixture and tablets from these mixtures were produced using a tablet press emulator. Tablets produced with different strain levels were measured using near infrared spectroscopy. Spectra were obtained in diffuse reflectance mode and pretreated with baseline correction to maintain the physical and chemical information of the tablets. Dissolution profiles were obtained using USP Apparatus 2 as a reference method. Principal component analysis was used to study the sources of variation in the spectra obtained. Partial least squares 2 was used to predict dissolution on tablets with different levels of strain.

  16. Predicting absorption and pharmacokinetic profile of carbamazepine from controlled-release tablet formulation in humans using rabbit model

    Directory of Open Access Journals (Sweden)

    Homšek Irena

    2011-01-01

    Full Text Available Controlled-release (CR pharmaceutical formulations offer several advantages over the conventional, immediate release dosage forms of the same drug, including reduced dosing frequency, decreased incidence and/or intensity of adverse effects, greater selectivity of pharmacological activity, reduced drug plasma fluctuation, and better compliance. After a drug product has been registered, and is already on market, minor changes in formulation might be needed. At the same time, the product has to remain effective and safe for patients that could be confirmed via plasma drug concentrations and pharmacokinetic characteristics. It is challenging to predict human absorption and pharmacokinetic characteristics of a drug based on the in vitro dissolution test and the animal pharmacokinetic data. Therefore, the objective of this study was to establish correlation of the pharmacokinetic parameters of carbamazepine (CBZ CR tablet formulation between the rabbit and the human model, and to establish in vitro in vivo correlation (IVIVC based on the predicted fractions of absorbed CBZ. Although differences in mean plasma concentration profiles were notified, the data concerning the predicted fraction of drug absorbed were almost superimposable. Accordingly, it can be concluded that rabbits may be representative as an in vivo model for predicting the pharmacokinetics of the CR formulation of CBZ in humans.

  17. A bioinformatics tool for linking gene expression profiling results with public databases of microRNA target predictions

    Science.gov (United States)

    Creighton, Chad J.; Nagaraja, Ankur K.; Hanash, Samir M.; Matzuk, Martin M.; Gunaratne, Preethi H.

    2008-01-01

    MicroRNAs are short (∼22 nucleotides) noncoding RNAs that regulate the stability and translation of mRNA targets. A number of computational algorithms have been developed to help predict which microRNAs are likely to regulate which genes. Gene expression profiling of biological systems where microRNAs might be active can yield hundreds of differentially expressed genes. The commonly used public microRNA target prediction databases facilitate gene-by-gene searches. However, integration of microRNA–mRNA target predictions with gene expression data on a large scale using these databases is currently cumbersome and time consuming for many researchers. We have developed a desktop software application which, for a given target prediction database, retrieves all microRNA:mRNA functional pairs represented by an experimentally derived set of genes. Furthermore, for each microRNA, the software computes an enrichment statistic for overrepresentation of predicted targets within the gene set, which could help to implicate roles for specific microRNAs and microRNA-regulated genes in the system under study. Currently, the software supports searching of results from PicTar, TargetScan, and miRanda algorithms. In addition, the software can accept any user-defined set of gene-to-class associations for searching, which can include the results of other target prediction algorithms, as well as gene annotation or gene-to-pathway associations. A search (using our software) of genes transcriptionally regulated in vitro by estrogen in breast cancer uncovered numerous targeting associations for specific microRNAs—above what could be observed in randomly generated gene lists—suggesting a role for microRNAs in mediating the estrogen response. The software and Excel VBA source code are freely available at http://sigterms.sourceforge.net. PMID:18812437

  18. A bioinformatics tool for linking gene expression profiling results with public databases of microRNA target predictions.

    Science.gov (United States)

    Creighton, Chad J; Nagaraja, Ankur K; Hanash, Samir M; Matzuk, Martin M; Gunaratne, Preethi H

    2008-11-01

    MicroRNAs are short (approximately 22 nucleotides) noncoding RNAs that regulate the stability and translation of mRNA targets. A number of computational algorithms have been developed to help predict which microRNAs are likely to regulate which genes. Gene expression profiling of biological systems where microRNAs might be active can yield hundreds of differentially expressed genes. The commonly used public microRNA target prediction databases facilitate gene-by-gene searches. However, integration of microRNA-mRNA target predictions with gene expression data on a large scale using these databases is currently cumbersome and time consuming for many researchers. We have developed a desktop software application which, for a given target prediction database, retrieves all microRNA:mRNA functional pairs represented by an experimentally derived set of genes. Furthermore, for each microRNA, the software computes an enrichment statistic for overrepresentation of predicted targets within the gene set, which could help to implicate roles for specific microRNAs and microRNA-regulated genes in the system under study. Currently, the software supports searching of results from PicTar, TargetScan, and miRanda algorithms. In addition, the software can accept any user-defined set of gene-to-class associations for searching, which can include the results of other target prediction algorithms, as well as gene annotation or gene-to-pathway associations. A search (using our software) of genes transcriptionally regulated in vitro by estrogen in breast cancer uncovered numerous targeting associations for specific microRNAs-above what could be observed in randomly generated gene lists-suggesting a role for microRNAs in mediating the estrogen response. The software and Excel VBA source code are freely available at http://sigterms.sourceforge.net.

  19. Predicting tenocyte expression profiles and average molecular concentrations in Achilles tendon ECM from tissue strain and fiber damage.

    Science.gov (United States)

    Mehdizadeh, Arash; Gardiner, Bruce S; Lavagnino, Michael; Smith, David W

    2017-03-13

    In this study, we propose a method for quantitative prediction of changes in concentrations of a number of key signaling, structural and effector molecules within the extracellular matrix of tendon. To achieve this, we introduce the notion of elementary cell responses (ECRs). An ECR defines a normal reference secretion profile of a molecule by a tenocyte in response to the tenocyte's local strain. ECRs are then coupled with a model for mechanical damage of tendon collagen fibers at different straining conditions of tendon and then scaled up to the tendon tissue level for comparison with experimental observations. Specifically, our model predicts relative changes in ECM concentrations of transforming growth factor beta, interleukin 1 beta, collagen type I, glycosaminoglycan, matrix metalloproteinase 1 and a disintegrin and metalloproteinase with thrombospondin motifs 5, with respect to tendon straining conditions that are consistent with the observations in the literature. In good agreement with a number of in vivo and in vitro observations, the model provides a logical and parsimonious explanation for how excessive mechanical loading of tendon can lead to under-stimulation of tenocytes and a degenerative tissue profile, which may well have bearing on a better understanding of tendon homeostasis and the origin of some tendinopathies.

  20. Identification of genes required for maximal tolerance to high-glucose concentrations, as those present in industrial alcoholic fermentation media, through a chemogenomics approach.

    Science.gov (United States)

    Teixeira, Miguel C; Raposo, Luís R; Palma, Margarida; Sá-Correia, Isabel

    2010-04-01

    Chemogenomics, the study of genomic responses to chemical compounds, has the potential to elucidate the basis of cellular resistance to those chemicals. This knowledge can be applied to improve the performance of strains of industrial interest. In this study, a collection of approximately 5,000 haploid single deletion mutants of Saccharomyces cerevisiae in which each nonessential yeast gene was individually deleted, was screened for strains with increased susceptibility toward stress induced by high-glucose concentration (30% w/v), one of the main stresses occurring during industrial alcoholic fermentation processes aiming the production of alcoholic beverages or bio-ethanol. Forty-four determinants of resistance to high-glucose stress were identified. The most significant Gene Ontology (GO) terms enriched in this dataset are vacuolar organization, late endosome to vacuole transport, and regulation of transcription. Clustering the identified resistance determinants by their known physical and genetic interactions further highlighted the importance of nutrient metabolism control in this context. A concentration of 30% (w/v) of glucose was found to perturb vacuolar function, by reducing cell ability to maintain the physiological acidification of the vacuolar lumen. This stress also affects the active rate of proton efflux through the plasma membrane. Based on results of published studies, the present work revealed shared determinants of yeast resistance to high-glucose and ethanol stresses, including genes involved in vacuolar function, cell wall biogenesis (ANP1), and in the transcriptional control of nutrient metabolism (GCN4 and GCR1), with possible impact on the design of more robust strains to be used in industrial alcoholic fermentation processes.

  1. Partially obstructed channel: Contraction ratio effect on the flow hydrodynamic structure and prediction of the transversal mean velocity profile

    Science.gov (United States)

    Ben Meftah, M.; Mossa, M.

    2016-11-01

    In this manuscript, we focus on the study of flow structures in a channel partially obstructed by arrays of vertical, rigid, emergent, vegetation/cylinders. Special attention is given to understand the effect of the contraction ratio, defined as the ratio of the obstructed area width to the width of the unobstructed area, on the flow hydrodynamic structures and to analyze the transversal flow velocity profile at the obstructed-unobstructed interface. A large data set of transversal mean flow velocity profiles and turbulence characteristics is reported from experiments carried out in a laboratory flume. The flow velocities and turbulence intensities have been measured with a 3D Acoustic Doppler Velocimeter (ADV)-Vectrino manufactured by Nortek. It was observed that the arrays of emergent vegetation/cylinders strongly affect the flow structures, forming a shear layer immediately next to the obstructed-unobstructed interface, followed by an adjacent free-stream region of full velocity flow. The experimental results show that the contraction ratio significantly affects the flow hydrodynamic structure. Adaptation of the Prandtl's log-law modified by Nikuradse led to the determination of a characteristic hydrodynamic roughness height to define the array resistance to the flow. Moreover, an improved modified log-law predicting the representative transversal profile of the mean flow velocity, at the obstructed-unobstructed interface, is proposed. The benefit of this modified log-law is its easier practical applicability, i.e., it avoids the measurements of some sensitive turbulence parameters, in addition, the flow hydrodynamic variables forming it are predictable, using the initial hydraulic conditions.

  2. Automatic selection of preprocessing methods for improving predictions on mass spectrometry protein profiles.

    Science.gov (United States)

    Pelikan, Richard C; Hauskrecht, Milos

    2010-11-13

    Mass spectrometry proteomic profiling has potential to be a useful clinical screening tool. One obstacle is providing a standardized method for preprocessing the noisy raw data. We have developed a system for automatically determining a set of preprocessing methods among several candidates. Our system's automated nature relieves the analyst of the need to be knowledgeable about which methods to use on any given dataset. Each stage of preprocessing is approached with many competing methods. We introduce metrics which are used to balance each method's attempts to correct noise versus preserving valuable discriminative information. We demonstrate the benefit of our preprocessing system on several SELDI and MALDI mass spectrometry datasets. Downstream classification is improved when using our system to preprocess the data.

  3. In-flight measurements and RCS-predictions: A comparison on broad-side radar range profiles of a Boeing 737

    NARCIS (Netherlands)

    Heiden, R. van der; Ewijk, L.J. van; Groen, F.C.A.

    1997-01-01

    The validation of Radar Cross Section (RCS) prediction techniques against real measurements is crucial to acquire confidence in predictions when measurements are not available. In this paper we present the first results of a comparison on one dimensional images, i.e., radar range profiles. The profi

  4. Transcriptome profiling of patient-specific human iPSC-cardiomyocytes predicts individual drug safety and efficacy responses in vitro

    Science.gov (United States)

    Matsa, Elena; Burridge, Paul W.; Yu, Kun-Hsing; Ahrens, John H.; Termglinchan, Vittavat; Wu, Haodi; Liu, Chun; Shukla, Praveen; Sayed, Nazish; Churko, Jared M.; Shao, Ningyi; Woo, Nicole A.; Chao, Alexander S.; Gold, Joseph D.; Karakikes, Ioannis; Snyder, Michael P.; Wu, Joseph C.

    2016-01-01

    SUMMARY Understanding individual susceptibility to drug-induced cardiotoxicity is key to improving patient safety and preventing drug attrition. Human induced pluripotent stem cells (hiPSCs) enable the study of pharmacological and toxicological responses in patient-specific cardiomyocytes (CMs), and may serve as preclinical platforms for precision medicine. Transcriptome profiling in hiPSC-CMs from seven individuals lacking known cardiovascular disease-associated mutations, and in three isogenic human heart tissue and hiPSC-CM pairs, showed greater inter-patient variation than intra-patient variation, verifying that reprogramming and differentiation preserve patient-specific gene expression, particularly in metabolic and stress-response genes. Transcriptome-based toxicology analysis predicted and risk-stratified patient-specific susceptibility to cardiotoxicity, and functional assays in hiPSC-CMs using tacrolimus and rosiglitazone, drugs targeting pathways predicted to produce cardiotoxicity, validated inter-patient differential responses. CRISPR/Cas9-mediated pathway correction prevented drug-induced cardiotoxicity. Our data suggest that hiPSC-CMs can be used in vitro to predict and validate patient-specific drug safety and efficacy, potentially enabling future clinical approaches to precision medicine. PMID:27545504

  5. Volatile profile analysis and quality prediction of Longjing tea (Camellia sinensis) by HS-SPME/GC-MS

    Institute of Scientific and Technical Information of China (English)

    Jie LIN; Yi DAI; Ya-nan GUO; Hai-rong XU; Xiao-chang WANG

    2012-01-01

    This study aimed to analyze the volatile chemical profile of Longjing tea,and further develop a prediction model for aroma quality of Longjing tea based on potent odorants.A total of 21 Longjing samples were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS).Pearson's linear correlation analysis and partial least square (PLS) regression were applied to investigate the relationship between sensory aroma scores and the volatile compounds.Results showed that 60 volatile compounds could be commonly detected in this famous green tea.Terpenes and esters were two major groups characterized,representing 33.89% and 15.53% of the total peak area respectively.Ten compounds were determined to contribute significantly to the perceived aroma quality of Longjing tea,especially linalool (0.701),nonanal (0.738),(Z)-3-hexenyl hexanoate (-0.785),and β-ionone (-0.763).On the basis of these 10 compounds,a model (correlation coefficient of 89.4% and cross-validated correlation coefficient of 80.4%) was constructed to predict the aroma quality of Longjing tea.Summarily,this study has provided a novel option for quality prediction of green tea based on HS-SPME/GC-MS technique.

  6. Prediction of fatty acid profiles in cow, ewe, and goat milk by mid-infrared spectrometry.

    Science.gov (United States)

    Ferrand-Calmels, M; Palhière, I; Brochard, M; Leray, O; Astruc, J M; Aurel, M R; Barbey, S; Bouvier, F; Brunschwig, P; Caillat, H; Douguet, M; Faucon-Lahalle, F; Gelé, M; Thomas, G; Trommenschlager, J M; Larroque, H

    2014-01-01

    Mid-infrared (MIR) spectrometry was used to estimate the fatty acid (FA) composition in cow, ewe, and goat milk. The objectives were to compare different statistical approaches with wavelength selection to predict the milk FA composition from MIR spectra, and to develop equations for FA in cow, goat, and ewe milk. In total, a set of 349 cow milk samples, 200 ewe milk samples, and 332 goat milk samples were both analyzed by MIR and by gas chromatography, the reference method. A broad FA variability was ensured by using milk from different breeds and feeding systems. The methods studied were partial least squares regression (PLS), first-derivative pretreatment + PLS, genetic algorithm + PLS, wavelets + PLS, least absolute shrinkage and selection operator method (LASSO), and elastic net. The best results were obtained with PLS, genetic algorithm + PLS and first derivative + PLS. The residual standard deviation and the coefficient of determination in external validation were used to characterize the equations and to retain the best for each FA in each species. In all cases, the predictions were of better quality for FA found at medium to high concentrations (i.e., for saturated FA and some monounsaturated FA with a coefficient of determination in external validation >0.90). The conversion of the FA expressed in grams per 100mL of milk to grams per 100g of FA was possible with a small loss of accuracy for some FA.

  7. The attribute of rotational profile to the hyperon puzzle in the prediction of heaviest compact star

    CERN Document Server

    Bhuyan, M

    2016-01-01

    In this theoretical study, we report an investigation of the equations of state (EoSs) of hyper-nuclear matter and its composition as a function of density within the framework of effective field theory motivated relativistic mean field model. We have used G2 force parameter along with various hyperon-meson coupling ratios by allowing the mixing and the breaking of SU(6) symmetry to predict the EoSs, keeping the nucleonic coupling constant intact. We have estimated the properties of non-rotating and rapidly rotating configuration of compact stars by employing a representative set of equations of state. The obtained results of the mass M$_{\\odot}$ and radius R$_{\\odot}$ for the compact stars are compared with the recent mass observations. We noticed that the inclusion of hyperon matter to the EoSs of nuclear matter under $\\beta$-equilibrium condition decreases the maximum mass of the compact star by $0.4$ unit in magnitude in comparison to the nuclear matter prediction. Further, we have studied the stability a...

  8. Predicting Delirium Duration in Elderly Hip-Surgery Patients: Does Early Symptom Profile Matter?

    Directory of Open Access Journals (Sweden)

    Chantal J. Slor

    2013-01-01

    Full Text Available Background. Features that may allow early identification of patients at risk of prolonged delirium, and therefore of poorer outcomes, are not well understood. The aim of this study was to determine if preoperative delirium risk factors and delirium symptoms (at onset and clinical symptomatology during the course of delirium are associated with delirium duration. Methods. This study was conducted in prospectively identified cases of incident delirium. We compared patients experiencing delirium of short duration (1 or 2 days with patients who had more prolonged delirium (≥3 days with regard to DRS-R-98 (Delirium Rating Scale Revised-98 symptoms on the first delirious day. Delirium symptom profile was evaluated daily during the delirium course. Results. In a homogenous population of 51 elderly hip-surgery patients, we found that the severity of individual delirium symptoms on the first day of delirium was not associated with duration of delirium. Preexisting cognitive decline was associated with prolonged delirium. Longitudinal analysis using the generalised estimating equations method (GEE identified that more severe impairment of long-term memory across the whole delirium episode was associated with longer duration of delirium. Conclusion. Preexisting cognitive decline rather than severity of individual delirium symptoms at onset is strongly associated with delirium duration.

  9. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

    Directory of Open Access Journals (Sweden)

    Minseung Kim

    2015-03-01

    Full Text Available A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5% to 98.3% (±2.3% for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain achieved 10.6% (±1.0% higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

  10. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

    Science.gov (United States)

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-03-01

    A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

  11. The Serum Profile of Hypercytokinemia Factors Identified in H7N9-Infected Patients can Predict Fatal Outcomes

    Science.gov (United States)

    Guo, Jing; Huang, Fengming; Liu, Jun; Chen, Yu; Wang, Wei; Cao, Bin; Zou, Zhen; Liu, Song; Pan, Jingcao; Bao, Changjun; Zeng, Mei; Xiao, Haixia; Gao, Hainv; Yang, Shigui; Zhao, Yan; Liu, Qiang; Zhou, Huandi; Zhu, Jingdong; Liu, Xiaoli; Liang, Weifeng; Yang, Yida; Zheng, Shufa; Yang, Jiezuan; Diao, Hongyan; Su, Kunkai; Shao, Li; Cao, Hongcui; Wu, Ying; Zhao, Min; Tan, Shuguang; Li, Hui; Xu, Xiaoqing; Wang, Chunmei; Zhang, Jianmin; Wang, Li; Wang, Jianwei; Xu, Jun; Li, Dangsheng; Zhong, Nanshan; Cao, Xuetao; Gao, George F.; Li, Lanjuan; Jiang, Chengyu

    2015-01-01

    The novel avian origin influenza A (H7N9) virus has caused severe diseases in humans in eastern China since the spring of 2013. Fatal outcomes of H7N9 infections are often attributed to the severe pneumonia and acute respiratory distress syndrome (ARDS). There is urgent need to discover biomarkers predicting the progression of disease and fatal outcome of potentially lethal flu infections, based on sound statistical analysis. We discovered that 34 of the 48 cytokines and chemokines examined in this study were significantly elevated in the plasma samples from patients infected with H7N9. We report for the first time that the levels of MIF, SCF, MCP-1, HGF, and SCGF-β are highly positively linked to disease severity and the profile of mediators MIF, SCF, MCP-1, HGF, SCGF-β, IP-10, IL-18, and IFN-γ is an independent outcome predictor. PMID:26028236

  12. Developing a Comparative Docking Protocol for the Prediction of Peptide Selectivity Profiles: Investigation of Potassium Channel Toxins

    Directory of Open Access Journals (Sweden)

    Serdar Kuyucak

    2012-02-01

    Full Text Available During the development of selective peptides against highly homologous targets, a reliable tool is sought that can predict information on both mechanisms of binding and relative affinities. These tools must first be tested on known profiles before application on novel therapeutic candidates. We therefore present a comparative docking protocol in HADDOCK using critical motifs, and use it to “predict” the various selectivity profiles of several major αKTX scorpion toxin families versus Kv1.1, Kv1.2 and Kv1.3. By correlating results across toxins of similar profiles, a comprehensive set of functional residues can be identified. Reasonable models of channel-toxin interactions can be then drawn that are consistent with known affinity and mutagenesis. Without biological information on the interaction, HADDOCK reproduces mechanisms underlying the universal binding of αKTX-2 toxins, and Kv1.3 selectivity of αKTX-3 toxins. The addition of constraints encouraging the critical lysine insertion confirms these findings, and gives analogous explanations for other families, including models of partial pore-block in αKTX-6. While qualitatively informative, the HADDOCK scoring function is not yet sufficient for accurate affinity-ranking. False minima in low-affinity complexes often resemble true binding in high-affinity complexes, despite steric/conformational penalties apparent from visual inspection. This contamination significantly complicates energetic analysis, although it is usually possible to obtain correct ranking via careful interpretation of binding-well characteristics and elimination of false positives. Aside from adaptations to the broader potassium channel family, we suggest that this strategy of comparative docking can be extended to other channels of interest with known structure, especially in cases where a critical motif exists to improve docking effectiveness.

  13. Molecule survival in magnetized protostellar disk winds. II. Predicted H2O line profiles versus Herschel/HIFI observations

    CERN Document Server

    Yvart, W; Forets, G Pineau des; Ferreira, J

    2016-01-01

    We investigate whether the broad wings of H2O emission identified with Herschel towards low-mass Class 0 and Class 1 protostars may be consistent with an origin in a dusty MHD disk wind, and the constraints it would set on the underlying disk properties. We present synthetic H2O line profiles predictions for a typical MHD disk wind solution with various values of disk accretion rate, stellar mass, extension of the launching area, and view angle. We compare them in terms of line shapes and intensities with the HIFI profiles observed by the WISH Key Program. We find that a dusty MHD disk wind launched from 0.2--0.6 AU AU to 3--25 AU can reproduce to a remarkable degree the observed shapes and intensities of the broad H2O component, both in the fundamental 557 GHz line and in more excited lines. Such a model also readily reproduces the observed correlation of 557 GHz line luminosity with envelope density, if the infall rate at 1000 AU is 1--3 times the disk accretion rate in the wind ejection region. It is also ...

  14. Quiescent and Active Tear Protein Profiles to Predict Vernal Keratoconjunctivitis Reactivation

    Directory of Open Access Journals (Sweden)

    Alessandra Micera

    2016-01-01

    Full Text Available Objective. Vernal keratoconjunctivitis (VKC is a chronic recurrent bilateral inflammation of the conjunctiva associated with atopy. Several inflammatory and tissue remodeling factors contribute to VKC disease. The aim is to provide a chip-based protein analysis in tears from patients suffering from quiescent or active VKC. Methods. This study cohort included 16 consecutive patients with VKC and 10 controls. Participants were subjected to clinical assessment of ocular surface and tear sampling. Total protein quantification, total protein sketch, and protein array (sixty protein candidates were evaluated. Results. An overall increased Fluorescent Intensity expression was observed in VKC arrays. Particularly, IL1β, IL15, IL21, Eotaxin2, TACE, MIP1α, MIP3α, NCAM1, ICAM2, βNGF, NT4, BDNF, βFGF, SCF, MMP1, and MMP2 were increased in quiescent VKC. Of those candidates, only IL1β, IL15, IL21, βNGF, SCF, MMP2, Eotaxin2, TACE, MIP1α, MIP3α, NCAM1, and ICAM2 were increased in both active and quiescent VKC. Finally, NT4, βFGF, and MMP1 were highly increased in active VKC. Conclusion. A distinct “protein tear-print” characterizes VKC activity, confirming some previously reported factors and highlighting some new candidates common to quiescent and active states. Those candidates expressed in quiescent VKC might be considered as predictive indicators of VKC reactivation and/or exacerbation out-of-season.

  15. Quiescent and Active Tear Protein Profiles to Predict Vernal Keratoconjunctivitis Reactivation

    Science.gov (United States)

    Micera, Alessandra; Di Zazzo, Antonio; Esposito, Graziana; Sgrulletta, Roberto; Calder, Virginia L.; Bonini, Stefano

    2016-01-01

    Objective. Vernal keratoconjunctivitis (VKC) is a chronic recurrent bilateral inflammation of the conjunctiva associated with atopy. Several inflammatory and tissue remodeling factors contribute to VKC disease. The aim is to provide a chip-based protein analysis in tears from patients suffering from quiescent or active VKC. Methods. This study cohort included 16 consecutive patients with VKC and 10 controls. Participants were subjected to clinical assessment of ocular surface and tear sampling. Total protein quantification, total protein sketch, and protein array (sixty protein candidates) were evaluated. Results. An overall increased Fluorescent Intensity expression was observed in VKC arrays. Particularly, IL1β, IL15, IL21, Eotaxin2, TACE, MIP1α, MIP3α, NCAM1, ICAM2, βNGF, NT4, BDNF, βFGF, SCF, MMP1, and MMP2 were increased in quiescent VKC. Of those candidates, only IL1β, IL15, IL21, βNGF, SCF, MMP2, Eotaxin2, TACE, MIP1α, MIP3α, NCAM1, and ICAM2 were increased in both active and quiescent VKC. Finally, NT4, βFGF, and MMP1 were highly increased in active VKC. Conclusion. A distinct “protein tear-print” characterizes VKC activity, confirming some previously reported factors and highlighting some new candidates common to quiescent and active states. Those candidates expressed in quiescent VKC might be considered as predictive indicators of VKC reactivation and/or exacerbation out-of-season. PMID:26989694

  16. Serum and synovial fluid lipidomic profiles predict obesity-associated osteoarthritis, synovitis, and wound repair

    Science.gov (United States)

    Wu, Chia-Lung; Kimmerling, Kelly A.; Little, Dianne; Guilak, Farshid

    2017-01-01

    High-fat diet-induced obesity is a major risk factor for osteoarthritis (OA) and diminished wound healing. The objective of this study was to determine the associations among serum and synovial fluid lipid levels with OA, synovitis, adipokine levels, and wound healing in a pre-clinical obese mouse model of OA. Male C57BL/6 J mice were fed either a low-fat (10% kcal) or one of three high-fat (HF, 60% kcal) diets rich in saturated fatty acids (SFAs), ω-6 or ω-3 polyunsaturated FAs (PUFAs). OA was induced by destabilization of the medial meniscus. Mice also received an ear punch for evaluating wound healing. Serum and synovial fluid were collected for lipidomic and adipokine analyses. We demonstrated that the serum levels of ω-3 PUFAs were negatively correlated with OA and wound size, but positively correlated with adiponectin levels. In contrast, most ω-6 PUFAs exhibited positive correlations with OA, impaired healing, and inflammatory adipokines. Interestingly, levels of pentadecylic acid (C15:0, an odd-chain SFA) and palmitoleic acid were inversely correlated with joint degradation. This study extends our understanding of the links of FAs with OA, synovitis and wound healing, and reports newly identified serum and synovial fluid FAs as predictive biomarkers of OA in obesity. PMID:28317846

  17. Prediction of Air Flow and Temperature Profiles Inside Convective Solar Dryer

    Directory of Open Access Journals (Sweden)

    Marian Vintilă

    2014-11-01

    Full Text Available Solar tray drying is an effective alternative for post-harvest processing of fruits and vegetables. Product quality and uniformity of the desired final moisture content are affected by the uneven air flow and temperature distribution inside the drying chamber. The purpose of this study is to numerically evaluate the operation parameters of a new indirect solar dryer having an appropriate design based on thermal uniformity inside the drying chamber, low construction costs and easy accessibility to resources needed for manufacture. The research was focused on both the investigation of different operation conditions and analysis of the influence of the damper position, which is incorporated into the chimney, on the internal cabinet temperature and air flow distribution. Numerical simulation was carried out with Comsol Multiphysics CFD commercial code using a reduced 2D domain model by neglecting any end effects from the side walls. The analysis of the coupled thermal-fluid model provided the velocity field, pressure distribution and temperature distribution in the solar collector and in the drying chamber when the damper was totally closed, half open and fully open and for different operation conditions. The predicted results were compared with measurements taken in-situ. With progressing computing power, it is conceivable that CFD will continue to provide explanations for more fluid flow, heat and mass transfer phenomena, leading to better equipment design and process control for the food industry.

  18. Cerebrospinal fluid cytokine profiles predict risk of early mortality and immune reconstitution inflammatory syndrome in HIV-associated cryptococcal meningitis.

    Directory of Open Access Journals (Sweden)

    Joseph N Jarvis

    2015-04-01

    Full Text Available Understanding the host immune response during cryptococcal meningitis (CM is of critical importance for the development of immunomodulatory therapies. We profiled the cerebrospinal fluid (CSF immune-response in ninety patients with HIV-associated CM, and examined associations between immune phenotype and clinical outcome. CSF cytokine, chemokine, and macrophage activation marker concentrations were assayed at disease presentation, and associations between these parameters and microbiological and clinical outcomes were examined using principal component analysis (PCA. PCA demonstrated a co-correlated CSF cytokine and chemokine response consisting primarily of Th1, Th2, and Th17-type cytokines. The presence of this CSF cytokine response was associated with evidence of increased macrophage activation, more rapid clearance of Cryptococci from CSF, and survival at 2 weeks. The key components of this protective immune-response were interleukin (IL-6 and interferon-γ, IL-4, IL-10 and IL-17 levels also made a modest positive contribution to the PC1 score. A second component of co-correlated chemokines was identified by PCA, consisting primarily of monocyte chemotactic protein-1 (MCP-1 and macrophage inflammatory protein-1α (MIP-1α. High CSF chemokine concentrations were associated with low peripheral CD4 cell counts and CSF lymphocyte counts and were predictive of immune reconstitution inflammatory syndrome (IRIS. In conclusion CSF cytokine and chemokine profiles predict risk of early mortality and IRIS in HIV-associated CM. We speculate that the presence of even minimal Cryptococcus-specific Th1-type CD4+ T-cell responses lead to increased recruitment of circulating lymphocytes and monocytes into the central nervous system (CNS, more effective activation of CNS macrophages and microglial cells, and faster organism clearance; while high CNS chemokine levels may predispose to over recruitment or inappropriate recruitment of immune cells to the CNS and

  19. Early second-trimester serum miRNA profiling predicts gestational diabetes mellitus.

    Directory of Open Access Journals (Sweden)

    Chun Zhao

    Full Text Available BACKGROUND: Gestational diabetes mellitus (GDM is one type of diabetes that presents during pregnancy and significantly increases the risk of a number of adverse consequences for the fetus and mother. The microRNAs (miRNA have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. However, no reported study investigates the associations between serum miRNA and GDM. METHODOLOGY/PRINCIPAL FINDINGS: We systematically used the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays to screen miRNAs in serum collected at 16-19 gestational weeks. The expression levels of three miRNAs (miR-132, miR-29a and miR-222 were significantly decreased in GDM women with respect to the controls in similar gestational weeks in our discovery evaluation and internal validation, and two miRNAs (miR-29a and miR-222 were also consistently validated in two-centric external validation sample sets. In addition, the knockdown of miR-29a could increase Insulin-induced gene 1 (Insig1 expression level and subsequently the level of Phosphoenolpyruvate Carboxy Kinase2 (PCK2 in HepG2 cell lines. CONCLUSIONS/SIGNIFICANCE: Serum miRNAs are differentially expressed between GDM women and controls and could be candidate biomarkers for predicting GDM. The utility of miR-29a, miR-222 and miR-132 as serum-based non-invasive biomarkers warrants further evaluation and optimization.

  20. Predictive potential of photoacoustic spectroscopy in breast tumor detection based on xenograft serum profiles

    Science.gov (United States)

    Priya, Mallika; Chandra, Subhas; Rao, Bola Sadashiva Satish; Ray, Satadru; Mahato, Krishna Kishore

    2015-02-01

    Breast cancer is the second most common cancer all over the world. Heterogeneity in breast cancer makes it a difficult task to detect with the existing serum markers at an early stage. With an aim to detect the disease early at the pre-malignant level, MCF-7 cells xenografts were developed using female nude mice and blood serum were extracted on days 0th, 10th, 15th & 20th post tumor cells injection (N=12 for each time point). Photoacoustic spectra were recorded on the serum samples at 281nm pulsed laser excitations. A total of 144 time domain spectra were recorded from 48 serum samples belonging to 4 different time points. These spectra were then converted into frequency domain (0-1250kHz) using MATLAB algorithms. Subsequently, seven features (mean, median, mode, variance, standard deviation, area under the curve & spectral residuals after 10th degree polynomial fit) were extracted from them and used for PCA. Further, using the first three Principal components (PCs) of the data, Linear Discriminate Analysis has been carried out. The performance of the analysis showed 82.64% accuracy in predicting various time points under study. Further, frequency-region wise analysis was also performed on the data and found 95 - 203.13 kHz region most suitable for the discrimination among the 4 time points. The analysis provided a clear discrimination in most of the spectral features under study suggesting that the photoacoustic technique has the potential to be a diagnostic tool for early detection of breast tumor development

  1. 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

  2. Transcription Profiles of Marker Genes Predict The Transdifferentiation Relationship between Eight Types of Liver Cell during Rat Liver Regeneration

    Directory of Open Access Journals (Sweden)

    Xiaguang Chen

    2015-07-01

    Full Text Available Objective: To investigate the transdifferentiation relationship between eight types of liver cell during rat liver regeneration (LR. Materials and Methods: 114 healthy Sprague-Dawley (SD rats were used in this experimental study. Eight types of liver cell were isolated and purified with percoll density gradient centrifugation and immunomagentic bead methods. Marker genes for eight types of cell were obtained by retrieving the relevant references and databases. Expression changes of markers for each cell of the eight cell types were measured using microarray. The relationships between the expression profiles of marker genes and transdifferentiation among liver cells were analyzed using bioinformatics. Liver cell transdifferentiation was predicted by comparing expression profiles of marker genes in different liver cells. Results: During LR hepatocytes (HCs not only express hepatic oval cells (HOC markers (including PROM1, KRT14 and LY6E, but also express biliary epithelial cell (BEC markers (including KRT7 and KRT19; BECs express both HOC markers (including GABRP, PCNA and THY1 and HC markers such as CPS1, TAT, KRT8 and KRT18; both HC markers (KRT18, KRT8 and WT1 and BEC markers (KRT7 and KRT19 were detected in HOCs. Additionally, some HC markers were also significantly upregulated in hepatic stellate cells ( HSCs, sinusoidal endothelial cells (SECs , Kupffer cells (KCs and dendritic cells (DCs, mainly at 6-72 hours post partial hepatectomy (PH. Conclusion: Our findings indicate that there is a mutual transdifferentiation relationship between HC, BEC and HOC during LR, and a tendency for HSCs, SECs, KCs and DCs to transdifferentiate into HCs.

  3. Evaluation of Uterine Biophysical Profile and to Assess its Role in Predicting Conception among Unexplained Primary Infertility Patients

    Directory of Open Access Journals (Sweden)

    Pooja Gupta

    2014-12-01

    Full Text Available Introduction: Infertility is a devastating disease which affects its victims at a very basic level the ability to reproduce. This can be divisive to the couples involved, their relatives and friends. The influence of infertility can be immense. There are a lot of medical and social consequences of infertility and the psychological sequelae are one of them. Affected patients and their families suffer from loss of esteem, disappointment and depression. Considering the immense effect of infertility on the life of not only the affected couples but also on their families and relatives the present study was conducted with following objective. Objective: To evaluate the Uterine Biophysical Profile and to assess its role in predicting the conception outcome in spontaneous cycles in patients with unexplained primary infertility. Material &Methods: A prospective observational study was conducted in the Department of Obstetrics and Gynaecology, U.P. Rural Institute of Medical Sciences & Research, Saifaion 55 women with unexplained primary infertility after standard diagnostic work up. Ultrasound (TVS measurement of all patients was performed in their midcycle of spontaneous cycle. The Uterine Biophysical Profile (UBP i.e. certain sonographic qualities of the uterus were noted during the normal mid-cycle of these patients. These included 7 parameters: Endometrial thickness in greatest AP dimension of 7 mm or greater (full-thickness measurement, a layered ("5 line" appearance to the endometrium, myometrial contractions causing a wave like motion of the endometrium, homogeneous myometrial echogenicity, uterine artery blood flow (as measured by PI, less than 3.0, blood flow within zone 3 using color doppler technique, myometrial blood flow seen on gray-scale examination. The Uterine Scoring System for Reproduction ("USSR" was used to evaluate the total score. Results: Among 55 unexplained primary infertility patients 24 i.e. 43.63% conceived by serial

  4. Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV

    Directory of Open Access Journals (Sweden)

    Izaskun Garrido

    2016-08-01

    Full Text Available Plasma stability is one of the obstacles in the path to the successful operation of fusion devices. Numerical control-oriented codes as it is the case of the widely accepted RZIp may be used within Tokamak simulations. The novelty of this article relies in the hierarchical development of a dynamic control loop. It is based on a current profile Model Predictive Control (MPC algorithm within a multiloop structure, where a MPC is developed at each step so as to improve the Proportional Integral Derivative (PID global scheme. The inner control loop is composed of a PID-based controller that acts over the Multiple Input Multiple Output (MIMO system resulting from the RZIp plasma model of the Tokamak à Configuration Variable (TCV. The coefficients of this PID controller are initially tuned using an eigenmode reduction over the passive structure model. The control action corresponding to the state of interest is then optimized in the outer MPC loop. For the sake of comparison, both the traditionally used PID global controller as well as the multiloop enhanced MPC are applied to the same TCV shot. The results show that the proposed control algorithm presents a superior performance over the conventional PID algorithm in terms of convergence. Furthermore, this enhanced MPC algorithm contributes to extend the discharge length and to overcome the limited power availability restrictions that hinder the performance of advanced tokamaks.

  5. Gene Expression Profiling to Predict Clinical Outcome of Breast Cancer: reproducing, analyzing and extending the Nature publication by vhVeer et al

    NARCIS (Netherlands)

    Li R.; Visser, H.M.

    2010-01-01

    Chemotherapy and hormonal therapy as adjuvant systemic therapies to inhibit breast cancer recurrence are not necessary for each patient. In Veer's paper "Gene expression profiling predicts clinical outcome of breast cancer" (Nature 2002, PMID: 11823860), they introduced a method based on DNA microa

  6. The Janus-faced nature of time spent on homework : Using latent profile analyses to predict academic achievement over a school year

    NARCIS (Netherlands)

    Flunger, Barbara; Trautwein, Ulrich; Nagengast, Benjamin; Lüdtke, Oliver; Niggli, Alois; Schnyder, Inge

    2015-01-01

    Homework time and achievement are only modestly associated, whereas homework effort has consistently been shown to positively predict later achievement. We argue that time spent on homework can be an important predictor of achievement when combined with measures of homework effort. Latent profile an

  7. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    Science.gov (United States)

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  8. A low TSH profile predicts olanzapine-induced weight gain and relief by adjunctive topiramate in healthy male volunteers.

    Science.gov (United States)

    Evers, Simon S; van Vliet, André; van Vugt, Barbara; Scheurink, Anton J W; van Dijk, Gertjan

    2016-04-01

    Second generation antipsychotics, like olanzapine (OLZ), have become the first line drug treatment for patients with schizophrenia. However, OLZ treatment is often associated with body weight (BW) gain and metabolic derangements. Therefore, the search for prospective markers for OLZ's negative side effects as well as adjunctive treatments to inhibit these has been of major interest. The aim of this study was to investigate in healthy male volunteers (age: 36 ± 11 years; BW: 84 ± 12 kg; BMI=25.5 ± 2.5) whether adjunctive topiramate (TPM) administration opposes OLZ-induced weight gain over the course of 14 days treatment. In addition, we investigated behavioral, endocrine and metabolic characteristics as underlying and potentially predictive factors for weight regulation and/or metabolic derangements associated with OLZ and TPM treatment. While adjunctive TPM indeed reduced OLZ-induced weight gain (PTPM. Using multiple regression analysis, BW gain was the key factor explaining metabolic disturbances (e.g., plasma insulin- LDL interaction: PTPM treatment, nor its circulating levels, contributed to variation observed in ΔBW. In a second multiple regression analysis, we observed that a low baseline thyrotropin profile (TSHAUC) before the start of drug treatment was associated with an increase in ΔBW over the course of drug treatment (PTPM treatment did attenuate OLZ induced BW gain (PTPM treatment blocking OLZ-induced ΔBW gain. Others have shown that OLZ-induced BW gain is associated with improvement in brief psychiatric rating scores (BPRS); adjunctive TPM treatment may be a solution specifically for those subjects susceptible to OLZ-induced rapid weight gain who-on a therapeutic level-benefit most of OLZ treatment.

  9. Mars Ozone Absorption Line Shapes from Infrared Heterodyne Spectra Applied to GCM-Predicted Ozone Profiles and to MEX/SPICAM Column Retrievals

    Science.gov (United States)

    Fast, Kelly E.; Kostiuk, T.; Annen, J.; Hewagama, T.; Delgado, J.; Livengood, T. A.; Lefevre, F.

    2008-01-01

    We present the application of infrared heterodyne line shapes of ozone on Mars to those produced by radiative transfer modeling of ozone profiles predicted by general circulation models (GCM), and to contemporaneous column abundances measured by Mars Express SPICAM. Ozone is an important tracer of photochemistry Mars' atmosphere, serving as an observable with which to test predictions of photochemistry-coupled GCMs. Infrared heterodyne spectroscopy at 9.5 microns with spectral resolving power >1,000,000 is the only technique that can directly measure fully-resolved line shapes of Martian ozone features from the surface of the Earth. Measurements were made with Goddard Space Flight Center's Heterodyne instrument for Planetary Wind And Composition (HIPWAC) at the NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii on February 21-24 2008 UT at Ls=35deg on or near the MEX orbital path. The HIPWAC observations were used to test GCM predictions. For example, a GCM-generated ozone profile for 60degN 112degW was scaled so that a radiative transfer calculation of its absorption line shape matched an observed HIPWAC absorption feature at the same areographic position, local time, and season. The RMS deviation of the model from the data was slightly smaller for the GCM-generated profile than for a line shape produced by a constant-with-height profile, even though the total column abundances were the same, showing potential for testing and constraining GCM ozone-profiles. The resulting ozone column abundance from matching the model to the HIPWAC line shape was 60% higher than that observed by SPICAM at the same areographic position one day earlier and 2.5 hours earlier in local time. This could be due to day-to-day, diurnal, or north polar region variability, or to measurement sensitivity to the ozone column and its distribution, and these possibilities will be explored. This work was supported by NASA's Planetary Astronomy Program.

  10. Ground-based remote sensing profiling and numerical weather prediction model to manage nuclear power plants meteorological surveillance in Switzerland

    Directory of Open Access Journals (Sweden)

    B. Calpini

    2011-08-01

    Full Text Available The meteorological surveillance of the four nuclear power plants in Switzerland is of first importance in a densely populated area such as the Swiss Plateau. The project "Centrales Nucléaires et Météorologie" CN-MET aimed at providing a new security tool based on one hand on the development of a high resolution numerical weather prediction (NWP model. The latter is providing essential nowcasting information in case of a radioactive release from a nuclear power plant in Switzerland. On the other hand, the model input over the Swiss Plateau is generated by a dedicated network of surface and upper air observations including remote sensing instruments (wind profilers and temperature/humidity passive microwave radiometers. This network is built upon three main sites ideally located for measuring the inflow/outflow and central conditions of the main wind field in the planetary boundary layer over the Swiss Plateau, as well as a number of surface automatic weather stations (AWS. The network data are assimilated in real-time into the fine grid NWP model using a rapid update cycle of eight runs per day (one forecast every three hours. This high resolution NWP model has replaced the former security tool based on in situ observations (in particular one meteorological mast at each of the power plants and a local dispersion model. It is used to forecast the dynamics of the atmosphere in the planetary boundary layer (typically the first 4 km above ground layer and over a time scale of 24 h. This tool provides at any time (e.g. starting at the initial time of a nuclear power plant release the best picture of the 24-h evolution of the air mass over the Swiss Plateau and furthermore generates the input data (in the form of simulated values substituting in situ observations required for the local dispersion model used at each of the nuclear power plants locations. This paper is presenting the concept and two validation studies as well as the results of an

  11. 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...

  12. Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

    Directory of Open Access Journals (Sweden)

    R. Larsson

    2015-10-01

    Full Text Available We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19–22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively and the expected profile errors at the affected altitudes (estimated to be around 5 K. For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K and smaller standard deviations (at below 0.4 K when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better

  13. Analysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells.

    Directory of Open Access Journals (Sweden)

    Victor Trevino

    Full Text Available Statistical modelling, in combination with genome-wide expression profiling techniques, has demonstrated that the molecular state of the tumour is sufficient to infer its pathological state. These studies have been extremely important in diagnostics and have contributed to improving our understanding of tumour biology. However, their importance in in-depth understanding of cancer patho-physiology may be limited since they do not explicitly take into consideration the fundamental role of the tissue microenvironment in specifying tumour physiology. Because of the importance of normal cells in shaping the tissue microenvironment we formulate the hypothesis that molecular components of the profile of normal epithelial cells adjacent the tumour are predictive of tumour physiology. We addressed this hypothesis by developing statistical models that link gene expression profiles representing the molecular state of adjacent normal epithelial cells to tumour features in prostate cancer. Furthermore, network analysis showed that predictive genes are linked to the activity of important secreted factors, which have the potential to influence tumor biology, such as IL1, IGF1, PDGF BB, AGT, and TGFβ.

  14. Evaluation of models to predict the stoichiometry of volatile fatty acid profiles in rumen fluid of lactating Holstein cows

    NARCIS (Netherlands)

    Morvay, Y.; Bannink, A.; France, J.; Kebreab, E.; Dijkstra, J.

    2011-01-01

    Volatile fatty acids (VFA), produced in the rumen by microbial fermentation, are the main energy source for ruminants. The VFA profile, particularly the nonglucogenic (acetate, Ac; butyrate, Bu) to glucogenic (propionate, Pr) VFA ratio (NGR), is associated with effects on methane production, milk co

  15. The affective profiles, psychological well-being, and harmony: environmental mastery and self-acceptance predict the sense of a harmonious life

    Directory of Open Access Journals (Sweden)

    Danilo Garcia

    2014-02-01

    explained by the dimensions of psychological well-being within the four affective profiles. Specifically, harmony in life was significantly predicted by environmental mastery and self-acceptance across all affective profiles. However, for the low affective group high purpose in life predicted low levels of harmony in life.Conclusions. The results demonstrated that affective profiles systematically relate to psychological well-being and harmony in life. Notably, individuals categorised as self-fulfilling tended to report higher levels of both psychological well-being and harmony in life when compared with the other profiles. Meanwhile individuals in the self-destructive group reported the lowest levels of psychological well-being and harmony when compared with the three other profiles. It is proposed that self-acceptance and environmental acceptance might enable individuals to go from self-destructive to a self-fulfilling state that also involves harmony in life.

  16. Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

    OpenAIRE

    Dijkstra, J.; Kebreab, E; Mills, J.A.N.; Pellikaan, W.F.; López, S.; Bannink, A; France, J.

    2007-01-01

    Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of t...

  17. Segmenting by risk perceptions: predicting young adults' genetic-belief profiles with health and opinion-leader covariates.

    Science.gov (United States)

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

    2014-01-01

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

  18. Prediction of the feeding background of Iberian pigs using the fatty acid profile of subcutaneous, muscle and hepatic fat.

    Science.gov (United States)

    Ruiz, J; Cava, R; Antequera, T; Martín, L; Ventanas, J; López-Bote, C J

    1998-06-01

    Thirty Iberian pigs weighing 95 kg were randomly distributed into three groups of 10 animals each and fattened in three traditional management systems ['montanera' (MO), fed extensively on acorns, 'cebo' (CE) fed on a commercial diet and 'recebo' (RE), fed on acorns and a commercial diet]. Fatty acids from the Masseter muscle, lard and liver were analysed. In the lard, fatty acid profiles from MO and RE pigs presented minor differences; however, in the liver, RE pigs showed differences to MO pigs in most of the fatty acids studied. This suggests that the muscle and especially the liver fatty acid profile reflects the feeding regime during the last phase of feeding, while the lard reflects longer term differences.

  19. Predicting nicotine dependence profiles among adolescent smokers: the roles of personal and social-environmental factors in a longitudinal framework

    OpenAIRE

    2012-01-01

    Abstract Background Although several studies have reported that symptoms of nicotine dependence can occur after limited exposure to smoking, the majority of research on nicotine dependence has focused on adult smokers. Insufficient knowledge exists regarding the epidemiology and aetiology of nicotine dependence among adolescent smokers. The objective of the present study is to identify the effects of theoretically driven social and individual predictors of nicotine dependence symptom profiles...

  20. Predicting nicotine dependence profiles among adolescent smokers: The roles of personal and social-environmental factors in a longitudinal framework

    OpenAIRE

    2012-01-01

    Background Although several studies have reported that symptoms of nicotine dependence can occur after limited exposure to smoking, the majority of research on nicotine dependence has focused on adult smokers. Insufficient knowledge exists regarding the epidemiology and aetiology of nicotine dependence among adolescent smokers. The objective of the present study is to identify the effects of theoretically driven social and individual predictors of nicotine dependence symptom profiles in a pop...

  1. Predicting the liquefaction phenomena from shear velocity profiling: Empirical approach to 6.3 Mw, May 2006 Yogyakarta earthquake

    Energy Technology Data Exchange (ETDEWEB)

    Hartantyo, Eddy, E-mail: hartantyo@ugm.ac.id [PhD student, Physics Department, FMIPA, UGM. Sekip Utara Yogyakarta 55281 Indonesia (Indonesia); Brotopuspito, Kirbani S.; Sismanto; Waluyo [Geophysics Laboratory, FMIPA, Universitas Gadjah Mada, Sekip Utara Yogyakarta 55281 (Indonesia)

    2015-04-24

    The liquefactions phenomena have been reported after a shocking 6.5Mw earthquake hit Yogyakarta province in the morning at 27 May 2006. Several researchers have reported the damage, casualties, and soil failure due to the quake, including the mapping and analyzing the liquefaction phenomena. Most of them based on SPT test. The study try to draw the liquefaction susceptibility by means the shear velocity profiling using modified Multichannel Analysis of Surface Waves (MASW). This paper is a preliminary report by using only several measured MASW points. The study built 8-channel seismic data logger with 4.5 Hz geophones for this purpose. Several different offsets used to record the high and low frequencies of surface waves. The phase-velocity diagrams were stacked in the frequency domain rather than in time domain, for a clearer and easier dispersion curve picking. All codes are implementing in Matlab. From these procedures, shear velocity profiling was collected beneath each geophone’s spread. By mapping the minimum depth of shallow water table, calculating PGA with soil classification, using empirical formula for saturated soil weight from shear velocity profile, and calculating CRR and CSR at every depth, the liquefaction characteristic can be identify in every layer. From several acquired data, a liquefiable potential at some depth below water table was obtained.

  2. Profiling cancer

    DEFF Research Database (Denmark)

    Ciro, Marco; Bracken, Adrian P; Helin, Kristian

    2003-01-01

    In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

  3. Changes in rat urinary porphyrin profiles predict the magnitude of the neurotoxic effects induced by a mixture of lead, arsenic and manganese.

    Science.gov (United States)

    Andrade, Vanda; Mateus, M Luísa; Batoréu, M Camila; Aschner, Michael; Marreilha dos Santos, A P

    2014-12-01

    The neurotoxic metals lead (Pb), arsenic (As) and manganese (Mn) are ubiquitous contaminants occurring as mixtures in environmental settings. The three metals may interfere with enzymes of the heme bioshyntetic pathway, leading to excessive porphyrin accumulation, which per se may trigger neurotoxicity. Given the multi-mechanisms associated with metal toxicity, we posited that a single biomarker is unlikely to predict neurotoxicity that is induced by a mixture of metals. Our objective was to evaluate the ability of a combination of urinary porphyrins to predict the magnitude of motor activity impairment induced by a mixture of Pb/As/Mn. Five groups of Wistar rats were treated for 8 days with Pb (5mg/kg), As (60 mg/L) or Mn (10mg/kg), and the 3-metal mixture (same doses as the single metals) along with a control group. Motor activity was evaluated after the administration of the last dose and 24-hour (h) urine was also collected after the treatments. Porphyrin profiles were determined both in the urine and brain. Rats treated with the metal-mixture showed a significant decrease in motor parameters compared with controls and the single metal-treated groups. Both brain and urinary porphyrin levels, when combined and analyzed by multiple linear regressions, were predictable of motor activity (p<0.05). The magnitude of change in urinary porphyrin profiles was consistent with the greatest impairments in motor activity as determined by receiver operating characteristic (ROC) curves, with a sensitivity of 88% and a specificity of 96%. Our work strongly suggests that the use of a linear combination of urinary prophyrin levels accurately predicts the magnitude of motor impairments in rats that is induced by a mixture of Pb, As and Mn.

  4. Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

    NARCIS (Netherlands)

    Dijkstra, J.; Kebreab, E.; Mills, J.A.N.; Pellikaan, W.F.; López, S.; Bannink, A.; France, J.

    2007-01-01

    Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product compositi

  5. Predicting sickness impact profile at six months after stroke: further results from the European multi-center CERISE study

    NARCIS (Netherlands)

    Stummer, C.A.; Verheyden, G.; Putman, K.; Jenni, W.; Schupp, W.; Wit, L. De

    2015-01-01

    PURPOSE: To develop prognostic models and equations for predicting participation at six months after stroke. METHODS: This European prospective cohort study recruited 532 consecutive patients from four rehabilitation centers. Participation was assessed at six months after stroke with the Sickness Im

  6. Immunohistochemical profiling of caspase signaling pathways predicts clinical response to chemotherapy in primary nodal diffuse large B-cell lymphomas.

    NARCIS (Netherlands)

    Muris, J.J.; Cillessen, S.A.; Vos, W.; Houdt, I.S. van; Kummer, J.A.; Krieken, J.H.J.M. van; Jiwa, N.M.; Jansen, P.A.M.; Kluin-Nelemans, H.C.; Ossenkoppele, G.J.; Gundy, C.; Meijer, C.J.M.; Oudejans, J.J.

    2005-01-01

    We used biopsy specimens of primary nodal diffuse large B-cell lymphoma (DLBCL) to investigate whether the inhibition of caspase 8 and/or 9 apoptosis signaling pathways predicts clinical outcome. Expression levels of cellular FLICE inhibitory protein (c-Flip) and numbers of active caspase 3-positive

  7. Immunohistochemical profiling of caspase signaling pathways predicts clinical response to chemotherapy in primary nodal diffuse large B-cell lymphomas

    NARCIS (Netherlands)

    Muris, JJF; Cillessen, SAGM; Vos, W; van Houdt, IS; Kummer, JA; van Krieken, JHJM; Jiwa, NM; Jansen, PM; Kluin-Nelemans, HC; Ossenkoppele, GJ; Gundy, C; Meijer, CJLM; Oudejans, JJ

    2005-01-01

    We used biopsy specimens of primary nodal diffuse large B-cell lymphoma (DLBCL) to investigate whether the inhibition of caspase 8 and/or 9 apoplosis signaling pathways predicts clinical outcome. Expression levels of cellular FLICE inhibitory protein (c-Flip) and numbers of active caspase 3-positive

  8. Accessibility and Reproducibility of Stable High-qmin Steady-State Scenarios by q-profile+βN Model Predictive Control

    Science.gov (United States)

    Schuster, E.; Wehner, W.; Holcomb, C. T.; Victor, B.; Ferron, J. R.; Luce, T. C.

    2016-10-01

    The capability of combined q-profile and βN control to enable access to and repeatability of steady-state scenarios for qmin > 1.4 discharges has been assessed in DIII-D experiments. To steer the plasma to the desired state, model predictive control (MPC) of both the q-profile and βN numerically solves successive optimization problems in real time over a receding time horizon by exploiting efficient quadratic programming techniques. A key advantage of this control approach is that it allows for explicit incorporation of state/input constraints to prevent the controller from driving the plasma outside of stability/performance limits and obtain, as closely as possible, steady state conditions. The enabler of this feedback-control approach is a control-oriented model capturing the dominant physics of the q-profile and βN responses to the available actuators. Experiments suggest that control-oriented model-based scenario planning in combination with MPC can play a crucial role in exploring stability limits of scenarios of interest. Supported by the US DOE under DE-SC0010661.

  9. Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience

    Directory of Open Access Journals (Sweden)

    Paolo Bellavista

    2015-07-01

    Full Text Available Nowadays, sensor-rich smartphones potentially enable the harvesting of huge amounts of valuable sensing data in urban environments, by opportunistically involving citizens to play the role of mobile virtual sensors to cover Smart City areas of interest. This paper proposes an in-depth study of the challenging technical issues related to the efficient assignment of Mobile Crowd Sensing (MCS data collection tasks to volunteers in a crowdsensing campaign. In particular, the paper originally describes how to increase the effectiveness of the proposed sensing campaigns through the inclusion of several new facilities, including accurate participant selection algorithms able to profile and predict user mobility patterns, gaming techniques, and timely geo-notification. The reported results show the feasibility of exploiting profiling trends/prediction techniques from volunteers’ behavior; moreover, they quantitatively compare different MCS task assignment strategies based on large-scale and real MCS data campaigns run in the ParticipAct living lab, an ongoing MCS real-world experiment that involved more than 170 students of the University of Bologna for more than one year.

  10. [DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer].

    Science.gov (United States)

    Kwiatkowski, Przemysław; Wierzbicki, Piotr; Kmieć, Andrzej; Godlewski, Janusz

    2012-06-11

     Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations. Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment. The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

  11. Proteomic profiling of pretreatment serum from HIV-infected patients identifies candidate markers predictive of lymphoma development

    DEFF Research Database (Denmark)

    Vase, Maja Ølholm; Ludvigsen, Maja; Bendix, Knud;

    2016-01-01

    Objective: HIV-infected individuals have an increased risk of developing lymphoma. We sought to identify markers predictive of lymphoma development by comparing protein expression patterns in serum obtained at the time of HIV diagnosis from patients who later developed malignant lymphoma or benign...... protein spots were detected. Using principal components analysis, spots containing immunoglobulin J chain, apolipoprotein A-I, procollagen C-endopeptidase enhancer-1 and complement C4-A were associated with lymphoma development (P...

  12. Intensive serial biomarker profiling for the prediction of neutropenic fever in patients with hematologic malignancies undergoing chemotherapy: a pilot study

    Directory of Open Access Journals (Sweden)

    Steven M. Chan

    2014-06-01

    Full Text Available Neutropenic fever (NF is a life-threatening complication of myelosuppressive chemotherapy in patients with hematologic malignancies and triggers the administration of broad-spectrum antimicrobials. The ability to accurately predict NF would permit initiation of antimicrobials earlier in the course of infection with the goal of decreasing morbid complications and progression to septic shock and death. Changes in the blood level of inflammatory biomarkers may precede the occurrence of NF. To identify potential biomarkers for the prediction of NF, we performed serial meas- urements of nine biomarkers [C-reactive protein (CRP, protein C, interleukin (IL-6, IL-8, IL-10, IL-1β, tumor necrosis factor-α, monocyte chemotactic protein-1, and intercellular adhesion molecule-1] using a multiplex ELISA array platform every 6-8 hours in patients undergoing myelosuppressive chemotherapy for hematologic malignancies. We found that the blood levels of IL-6 and CRP increased significantly 24 to 48 hours prior to the onset of fever. In addition, we showed that frequent biomarker monitoring is feasible using a bedside micro sample test device. The results of this pilot study suggest that serial monitoring of IL-6 and CRP levels using a bedside device may be useful in the prediction of NF. Prospective studies involving a larger cohort of patients to validate this observation are warranted. This trial is registered at ClinicalTrials.gov (NCT01144793.

  13. Transcriptional profiling of human brain endothelial cells reveals key properties crucial for predictive in vitro blood-brain barrier models.

    Directory of Open Access Journals (Sweden)

    Eduard Urich

    Full Text Available Brain microvascular endothelial cells (BEC constitute the blood-brain barrier (BBB which forms a dynamic interface between the blood and the central nervous system (CNS. This highly specialized interface restricts paracellular diffusion of fluids and solutes including chemicals, toxins and drugs from entering the brain. In this study we compared the transcriptome profiles of the human immortalized brain endothelial cell line hCMEC/D3 and human primary BEC. We identified transcriptional differences in immune response genes which are directly related to the immortalization procedure of the hCMEC/D3 cells. Interestingly, astrocytic co-culturing reduced cell adhesion and migration molecules in both BECs, which possibly could be related to regulation of immune surveillance of the CNS controlled by astrocytic cells within the neurovascular unit. By matching the transcriptome data from these two cell lines with published transcriptional data from freshly isolated mouse BECs, we discovered striking differences that could explain some of the limitations of using cultured BECs to study BBB properties. Key protein classes such as tight junction proteins, transporters and cell surface receptors show differing expression profiles. For example, the claudin-5, occludin and JAM2 expression is dramatically reduced in the two human BEC lines, which likely explains their low transcellular electric resistance and paracellular leakiness. In addition, the human BEC lines express low levels of unique brain endothelial transporters such as Glut1 and Pgp. Cell surface receptors such as LRP1, RAGE and the insulin receptor that are involved in receptor-mediated transport are also expressed at very low levels. Taken together, these data illustrate that BECs lose their unique protein expression pattern outside of their native environment and display a more generic endothelial cell phenotype. A collection of key genes that seems to be highly regulated by the local

  14. AQA - Air Quality model for Austria: comparison of ALADIN and ALARO forecasts with observed meteorological profiles and PM10 predictions with CAMx

    Science.gov (United States)

    Hirtl, M.; Krüger, B. C.; Kaiser, A.

    2009-09-01

    In AQA, Air Quality model for Austria, the regional weather forecast model ALADIN-Austria of the Central Institute for Meteorology and Geodynamics (ZAMG) is used in combination with the chemical transport model CAMx (www.camx.com) to conduct forecasts of gaseous and particulate air pollutants over Austria. The forecasts which are done in cooperation with the University of Natural Resources and Applied Life Sciences in Vienna (BOKU) are supported by the regional governments since 2005. In the current model version AQA uses the operational meteorological forecasts conducted with ALADIN which has a horizontal resolution of 9.7 km. Since 2008 the higher resolved ALARO is also available at the ZAMG. It has a horizontal resolution of 4.9 km and models the PBL with more vertical layers than ALADIN. ALARO also uses more complex algorithms to calculate precipitation, radiation and TKE. Another advantage of ALARO concerning the chemical modelling with CAMx is that additionally to the higher resolved meteorological forecasts it is possible to use finer emission inventories which are available for Austria. From 2006 to 2007 a SODAR-RASS of the ZAMG was operated in the north-eastern Austrian flat lands (Kittsee). In this study the measured vertical profiles of wind and temperature are compared with the model predictions. The evaluation is conducted for an episode in January 2007 when high PM10 concentrations were measured at the air quality station Kittsee. Analysis of the RASS-temperature-profiles show that during this episode a strong nocturnal inversion developed at the investigated area. The ability of the models ALADIN and ALARO to predict this complex meteorological condition is investigated. Both models are also used as meteorological driver for the chemical dispersion model CAMx and the results of predicted PM10 concentrations are compared to air quality measurements.

  15. Profiling of volatile organic compounds in exhaled breath as a strategy to find early predictive signatures of asthma in children.

    Directory of Open Access Journals (Sweden)

    Agnieszka Smolinska

    Full Text Available Wheezing is one of the most common respiratory symptoms in preschool children under six years old. Currently, no tests are available that predict at early stage who will develop asthma and who will be a transient wheezer. Diagnostic tests of asthma are reliable in adults but the same tests are difficult to use in children, because they are invasive and require active cooperation of the patient. A non-invasive alternative is needed for children. Volatile Organic Compounds (VOCs excreted in breath could yield such non-invasive and patient-friendly diagnostic. The aim of this study was to identify VOCs in the breath of preschool children (inclusion at age 2-4 years that indicate preclinical asthma. For that purpose we analyzed the total array of exhaled VOCs with Gas Chromatography time of flight Mass Spectrometry of 252 children between 2 and 6 years of age. Breath samples were collected at multiple time points of each child. Each breath-o-gram contained between 300 and 500 VOCs; in total 3256 different compounds were identified across all samples. Using two multivariate methods, Random Forests and dissimilarity Partial Least Squares Discriminant Analysis, we were able to select a set of 17 VOCs which discriminated preschool asthmatic children from transient wheezing children. The correct prediction rate was equal to 80% in an independent test set. These VOCs are related to oxidative stress caused by inflammation in the lungs and consequently lipid peroxidation. In conclusion, we showed that VOCs in the exhaled breath predict the subsequent development of asthma which might guide early treatment.

  16. Alkaloid metabolite profiles by GC/MS and acetylcholinesterase inhibitory activities with binding-mode predictions of five Amaryllidaceae plants.

    Science.gov (United States)

    Cortes, Natalie; Alvarez, Rafael; Osorio, Edison H; Alzate, Fernando; Berkov, Strahil; Osorio, Edison

    2015-01-01

    Acetylcholinesterase (AChE) enzymatic inhibition is an important target for the management of Alzheimer disease (AD) and AChE inhibitors are the mainstay drugs for its treatment. In order to discover new sources of potent AChE inhibitors, a combined strategy is presented based on AChE-inhibitory activity and chemical profiles by GC/MS, together with in silico studies. The combined strategy was applied on alkaloid extracts of five Amaryllidaceae species that grow in Colombia. Fifty-seven alkaloids were detected using GC/MS, and 21 of them were identified by comparing their mass-spectral fragmentation patterns with standard reference spectra in commercial and private library databases. The alkaloid extracts of Zephyranthes carinata exhibited a high level of inhibitory activity (IC50 = 5.97 ± 0.24 μg/mL). Molecular modeling, which was performed using the structures of some of the alkaloids present in this extract and the three-dimensional crystal structures of AChE derived from Torpedo californica, disclosed their binding configuration in the active site of this AChE. The results suggested that the alkaloids 3-epimacronine and lycoramine might be of interest for AChE inhibition. Although the galanthamine group is known for its potential utility in treating AD, the tazettine-type alkaloids should be evaluated to find more selective compounds of potential benefit for AD.

  17. Identifying Gene Regulatory Networks in Arabidopsis by In Silico Prediction, Yeast-1-Hybrid, and Inducible Gene Profiling Assays.

    Science.gov (United States)

    Sparks, Erin E; Benfey, Philip N

    2016-01-01

    A system-wide understanding of gene regulation will provide deep insights into plant development and physiology. In this chapter we describe a threefold approach to identify the gene regulatory networks in Arabidopsis thaliana that function in a specific tissue or biological process. Since no single method is sufficient to establish comprehensive and high-confidence gene regulatory networks, we focus on the integration of three approaches. First, we describe an in silico prediction method of transcription factor-DNA binding, then an in vivo assay of transcription factor-DNA binding by yeast-1-hybrid and lastly the identification of co-expression clusters by transcription factor induction in planta. Each of these methods provides a unique tool to advance our understanding of gene regulation, and together provide a robust model for the generation of gene regulatory networks.

  18. Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

    Directory of Open Access Journals (Sweden)

    Mark Burton

    2012-01-01

    Full Text Available Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. However, method comparisons in cross-study datasets are very scarce. This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or across datasets on similar or dissimilar microarray platforms. Combining classification results from seven classifiers into one voting decision performed significantly better during internal validation as well as external validation in similar microarray platforms than the underlying classification methods. When validating between different microarray platforms, random forest, another voting-based method, proved to be the best performing method. We conclude that voting based classifiers provided an advantage with respect to classifying metastasis outcome in breast cancer patients.

  19. Multiplex cytokine profile from dengue patients: MIP-1beta and IFN-gamma as predictive factors for severity

    Directory of Open Access Journals (Sweden)

    Bozza Patricia T

    2008-06-01

    Full Text Available Abstract Background Dengue virus pathogenesis is not yet fully understood and the identification of patients at high risk for developing severe disease forms is still a great challenge in dengue patient care. During the present study, we evaluated prospectively the potential of cytokines present in plasma from patients with dengue in stratifying disease severity. Methods Seventeen-cytokine multiplex fluorescent microbead immunoassay was used for the simultaneous detection in 59 dengue patients. GLM models using bimodal or Gaussian family were determined in order to associate cytokines with clinical manifestations and laboratory diagnosis. Results IL-1β, IFN-γ, IL-4, IL-6, IL-13, IL-7 and GM-CSF were significantly increased in patients with severe clinical manifestations (severe dengue when compared to mild disease forms (mild dengue. In contrast, increased MIP-1β levels were observed in patients with mild dengue. MIP-1β was also associated with CD56+NK cell circulating rates. IL-1β, IL-8, TNF-α and MCP-1 were associated with marked thrombocytopenia. Increased MCP-1 and GM-CSF levels correlated with hypotension. Moreover, MIP-1β and IFN-γ were independently associated with both dengue severity and disease outcome. Conclusion Our data demonstrated that the use of a multiple cytokine assay platform was suitable for identifying distinct cytokine profiles associated with the dengue clinical manifestations and severity. MIP-β is indicated for the first time as a good prognostic marker in contrast to IFN-γ that was associated with disease severity.

  20. Predictive value of a profile of routine blood measurements on mortality in older persons in the general population: the Leiden 85-plus Study.

    Directory of Open Access Journals (Sweden)

    Anne H van Houwelingen

    Full Text Available BACKGROUND: Various questionnaires and performance tests predict mortality in older people. However, most are heterogeneous, laborious and a validated consensus index is not available yet. Since most older people are regularly monitored by laboratory tests, we compared the predictive value of a profile of seven routine laboratory measurements on mortality in older persons in the general population with other predictors of mortality; gait speed and disability in instrumental activities of daily living (IADL. METHODOLOGY/PRINCIPAL FINDINGS: Within the Leiden 85-plus Study, a prospective population-based study, we followed 562 participants aged 85 years for mortality over five years. At baseline (age 85 years high-density lipoprotein cholesterol, albumin, alanine transaminase, hemoglobin, creatinin clearance, C-reactive protein and homocysteine were measured. Participants were stratified based on their number of laboratory abnormalities (0, 1, 2-4 and 5-7. The predictive capacity was compared with gait speed (6-meter walking test and disability in IADL (Groningen Activity Restriction Scale by C-statistics. At baseline, 418 (74% 85-year old participants had at least one laboratory abnormality. All cause mortality risk increased with increasing number of laboratory abnormalities to a hazard ratio of 5.64 [95% CI 3.49-9.12] for those with 5-7 laboratory abnormalities (p<0.001 compared to those without abnormalities. The c-statistic was 0.66 [95% CI 0.59-0.69], similar to that of gait speed and disability in IADL. CONCLUSIONS/SIGNIFICANCE: In the general population of oldest old, the number of abnormalities in seven routine laboratory measurements predicts five-year mortality as accurately as gait speed and IADL disability.

  1. Visceral adiposity index (VAI is predictive of an altered adipokine profile in patients with type 2 diabetes.

    Directory of Open Access Journals (Sweden)

    Marco C Amato

    Full Text Available AIMS: Although there is still no clear definition of "adipose tissue dysfunction" or ATD, the identification of a clinical marker of altered fat distribution and function may provide the needed tools for early identification of a condition of cardiometabolic risk. Our aim was to evaluate the correlations among various anthropometric indices [BMI, Waist Circumference (WC, Hip Circumference (HC, Waist/Hip ratio (WHR, Body Adiposity Index (BAI and Visceral adiposity Index (VAI] and several adipocytokines [Visfatin, Resistin, Leptin, Soluble leptin receptors (sOB-R, Adiponectin, Ghrelin, Adipsin, PAI-1, vascular endothelial growth factor (VEGF, Hepatocyte growth factor (HGF TNF-α, hs-CRP, IL-6, IL-18] in patients with type 2 diabetes (DM2. MATERIALS AND METHODS: Ninety-one DM2 patients (age: 65.25 ± 6.38 years; 42 men and 49 women in stable treatment for the last six months with metformin in monotherapy (1.5-2 g/day were cross-sectionally studied. Clinical, anthropometric, and metabolic parameters were evaluated. Serum adipocytokine levels were assayed with Luminex based kits. RESULTS: At the Pearson's correlation, among all the indices investigated, VAI showed a significant correlation with almost all adipocytokines analyzed [Visfatin, Resistin and hsCRP (all p<0.001; Adiponectin, sOb-R, IL-6, IL-18, HGF (all p<0.010; Ghrelin and VEGF (both p<0.05]. Through a two-step cluster analysis, 55 patients were identified with the most altered adipocytokine profile (patients with ATD. At a ROC analysis, VAI showed the highest C-statistic [0.767 (95% CI 0.66-0.84] of all the indices. CONCLUSIONS: Our study suggests that the VAI, among the most common indexes of adiposity assessment, shows the best correlation with the best known adipocytokines and cardiometabolic risk serum markers. Although to date we are still far from clearly identifying an ATD, the VAI would be an easy tool for clearly mirroring a condition of cardiometabolic risk, in the absence of an

  2. MicroRNA profiling predicts survival in anti-EGFR treated chemorefractory metastatic colorectal cancer patients with wild-type KRAS and BRAF.

    Science.gov (United States)

    Mosakhani, Neda; Lahti, Leo; Borze, Ioana; Karjalainen-Lindsberg, Marja-Liisa; Sundström, Jari; Ristamäki, Raija; Osterlund, Pia; Knuutila, Sakari; Sarhadi, Virinder Kaur

    2012-11-01

    Anti-EGFR monoclonal antibodies (anti-EGFRmAb) serve in the treatment of metastatic colorectal cancer (mCRC), but patients with a mutation in KRAS/BRAF and nearly one-half of those without the mutation fail to respond. We performed microRNA (miRNA) analysis to find miRNAs predicting anti-EGFRmAb efficacy. Of the 99 mCRC patients, we studied differential miRNA expression by microarrays from primary tumors of 33 patients who had wild-type KRAS/BRAF and third- to sixth-line anti-EGFRmAb treatment, with/without irinotecan. We tested the association of each miRNA with overall survival (OS) by the Cox proportional hazards regression model. Significant miR-31* up-regulation and miR-592 down-regulation appeared in progressive disease versus disease control. miR-31* expression and down-regulation of its target genes SLC26A3 and ATN1 were verified by quantitative reverse transcriptase polymerase chain reaction. Clustering of patients based on miRNA expression revealed a significant difference in OS between patient clusters. Members of the let-7 family showed significant up-regulation in the patient cluster with poor OS. Additionally, miR-140-5p up-regulation and miR-1224-5p down-regulation were significantly associated with poor OS in both cluster analysis and the Cox proportional hazards regression model. In mCRC patients with wild-type KRAS/BRAF, miRNA profiling can efficiently predict the benefits of anti-EGFRmAb treatment. Larger series of patients are necessary for application of these miRNAs as predictive/prognostic markers.

  3. RGS2 expression predicts amyloid-β sensitivity, MCI and Alzheimer's disease: genome-wide transcriptomic profiling and bioinformatics data mining

    Science.gov (United States)

    Hadar, A; Milanesi, E; Squassina, A; Niola, P; Chillotti, C; Pasmanik-Chor, M; Yaron, O; Martásek, P; Rehavi, M; Weissglas-Volkov, D; Shomron, N; Gozes, I; Gurwitz, D

    2016-01-01

    Alzheimer's disease (AD) is the most frequent cause of dementia. Misfolded protein pathological hallmarks of AD are brain deposits of amyloid-β (Aβ) plaques and phosphorylated tau neurofibrillary tangles. However, doubts about the role of Aβ in AD pathology have been raised as Aβ is a common component of extracellular brain deposits found, also by in vivo imaging, in non-demented aged individuals. It has been suggested that some individuals are more prone to Aβ neurotoxicity and hence more likely to develop AD when aging brains start accumulating Aβ plaques. Here, we applied genome-wide transcriptomic profiling of lymphoblastoid cells lines (LCLs) from healthy individuals and AD patients for identifying genes that predict sensitivity to Aβ. Real-time PCR validation identified 3.78-fold lower expression of RGS2 (regulator of G-protein signaling 2; P=0.0085) in LCLs from healthy individuals exhibiting high vs low Aβ sensitivity. Furthermore, RGS2 showed 3.3-fold lower expression (P=0.0008) in AD LCLs compared with controls. Notably, RGS2 expression in AD LCLs correlated with the patients' cognitive function. Lower RGS2 expression levels were also discovered in published expression data sets from postmortem AD brain tissues as well as in mild cognitive impairment and AD blood samples compared with controls. In conclusion, Aβ sensitivity phenotyping followed by transcriptomic profiling and published patient data mining identified reduced peripheral and brain expression levels of RGS2, a key regulator of G-protein-coupled receptor signaling and neuronal plasticity. RGS2 is suggested as a novel AD biomarker (alongside other genes) toward early AD detection and future disease modifying therapeutics. PMID:27701409

  4. Comparison of percentage body fat and body mass index for the prediction of inflammatory and atherogenic lipid risk profiles in elderly women

    Directory of Open Access Journals (Sweden)

    Funghetto SS

    2015-01-01

    Full Text Available Silvana Schwerz Funghetto,1 Alessandro de Oliveira Silva,2 Nuno Manuel Frade de Sousa,3 Marina Morato Stival,1 Ramires Alsamir Tibana,4 Leonardo Costa Pereira,1 Marja Letícia Chaves Antunes,1 Luciano Ramos de Lima,1 Jonato Prestes,4 Ricardo Jacó Oliveira,1 Maurílio Tiradentes Dutra,2 Vinícius Carolino Souza,1,4 Dahan da Cunha Nascimento,4 Margô Gomes de Oliveira Karnikowski1 1University of Brasília (UnB, Brasília, DF, Brazil; 2Center University of Brasilia (UNICEUB, Brasilia, DF, Brazil; 3Laboratory of Exercise Physiology, Faculty Estácio de Sá of Vitória, ES, Brazil; 4Catholic University of Brasília, Brasília, DF, Brazil Objective: To compare the clinical classification of the body mass index (BMI and percentage body fat (PBF for the prediction of inflammatory and atherogenic lipid profile risk in older women.Method: Cross-sectional analytical study with 277 elderly women from a local community in the Federal District, Brazil. PBF and fat-free mass (FFM were determined by dual energy X-ray absorptiometry. The investigated inflammatory parameters were interleukin 6 and C-reactive protein.Results: Twenty-five percent of the elderly women were classified as normal weight, 50% overweight, and 25% obese by the BMI. The obese group had higher levels of triglycerides and very low-density lipoproteins than did the normal weight group (P≤0.05 and lower levels of high-density lipoproteins (HDL than did the overweight group (P≤0.05. According to the PBF, 49% of the elderly women were classified as eutrophic, 28% overweight, and 23% obese. In the binomial logistic regression analyses including age, FFM, and lipid profile, only FFM (odds ratio [OR]=0.809, 95% confidence interval [CI]: 0.739–0.886; P<0.0005 proved to be a predictor of reaching the eutrophic state by the BMI. When the cutoff points of PBF were used for the classification, FFM (OR=0.903, CI=0.884–0.965; P=0.003 and the total cholesterol/HDL ratio (OR=0.113, CI=0.023–0

  5. Geographic Profiling: Knowledge Through Prediction

    Science.gov (United States)

    2014-06-01

    Sumisip 5 18.52 4 44.44 1 12.50 2 33.33 3 75.00 0 0.00 0 0.00 1 6.67 Tipo - Tipo 2 7.41 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 6 66.67 4 26.67 Tuburan 3...Lamitan (6.642691, 122.155193) 3 Tipo - Tipo (6.460622, 122.153796) 3 Sumisip (6.451078, 121.978106) 3 Lantawan (6.646073... Tipo - Tipo - 3 (3) – Lamitan - 3 43 Figure 4. Basilan 2008 Incidents Compared to 2001–2007 CrimeStat Hot Spots For both of these islands

  6. Estimation of the bioaccumulation potential of a nonchlorinated bisphenol and an ionogenic xanthene dye to Eisenia andrei in field-collected soils, in conjunction with predictive in silico profiling.

    Science.gov (United States)

    Princz, Juliska; Bonnell, Mark; Ritchie, Ellyn; Velicogna, Jessica; Robidoux, Pierre-Yves; Scroggins, Rick

    2014-02-01

    In silico-based model predictions, originating from structural and mechanistic (e.g., transport, bioavailability, reactivity, and binding potential) profiling, were compared against laboratory-derived data to estimate the bioaccumulation potential in earthworms of 2 organic substances (1 neutral, 1 ionogenic) known to primarily partition to soil. Two compounds representative of specific classes of chemicals were evaluated: a nonchlorinated bisphenol containing an -OH group (4,4′-methylenebis[2,6-di-tert-butylphenol] [Binox]), and an ionogenic xanthene dye (2′,4′,5′,7′-tetrabromo-4,5,6,7-tetrachloro-3′,6′-dihydroxy-, disodium salt [Phloxine B]). Soil bioaccumulation studies were conducted using Eisenia andrei and 2 field-collected soils (a clay loam and a sandy soil). In general, the in silico structural and mechanistic profiling was consistent with the observed soil bioaccumulation tests. Binox did not bioaccumulate to a significant extent in E. andrei in either soil type; however, Phloxine B not only accumulated within tissue, but was not depurated from the earthworms during the course of the elimination phase. Structural and mechanistic profiling demonstrated the binding and reactivity potential of Phloxine B; this would not be accounted for using traditional bioaccumulation metrics, which are founded on passive-based diffusion mechanisms. This illustrates the importance of profiling for reactive ionogenic substances; even limited bioavailability combined with reactivity can result in exposures to a hazardous substance not predictable by traditional in silico modeling methods.

  7. Sexual victimization and family violence among urban African American adolescent women: do violence cluster profiles predict partner violence victimization and sex trade exposure?

    Science.gov (United States)

    Kennedy, Angie C; Bybee, Deborah; Kulkarni, Shanti J; Archer, Gretchen

    2012-11-01

    Guided by an intersectional feminist perspective, we examined sexual victimization, witnessing intimate partner violence (IPV) in the family, and familial physical abuse among a sample of 180 urban African American adolescent women. We used cluster analysis to better understand the profiles of cumulative victimization, and the relationships between profiles and IPV victimization and personal exposure to the sex trade. Just under one third of the sample reported sexual victimization, with cooccurrence with both forms of family violence common. The cluster profile with high levels of severe family violence was associated with the highest rate of IPV victimization and sex trade exposure.

  8. Temperature profiles from XBT casts from the ENDEAVOR as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1981-07-16 (NODC Accession 8100627)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the ENDEAVOR from 16 July 1981. Data were collected by the National Marine Fisheries Service (NMFS) as part...

  9. Structure prediction of the EcoRV DNA methyltransferase based on mutant profiling, secondary structure analysis, comparison with known structures of methyltransferases and isolation of catalytically inactive single mutants.

    Science.gov (United States)

    Jeltsch, A; Sobotta, T; Pingoud, A

    1996-05-01

    The EcoRV DNA methyltransferase (M.EcoRV) is an alpha-adenine methyltransferase. We have used two different programs to predict the secondary structure of M.EcoRV. The resulting consensus prediction was tested by a mutant profiling analysis. 29 neutral mutations of M.EcoRV were generated by five cycles of random mutagenesis and selection for active variants to increase the reliability of the prediction and to get a secondary structure prediction for some ambiguously predicted regions. The predicted consensus secondary structure elements could be aligned to the common topology of the structures of the catalytic domains of M.HhaI and M.TaqI. In a complementary approach we have isolated nine catalytically inactive single mutants. Five of these mutants contain an amino acid exchange within the catalytic domain of M.EcoRV (Val2-Ala, Lys81Arg, Cys192Arg, Asp193Gly, Trp231Arg). The Trp231Arg mutant binds DNA similarly to wild-type M.EcoRV, but is catalytically inactive. Hence this mutant behaves like a bona fide active site mutant. According to the structure prediction, Trp231 is located in a loop at the putative active site of M.EcoRV. The other inactive mutants were insoluble. They contain amino acid exchanges within the conserved amino acid motifs X, III or IV in M.EcoRV confirming the importance of these regions.

  10. Chemogenomics with protein secondary-structure mimetics.

    Science.gov (United States)

    Marshall, Garland R; Kuster, Daniel J; Che, Ye

    2009-01-01

    During molecular recognition of proteins in biological systems, helices, reverse turns, and beta-sheets are dominant motifs. Often there are therapeutic reasons for blocking such recognition sites, and significant progress has been made by medicinal chemists in the design and synthesis of semirigid molecular scaffolds on which to display amino acid side chains. The basic premise is that preorganization of the competing ligand enhances the binding affinity and potential selectivity of the inhibitor. In this chapter, current progress in these efforts is reviewed.

  11. High VEGFC expression is associated with unique gene expression profiles and predicts adverse prognosis in pediatric and adult acute myeloid leukemia

    NARCIS (Netherlands)

    de Jonge, Hendrik J. M.; Valk, Peter J. M.; Veeger, Nic J. G. M.; ter Elst, Arja; den Boer, Monique L.; Cloos, Jacqueline; de Haas, Valerie; van den Heuvel-Eibrink, Marry M.; Kaspers, Gertjan J. L.; Zwaan, Christian M.; Kamps, Willem A.; Lowenberg, Bob; de Bont, Eveline S. J. M.

    2010-01-01

    High VEGFC mRNA expression of acute myeloid leukemia (AML) blasts is related to increased in vitro and in vivo drug resistance. Prognostic significance of VEGFC on long-term outcome and its associated gene expression profiles remain to be defined. We studied effect of VEGFC on treatment outcome and

  12. High VEGFC expression is associated with unique gene expression profiles and predicts adverse prognosis in pediatric and adult acute myeloid leukemia

    NARCIS (Netherlands)

    H.J.M. de Jonge (Hendrik); P.J.M. Valk (Peter); N.J.G.M. Veeger (Nic); A. ter Elst (Arja); M.L. den Boer (Monique); J. Cloos (Jacqueline); V. de Haas (Valerie); M.M. van den Heuvel-Eibrink (Marry); G.J. Kaspers (Gertjan); C.M. Zwaan (Christian Michel); W.A. Kamps (Willem); B. Löwenberg (Bob); E.S.J.M. de Bont (Eveline)

    2010-01-01

    textabstractHigh VEGFC mRNA expression of acute myeloid leukemia (AML) blasts is related to increased in vitro and in vivo drug resistance. Prognostic significance of VEGFC on long-term outcome and its associated gene expression profiles remain to be defined. We studied effect of VEGFC on treatment

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

    Science.gov (United States)

    Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

    2014-01-01

    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.

  15. Long non-coding RNA expression profiles predict metastasis in lymph node-negative breast cancer independently of traditional prognostic markers

    DEFF Research Database (Denmark)

    Sørensen, Kristina P; Thomassen, Mads; Tan, Qihua;

    2015-01-01

    INTRODUCTION: Patients with clinically and pathologically similar breast tumors often have very different outcomes and treatment responses. Current prognostic markers allocate the majority of breast cancer patients to the high-risk group, yielding high sensitivities in expense of specificities be...... cancer patients eligible for adjuvant therapy, as well as early breast cancer patients that could avoid unnecessary systemic adjuvant therapy. This study emphasizes the potential role of lncRNAs in breast cancer prognosis.......INTRODUCTION: Patients with clinically and pathologically similar breast tumors often have very different outcomes and treatment responses. Current prognostic markers allocate the majority of breast cancer patients to the high-risk group, yielding high sensitivities in expense of specificities...... of traditional prognostic markers and time to metastasis. CONCLUSIONS: To our knowledge, this is the first study investigating the prognostic potential of lncRNA profiles. Our study suggest that lncRNA profiles provide additional prognostic information and may contribute to the identification of early breast...

  16. Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA).

    Science.gov (United States)

    Grötzinger, Stefan W; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B; Stingl, Ulrich; Eppinger, Jörg

    2014-01-01

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  17. Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA).

    KAUST Repository

    Grötzinger, Stefan W.

    2014-04-07

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile\\'s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  18. Mining a database of single amplified genomes from Red Sea brine pool extremophiles – Improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA

    Directory of Open Access Journals (Sweden)

    Stefan Wolfgang Grötzinger

    2014-04-01

    Full Text Available Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs and poor homology of novel extremophile’s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the INDIGO data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes may translate into false positives when searching for specific functions. The Profile & Pattern Matching (PPM strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO-terms (which represent enzyme function profiles and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern. The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2,577 E.C. numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from 6 different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter and PROSITE IDs (pattern filter. Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

  19. MicroRNA profiling predicts survival in anti-EGFR treated chemorefractory metastatic colorectal cancer patients with wild-type KRAS and BRAF

    NARCIS (Netherlands)

    Mosakhani, N.; Lahti, L.M.; Borze, I.; Karjalainen-Lindsberg, M.L.; Sundström, A.; Ristamäki, R.; Osterlund, P.; Knuutila, S.; Sarhadi, V.K.

    2012-01-01

    Anti-EGFR monoclonal antibodies (anti-EGFRmAb) serve in the treatment of metastatic colorectal cancer (mCRC), but patients with a mutation in KRAS/BRAF and nearly one-half of those without the mutation fail to respond. We performed microRNA (miRNA) analysis to find miRNAs predicting anti-EGFRmAb eff

  20. Development of methodology and correlations to predict solids concentration profile during oil well drilling static periods; Desenvolvimento de metodologia e correlacoes para previsao de perfil de concentracao de solidos durante a perfuracao de pocos de petroleo em periodos de estatica

    Energy Technology Data Exchange (ETDEWEB)

    Gandelman, Roni Abensur [Centro de Pesquisas da Petrobras (CENPES). Gerencia de Interacao Rocha-Fluido (Brazil)], e-mail: roniag@petrobras.com.br; Pinto, Gustavo Henrique Vieira Pereira [E and P Norte-Nordeste. Gerencia de Intervencao e Perfuracao de Pocos - BA (Brazil)], e-mail: gustavovieira@petrobras.com.br

    2009-12-15

    One of the main function of drilling fluid is to transport solids, generated by the bit, to the surface. Therefore, gelation is an important and desirable drilling fluid characteristic as it avoids solids sedimentation during pump -off periods. However, when circulation is resumed, an extra energy is required to break the gelled structure. Consequently, bottom-hole pressure peaks are observed and this may represent an operational risk if the fracture pressure is reached. The risk is especially high in narrow operational window scenarios, typical of deep and ultra-deep water environments. On the other hand, gelled fluids may not avoid some heavier and/or larger particles settling. It is therefore important to understand how particles settle in gelled fluids (and while the gelled structure is forming) to predict the solid concentration profiles during and after pump -off periods. This prediction is very important as it can help operators to avoid operational problems. This study developed a methodology to predict particles sedimentation in gelled fluids and pressure peaks when circulation is resumed. To develop the correlations and predict pressure peaks, several experiments were carried out with rheometers and field viscosimeters in transient and stationary conditions. The results were used to build a model that is currently being used with very promising results. (author)

  1.  DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Przemysław Kwiatkowski

    2012-06-01

    Full Text Available  Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations.Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment.The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

  2. Relationship between the prognostic and predictive value of the intrinsic subtypes and a validated gene profile predictive of loco-regional control and benefit from post-mastectomy radiotherapy in patients with high-risk breast cancer

    DEFF Research Database (Denmark)

    Tramm, Trine; Kyndi, Marianne; Myhre, Simen

    2014-01-01

    of triple negative patients with high risk of LRR and significant benefit from PMRT. Agreement in the different assignments of tumors to the subtypes was suboptimal, and the clinical outcome and predicted benefit from PMRT varied according to the method used for assignment. CONCLUSION: The prognostic...

  3. Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index.

    Directory of Open Access Journals (Sweden)

    Ping Wang

    Full Text Available BACKGROUND: Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI diet improved weight maintenance. OBJECTIVE: To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study. DESIGN: Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured. RESULTS: Angiotensin I converting enzyme (ACE was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%. CONCLUSIONS: A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss. REGISTRATION: ClinicalTrials.gov NCT00390637.

  4. Metabolic Profiling of Human Long-Term Liver Models and Hepatic Clearance Predictions from In Vitro Data Using Nonlinear Mixed-Effects Modeling.

    Science.gov (United States)

    Kratochwil, Nicole A; Meille, Christophe; Fowler, Stephen; Klammers, Florian; Ekiciler, Aynur; Molitor, Birgit; Simon, Sandrine; Walter, Isabelle; McGinnis, Claudia; Walther, Johanna; Leonard, Brian; Triyatni, Miriam; Javanbakht, Hassan; Funk, Christoph; Schuler, Franz; Lavé, Thierry; Parrott, Neil J

    2017-03-01

    Early prediction of human clearance is often challenging, in particular for the growing number of low-clearance compounds. Long-term in vitro models have been developed which enable sophisticated hepatic drug disposition studies and improved clearance predictions. Here, the cell line HepG2, iPSC-derived hepatocytes (iCell®), the hepatic stem cell line HepaRG™, and human hepatocyte co-cultures (HμREL™ and HepatoPac®) were compared to primary hepatocyte suspension cultures with respect to their key metabolic activities. Similar metabolic activities were found for the long-term models HepaRG™, HμREL™, and HepatoPac® and the short-term suspension cultures when averaged across all 11 enzyme markers, although differences were seen in the activities of CYP2D6 and non-CYP enzymes. For iCell® and HepG2, the metabolic activity was more than tenfold lower. The micropatterned HepatoPac® model was further evaluated with respect to clearance prediction. To assess the in vitro parameters, pharmacokinetic modeling was applied. The determination of intrinsic clearance by nonlinear mixed-effects modeling in a long-term model significantly increased the confidence in the parameter estimation and extended the sensitive range towards 3% of liver blood flow, i.e., >10-fold lower as compared to suspension cultures. For in vitro to in vivo extrapolation, the well-stirred model was used. The micropatterned model gave rise to clearance prediction in man within a twofold error for the majority of low-clearance compounds. Further research is needed to understand whether transporter activity and drug metabolism by non-CYP enzymes, such as UGTs, SULTs, AO, and FMO, is comparable to the in vivo situation in these long-term culture models.

  5. The effect of unsteady and baroclinic forcing on predicted wind profiles in Large Eddy Simulations: Two case studies of the daytime atmospheric boundary layer

    DEFF Research Database (Denmark)

    Pedersen, Jesper Grønnegaard; Kelly, Mark C.; Gryning, Sven-Erik;

    2013-01-01

    Due to its fine-resolution requirement and subsequent computational demand, Large Eddy Simulation of the atmospheric boundary layer is limited in most cases to computational domains extending only a few kilometers in both the vertical and horizontal directions. Variations in the flow...... and in relevant atmospheric fields (e.g. temperature) that occur at larger scales must be imposed through boundary conditions or as external forcing. In this work we study the influence of such variations on the wind profile in Large Eddy Simulations of daytime atmospheric boundary layers, by comparing......, LIDAR measurements of the wind speed up to heights between 900 and 1600 m and tower-based measurements up to 100 and 250 m are used to evaluate the performance of the variably-driven Large Eddy Simulations. We find in both case studies that including height- and time-variations in the applied pressure...

  6. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data

    Directory of Open Access Journals (Sweden)

    Mitchell Pesesky

    2016-11-01

    Full Text Available The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitate initial use of empiric (frequently broad-spectrum antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0% and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance

  7. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

    Science.gov (United States)

    Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  8. Gene-expression profiling and not immunophenotypic algorithms predicts prognosis in patients with diffuse large B-cell lymphoma treated with immunochemotherapy.

    Science.gov (United States)

    Gutiérrez-García, Gonzalo; Cardesa-Salzmann, Teresa; Climent, Fina; González-Barca, Eva; Mercadal, Santiago; Mate, José L; Sancho, Juan M; Arenillas, Leonor; Serrano, Sergi; Escoda, Lourdes; Martínez, Salomé; Valera, Alexandra; Martínez, Antonio; Jares, Pedro; Pinyol, Magdalena; García-Herrera, Adriana; Martínez-Trillos, Alejandra; Giné, Eva; Villamor, Neus; Campo, Elías; Colomo, Luis; López-Guillermo, Armando

    2011-05-05

    Diffuse large B-cell lymphomas (DLBCLs) can be divided into germinal-center B cell-like (GCB) and activated-B cell-like (ABC) subtypes by gene-expression profiling (GEP), with the latter showing a poorer outcome. Although this classification can be mimicked by different immunostaining algorithms, their reliability is the object of controversy. We constructed tissue microarrays with samples of 157 DLBCL patients homogeneously treated with immunochemotherapy to apply the following algorithms: Colomo (MUM1/IRF4, CD10, and BCL6 antigens), Hans (CD10, BCL6, and MUM1/IRF4), Muris (CD10 and MUM1/IRF4 plus BCL2), Choi (GCET1, MUM1/IRF4, CD10, FOXP1, and BCL6), and Tally (CD10, GCET1, MUM1/IRF4, FOXP1, and LMO2). GEP information was available in 62 cases. The proportion of misclassified cases by immunohistochemistry compared with GEP was higher when defining the GCB subset: 41%, 48%, 30%, 60%, and 40% for Colomo, Hans, Muris, Choi, and Tally, respectively. Whereas the GEP groups showed significantly different 5-year progression-free survival (76% vs 31% for GCB and activated DLBCL) and overall survival (80% vs 45%), none of the immunostaining algorithms was able to retain the prognostic impact of the groups (GCB vs non-GCB). In conclusion, stratification based on immunostaining algorithms should be used with caution in guiding therapy, even in clinical trials.

  9. Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees

    Directory of Open Access Journals (Sweden)

    Chi-Ming Chu

    2014-01-01

    Full Text Available Background. Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0. Methods. Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. Results. The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. Conclusion. We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%. This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.

  10. The association between school exclusion, delinquency and subtypes of cyber- and F2F-victimizations: identifying and predicting risk profiles and subtypes using latent class analysis.

    Science.gov (United States)

    Barboza, Gia Elise

    2015-01-01

    This purpose of this paper is to identify risk profiles of youth who are victimized by on- and offline harassment and to explore the consequences of victimization on school outcomes. Latent class analysis is used to explore the overlap and co-occurrence of different clusters of victims and to examine the relationship between class membership and school exclusion and delinquency. Participants were a random sample of youth between the ages of 12 and 18 selected for inclusion to participate in the 2011 National Crime Victimization Survey: School Supplement. The latent class analysis resulted in four categories of victims: approximately 3.1% of students were highly victimized by both bullying and cyberbullying behaviors; 11.6% of youth were classified as being victims of relational bullying, verbal bullying and cyberbullying; a third class of students were victims of relational bullying, verbal bullying and physical bullying but were not cyberbullied (8%); the fourth and final class, characteristic of the majority of students (77.3%), was comprised of non-victims. The inclusion of covariates to the latent class model indicated that gender, grade and race were significant predictors of at least one of the four victim classes. School delinquency measures were included as distal outcomes to test for both overall and pairwise associations between classes. With one exception, the results were indicative of a significant relationship between school delinquency and the victim subtypes. Implications for these findings are discussed.

  11. Karolinske psychodynamic profile (KAPP)

    DEFF Research Database (Denmark)

    Mathiesen, Birgit Bork; Søgaard, Ulf

    2006-01-01

    psykologiske testmetoder, assesment, Karolinska psychodynamic profile (KAPP), psykodynamisk profil......psykologiske testmetoder, assesment, Karolinska psychodynamic profile (KAPP), psykodynamisk profil...

  12. Association for methodology and documentation in psychiatry profiles predict later risk for criminal behavior and violent crimes in former inpatients with affective disorder.

    Science.gov (United States)

    Soyka, Michael; Zingg, Christina

    2010-05-01

    Few studies have investigated criminal and violent behavior in patients with affective disorders. We reviewed the national crime register for records of criminal offenses committed by 1561 patients with affective disorders and studied the predictive value of certain psychopathological symptoms assessed with the Association for Methodology and Documentation in Psychiatry (AMDP) system concerning future criminal behavior. Sixty-five (4.2%) patients had been convicted in the 7-12 years after discharge (307 cases). Patients with the AMDP syndrome mania had a significantly higher risk for later criminal behavior. The combination with the hostility syndrome further increased the risk. These findings are in line with previous data indicating a higher risk for later criminal behavior in patients with a manic/bipolar disorder compared to depressive disorder. As previously demonstrated in another sample of schizophrenic patients, the AMDP syndromes mania (and hostility) is associated with a higher risk of later criminal behavior.

  13. A Danish Profiling System

    DEFF Research Database (Denmark)

    Rosholm, Michael; Staghøj, Jonas; Svarer, Michael;

    2006-01-01

    This paper describes the statistical model used for profiling new unemployed workers in Denmark. When a worker – during his or her first six months in unemployment – enters the employment office for the first time, this model predicts whether or not he or she will be unemployed for more than six ...

  14. A curative immune profile one week after treatment of Indian kala-azar patients predicts success with a short-course liposomal amphotericin B therapy.

    Directory of Open Access Journals (Sweden)

    Smriti Mondal

    Full Text Available BACKGROUND: The present pilot study investigating the minimum dose for short-course single and double-dose treatment of kala-azar with an apparently new liposomal formulation of amphotericin B, Fungisome, led to identification of immunological components for early detection of success and/or failure to cure. METHODS: Patients were treated with 5, 7.5 (single-dose and 10 mg/kg body weight (5 mg/kg double-dose of Fungisome. Immunological investigations involving plasma cytokines and antigen-specific lymphoproliferation and cytokine responses from PBMCs were carried out before, 1 week after Fungisome treatment, at the time of relapse, and again after conventional amphotericin B treatment. RESULTS: At 1-month follow-up all the patients showed 100% initial cure. However, total doses of 5, 7.5 and 10 mg/kg Fungisome showed 60%, 50% and 90% cure, respectively, at 6-months posttreatment. Patients successfully cured demonstrated downregulation of IL-12 and IL-10 in plasma, and two-fold or more elevation of IFN-gamma, IL-12 and TNF, and significant down-regulation of IL-10 and TGF-beta in culture supernatants 1-week posttreatment irrespective of drug-dose. A differential immune profile, involving insignificant decline in IL-10 and IL-12 in plasma and negligible elevation of IFN-gamma, IL-12 and TNF, and persistence of IL-10, despite decline in TGF-beta in culture supernatants, in apparently cured individuals, corresponded with relapse within 6-months of treatment. CONCLUSION: Immunological investigations revealed significant curative and non-curative immunomodulation 1-week posttreatment, correlating with successful cure and relapse, respectively. Although immune-correlation was dose-independent, almost consistent curative response in patients treated with the highest dose 10 mg/kg reflected a definitive impact of the higher-dose on the immune response. TRIAL REGISTRATION NAME AND NUMBER: Clinical Trials Registry--India (CTRI CTRI/2009/091/000764.

  15. The β5/focal adhesion kinase/glycogen synthase kinase 3β integrin pathway in high-grade osteosarcoma: a protein expression profile predictive of response to neoadjuvant chemotherapy.

    Science.gov (United States)

    Le Guellec, Sophie; Moyal, Elizabeth Cohen-Jonathan; Filleron, Thomas; Delisle, Marie-Bernadette; Chevreau, Christine; Rubie, Hervé; Castex, Marie-Pierre; de Gauzy, Jerome Sales; Bonnevialle, Paul; Gomez-Brouchet, Anne

    2013-10-01

    To date, chemosensitivity to neoadjuvant chemotherapy of patients with high-grade osteosarcoma is evaluated on surgical resection by evaluation of the percentage of necrotic cells. As yet, no predictive profile of response to chemotherapy has been used in clinical practice. Because we have previously shown that the integrin pathway controls genotoxic-induced cell death and hypoxia, we hypothesized that in primary biopsies, expression of proteins involved in this pathway could be associated with sensitivity to neoadjuvant chemotherapy in high-grade osteosarcoma. We studied β1, β3, and β5 integrin expression and integrin-linked kinase, focal adhesion kinase (FAK), glycogen synthase kinase 3β (GSK3β), Rho B, angiopoietin-2, β-catenin, and ezrin expression by immunohistochemistry in 36 biopsies of osteosarcomas obtained before treatment. All patients received a chemotherapy regimen in the neoadjuvant setting. An immunoreactive score was assessed, combining the percentage of positive tumor cells and staining intensity. We evaluated the correlation of the biomarkers with response to chemotherapy, metastasis-free survival, and overall survival. A combination of 3 biomarkers (β5 integrin, FAK, and GSK3β) discriminated good and poor responders to chemotherapy, with the highest area under the curve (89.9%; 95% confidence interval, 77.4-1.00) and a diagnostic accuracy of 90.3%. Moreover, high expression of ezrin was associated with an increased risk of metastasis (hazard ratio, 3.93; 95% confidence interval, 1.19-12.9; P = .024). We report a protein expression profile in high-grade osteosarcoma associating β5 integrin, FAK, and GSK3β that significantly correlates with poor response to neoadjuvant chemotherapy. This biomarker profile could help select patients for whom an alternative protocol using inhibitors of this pathway can be proposed.

  16. Phenolic profile within the fine-root branching orders of an evergreen species highlights a disconnect in root tissue quality predicted by elemental- and molecular-level carbon composition.

    Science.gov (United States)

    Wang, Jun-Jian; Tharayil, Nishanth; Chow, Alex T; Suseela, Vidya; Zeng, Hui

    2015-06-01

    Fine roots constitute a significant source of plant productivity and litter turnover across terrestrial ecosystems, but less is known about the quantitative and qualitative profile of phenolic compounds within the fine-root architecture, which could regulate the potential contribution of plant roots to the soil organic matter pool. To understand the linkage between traditional macro-elemental and morphological traits of roots and their molecular-level carbon chemistry, we analyzed seasonal variations in monomeric yields of the free, bound, and lignin phenols in fine roots (distal five orders) and leaves of Ardisia quinquegona. Fine roots contained two-fold higher concentrations of bound phenols and three-fold higher concentrations of lignin phenols than leaves. Within fine roots, the concentrations of free and bound phenols decreased with increasing root order, and seasonal variation in the phenolic profile was more evident in lower order than in higher order roots. The morphological and macro-elemental root traits were decoupled from the quantity, composition and tissue association of phenolic compounds, revealing the potential inability of these traditional parameters to capture the molecular identity of phenolic carbon within the fine-root architecture and between fine roots and leaves. Our results highlight the molecular-level heterogeneity in phenolic carbon composition within the fine-root architecture, and imply that traits that capture the molecular identity of the root construct might better predict the decomposition dynamics within fine-root orders.

  17. Poly-substance use and antisocial personality traits at admission predict cumulative retention in a buprenorphine programme with mandatory work and high compliance profile

    Directory of Open Access Journals (Sweden)

    Fridell Mats

    2011-05-01

    Full Text Available Abstract Background Continuous abstinence and retention in treatment for alcohol and drug use disorders are central challenges for the treatment providers. The literature has failed to show consistent, strong predictors of retention. Predictors and treatment structure may differ across treatment modalities. In this study the structure was reinforced by the addition of supervised urine samples three times a week and mandatory daily work/structured education activities as a prerequisite of inclusion in the program. Methods Of 128 patients consecutively admitted to buprenorphine maintenance treatment five patients dropped out within the first week. Of the remaining 123 demographic data and psychiatric assessment were used to predict involuntary discharge from treatment and corresponding cumulative abstinence probability. All subjects were administered the Structured Clinical Interview for DSM-IV-TR, and the Symptom Checklist 90 (SCL-90, the Alcohol Use Disorder Identification Test (AUDIT, the Swedish universities Scales of Personality (SSP and the Sense of Coherence Scale (SOC, all self-report measures. Some measures were repeated every third month in addition to interviews. Results Of 123 patients admitted, 86 (70% remained in treatment after six months and 61 (50% remained in treatment after 12 months. Of those discharged involuntarily, 34/62 individuals were readmitted after a suspension period of three months. Younger age at intake, poly-substance abuse at intake (number of drugs in urine, and number of conduct disorder criteria on the SCID Screen were independently associated with an increased risk of involuntary discharge. There were no significant differences between dropouts and completers on SCL-90, SSP, SOC or AUDIT. Conclusion Of the patients admitted to the programme 50% stayed for the first 12 months with continuous abstinence and daily work. Poly-substance use before intake into treatment, high levels of conduct disorder on SCID

  18. Proteomic profiling of the planarian Schmidtea mediterranea and its mucous reveals similarities with human secretions and those predicted for parasitic flatworms.

    Science.gov (United States)

    Bocchinfuso, Donald G; Taylor, Paul; Ross, Eric; Ignatchenko, Alex; Ignatchenko, Vladimir; Kislinger, Thomas; Pearson, Bret J; Moran, Michael F

    2012-09-01

    The freshwater planarian Schmidtea mediterranea has been used in research for over 100 years, and is an emerging stem cell model because of its capability of regenerating large portions of missing body parts. Exteriorly, planarians are covered in mucous secretions of unknown composition, implicated in locomotion, predation, innate immunity, and substrate adhesion. Although the planarian genome has been sequenced, it remains mostly unannotated, challenging both genomic and proteomic analyses. The goal of the current study was to annotate the proteome of the whole planarian and its mucous fraction. The S. mediterranea proteome was analyzed via mass spectrometry by using multidimensional protein identification technology with whole-worm tryptic digests. By using a proteogenomics approach, MS data were searched against an in silico translated planarian transcript database, and by using the Swiss-Prot BLAST algorithm to identify proteins similar to planarian queries. A total of 1604 proteins were identified. The mucous subproteome was defined through analysis of a mucous trail fraction and an extract obtained by treating whole worms with the mucolytic agent N-acetylcysteine. Gene Ontology analysis confirmed that the mucous fractions were enriched with secreted proteins. The S. mediterranea proteome is highly similar to that predicted for the trematode Schistosoma mansoni associated with intestinal schistosomiasis, with the mucous subproteome particularly highly conserved. Remarkably, orthologs of 119 planarian mucous proteins are present in human mucosal secretions and tear fluid. We suggest planarians have potential to be a model system for the characterization of mucous protein function and relevant to parasitic flatworm infections and diseases underlined by mucous aberrancies, such as cystic fibrosis, asthma, and other lung diseases.

  19. Proteochemometric modelling coupled to in silico target prediction: an integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.

    Science.gov (United States)

    Paricharak, Shardul; Cortés-Ciriano, Isidro; IJzerman, Adriaan P; Malliavin, Thérèse E; Bender, Andreas

    2015-01-01

    The rampant increase of public bioactivity databases has fostered the development of computational chemogenomics methodologies to evaluate potential ligand-target interactions (polypharmacology) both in a qualitative and quantitative way. Bayesian target prediction algorithms predict the probability of an interaction between a compound and a panel of targets, thus assessing compound polypharmacology qualitatively, whereas structure-activity relationship techniques are able to provide quantitative bioactivity predictions. We propose an integrated drug discovery pipeline combining in silico target prediction and proteochemometric modelling (PCM) for the respective prediction of compound polypharmacology and potency/affinity. The proposed pipeline was evaluated on the retrospective discovery of Plasmodium falciparum DHFR inhibitors. The qualitative in silico target prediction model comprised 553,084 ligand-target associations (a total of 262,174 compounds), covering 3,481 protein targets and used protein domain annotations to extrapolate predictions across species. The prediction of bioactivities for plasmodial DHFR led to a recall value of 79% and a precision of 100%, where the latter high value arises from the structural similarity of plasmodial DHFR inhibitors and T. gondii DHFR inhibitors in the training set. Quantitative PCM models were then trained on a dataset comprising 20 eukaryotic, protozoan and bacterial DHFR sequences, and 1,505 distinct compounds (in total 3,099 data points). The most predictive PCM model exhibited R (2) 0 test and RMSEtest values of 0.79 and 0.59 pIC50 units respectively, which was shown to outperform models based exclusively on compound (R (2) 0 test/RMSEtest = 0.63/0.78) and target information (R (2) 0 test/RMSEtest = 0.09/1.22), as well as inductive transfer knowledge between targets, with respective R (2) 0 test and RMSEtest values of 0.76 and 0.63 pIC50 units. Finally, both methods were integrated to predict the protein

  20. Profile summary.

    Science.gov (United States)

    2003-01-01

    All drugs appearing in the Adis Profile Summary table have been selected based on information contained in R&D Insight trade mark, a proprietary product of Adis International. The information in the profiles is gathered from the world's medical and scientific literature, at international conferences and symposia, and directly from the developing companies themselves. The emphasis of Drugs in R&D is on the clinical potential of new drugs, and selection of agents for inclusion is based on products in late-phase clinical development that have recently had a significant change in status.

  1. The ‘SAR Matrix’ method and its extensions for applications in medicinal chemistry and chemogenomics [v1; ref status: indexed, http://f1000r.es/3gh

    Directory of Open Access Journals (Sweden)

    Disha Gupta-Ostermann

    2014-05-01

    Full Text Available We describe the ‘Structure-Activity Relationship (SAR Matrix’ (SARM methodology that is based upon a special two-step application of the matched molecular pair (MMP formalism. The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets. It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces. The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.

  2. Prediction and Bioinformatics Analysis of Human Gene Expression Profiling Regulated by Amifostine%依硫磷酸调控人类基因表达谱的预测及生物信息学分析

    Institute of Scientific and Technical Information of China (English)

    杨波; 脱朝伟; 蔡力力; 迟小华; 卢学春; 张峰; 脱帅; 朱宏丽; 刘丽宏; 严江伟

    2011-01-01

    Objective of this study was to perform bioinformatics analysis of the characteristics of gene expression profiling regulated by amifostine and predict its novel potential biological function to provide a direction for further exploring pharmacological actions of amifostine and study methods. Amifostine was used as a key word to search intemet-based free gene expression database including GEO, affymetrix gene chip database, GenBank, SAGE,GeneCard, InterPro, ProtoNet, UniProt and BLOCKS and the sifted amifostine-regulated gene expression profiling data was subjected to validity testing, gene expression difference analysis and functional clustering and gene annotation. The results showed that only one data of gene expression profiling regulated by amifostine was sifted from GEO database (accession: GSE3212). Through validity testing and gene expression difference analysis, significant difference (p <0.01 ) was only found in 2.14% of the whole genome (460/192000). Gene annotation analysis showed that 139 out of 460 genes were known genes, in which 77 genes were up-regulated and 62 genes were down-regulated. 13 out of 139 genes were newly expressed following amifostine treatment of K562 cells, however expression of 5 genes was completely inhibited. Functional clustering displayed that 139 genes were divided into 1 l categories and their biological function was involved in hematopoietic and immunologic regulation, apoptosis and cell cycle. It is concluded that bioinformatics method can be applied to analysis of gene expression profiling regulated by amifostine. Amifostine has a regulatory effect on human gene expression profiling and this action is mainly presented in biological processes including hematopoiesis,immunologic regulation, apoptosis and cell cycle and so on. The effect of amifostine on human gene expression need to be further testified in experimental condition.%本研究对依硫磷酸调控人类基因表达谱进行生物信息学分析,预测其可

  3. MPI Profiling

    Energy Technology Data Exchange (ETDEWEB)

    Han, D K; Jones, T R

    2005-02-11

    The Message Passing Interface (MPI) is the de facto message-passing standard for massively parallel programs. It is often the case that application performance is a crucial factor, especially for solving grand challenge problems. While there have been many studies on the scalability of applications, there have not been many focusing on the specific types of MPI calls being made and their impact on application performance. Using a profiling tool called mpiP, a large spectrum of parallel scientific applications were surveyed and their performance results analyzed.

  4. Temperature profiles from XBT casts from the ACTIVE and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1979-02-01 to 1979-04-01 (NODC Accession 7900172)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the ACTIVE and other platforms from 01 February 1979 to 01 April 1979. Data were collected by the National...

  5. Oceanographic Station Data and temperature profiles from XBT and bottle casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1975-12-03 to 1975-12-06 (NODC Accession 7600754)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from XBT and bottle casts from the DOLPHIN from 03 December 1975 to 06 December 1975. Data were...

  6. Temperature profiles from XBT casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1974-11-08 to 1974-11-14 (NODC Accession 7500079)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the DOLPHIN from 08 November 1974 to 14 November 1974. Data were collected by the National Marine Fisheries...

  7. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1981-02-14 to 1981-02-15 (NODC Accession 8100486)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the EDGAR M. QUEENY from 14 February 1981 to 15 February 1981. Data were collected by the National Marine...

  8. Temperature profiles from XBT casts from the PORT JEFFERSON as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-03-28 to 1978-03-29 (NODC Accession 7800452)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the PORT JEFFERSON from 28 March 1978 to 29 March 1978. Data were collected by the National Marine Fisheries...

  9. Temperature profiles from XBT casts from the DELTA ARGENTINA as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1973-09-21 to 1973-10-17 (NODC Accession 7301174)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the DELTA ARGENTINA from 21 September 1973 to 17 October 1973. Data were collected by Delata Steamship Co. as...

  10. Temperature profiles from XBT casts from the SANTA CRUZ as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1974-05-17 to 1974-06-12 (NODC Accession 7400570)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the SANTA CRUZ from 17 May 1974 to 12 June 1974. Data were collected by Grace Prudential Lines as part of the...

  11. Oceanographic Station Data and temperature profiles from bottle and XBT casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1975-08-31 to 1975-09-19 (NODC Accession 7600375)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from bottle and XBT casts from the DOLPHIN from 31 August 1975 to 19 September 1975. Data were...

  12. Temperature profiles from XBT casts from the DELTA ARGENTINA as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1972-11-14 to 1973-01-02 (NODC Accession 7300035)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the DELTA ARGENTINA and other platforms from 14 November 1972 to 02 January 1973. Data were collected by the...

  13. Temperature profiles from XBT casts from the SANTA CRUZ and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1975-06-22 to 1975-09-17 (NODC Accession 7500932)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the SANTA CRUZ and other platforms from 22 June 1975 to 17 September 1975. Data were collected by Grace...

  14. Temperature profiles from XBT casts from the EVERGREEN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1977-04-02 to 1977-04-30 (NCEI Accession 7700355)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the EVERGREEN from 02 April 1977 to 30 April 1977. Data were collected by the National Marine Fisheries...

  15. Temperature profiles from XBT casts from the CARIBOU REEFER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-06-02 to 1978-06-03 (NCEI Accession 7800532)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the CARIBOU REEFER from 02 June 1978 to 03 June 1978. Data were collected by the National Marine Fisheries...

  16. Temperature profiles from XBT casts from the LASH ATLANTICO as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-07-17 to 1978-07-18 (NCEI Accession 7800744)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the LASH ATLANTICO from 17 July 1978 to 18 July 1978. Data were collected by the National Marine Fisheries...

  17. Temperature profiles from XBT casts from the CARIBOU REEFER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-05-22 to 1978-05-23 (NCEI Accession 7800456)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the CARIBOU REEFER from 22 May 1978 to 23 May 1978. Data were collected by the National Marine Fisheries...

  18. Temperature profiles from XBT casts from the LASH ATLANTICO as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-04-30 to 1978-05-01 (NCEI Accession 7800512)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the LASH ATLANTICO from 30 April 1978 to 01 May 1978. Data were collected by the National Marine Fisheries...

  19. Temperature profiles from XBT casts from the INGHAM as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1975-03-26 to 1975-03-27 (NODC Accession 7500244)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the INGHAM from 26 March 1975 to 27 March 1975. Data were collected by the United States Coast Guard (USCG)...

  20. Temperature profiles from XBT casts from the DELTA SUD as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1975-02-09 to 1975-03-16 (NODC Accession 7500643)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the DELTA SUD from 09 February 1975 to 16 March 1975. Data were collected by the Delta Steamship Co. as part...

  1. Temperature profiles from XBT casts from the SANTA CRUZ and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1974-10-01 to 1974-11-28 (NODC Accession 7400823)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the SANTA CRUZ and other platforms from 01 October 1974 to 28 November 1974. Data were collected by the Delta...

  2. Temperature profiles from XBT casts from the SANTA CRUZ as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1972-09-01 to 1972-10-09 (NODC Accession 7201316)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the SANTA CRUZ from 01 September 1972 to 09 October 1972. Data were collected by Grace Prudential Lines as...

  3. Temperature profiles from XBT casts from the CARIBOU REEFER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-05-07 (NODC Accession 7800391)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the CARIBOU REEFER from 07 May 1978. Data were collected as part of the Marine Resources Monitoring,...

  4. Temperature profiles from XBT casts from the MARINE CRUISER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1977-02-18 to 1977-02-19 (NODC Accession 7700191)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the MARINE CRUISER from 18 February 1977 to 19 February 1977. Data were collected by the National Marine...

  5. Temperature profiles from XBT casts from the AMERICAN RIGEL as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-02-12 to 1978-03-22 (NODC Accession 7800316)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the AMERICAN RIGEL from 12 February 1978 to 22 March 1978. Data were collected by Moore-McCormack Lines Inc....

  6. Oceanographic station, temperature profiles, meteorological, and other data from bottle and XBT from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1974-01-09 to 1974-01-12 (NODC Accession 7400287)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic station, temperature profiles, meteorological, and other data were collected from bottle and XBT casts from the DOLPHIN from 09 January 1974 to 12...

  7. Oceanographic Station Data and temperature profiles from bottle and XBT casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1975-04-17 to 1976-02-07 (NODC Accession 7600888)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from bottle and XBT casts from the DOLPHIN from 17 April 1975 to 07 February 1976. Data were...

  8. Oceanographic Station, temperature profiles, and other data from XBT and bottle casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1975-01-17 to 1975-04-10 (NODC Accession 7500672)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station, temperature profiles, and other data were collected from XBT and bottle casts from the DOLPHIN from 17 January 1975 to 10 April 1975. Data...

  9. Oceanographic Station, temperature profiles, and other data from XBT and bottle casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1974-04-01 to 1974-05-09 (NODC Accession 7400626)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station, temperature profiles, and other data were collected from XBT and bottle casts from the DOLPHIN from 01 April 1974 to 09 May 1974. Data were...

  10. Oceanographic Station Data and temperature profiles from bottle and XBT casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1977-01-18 to 1977-05-22 (NCEI Accession 7800595)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from bottle and XBT casts from the DOLPHIN from 18 January 1977 to 22 May 1977. Data were...

  11. Oceanographic Station, temperature profiles, and other data from bottle and XBT casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1974-08-13 to 1974-09-18 (NODC Accession 7400814)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station, temperature profiles, and other data were collected from bottle and XBT casts from the DOLPHIN from 13 August 1974 to 18 September 1974. Data...

  12. Oceanographic Station, temperature profiles, and other data from XBT and bottle casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1973-02-12 to 1973-03-23 (NCEI Accession 7300813)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station,temperature profiles, and other data were collected from XBT and bottle casts from the DOLPHIN from 12 February 1973 to 23 March 1973. Data...

  13. Oceanographic Station Data and temperature profiles from XBT and bottle casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1976-08-28 to 1976-09-21 (NODC Accession 7700036)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from XBT and bottle casts from the DOLPHIN from 28 August 1976 to 21 September 1976. Data were...

  14. Temperature profiles from XBT casts from the MARINE EVANGELINE and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1981-06-03 to 1981-11-20 (NODC Accession 8100721)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the MARINE EVANGELINE and other platforms from 03 June 1981 to 20 November 1981. Data were collected by the...

  15. Temperature profiles from XBT casts from the SANTA CRUZ and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1972-09-01 to 1972-11-05 (NODC Accession 7201439)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the SANTA CRUZ and other platforms from 01 September 1972 to 05 November 1972. Data were collected by the...

  16. Temperature profiles from XBT casts from the YANKEE CLIPPER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1982-06-11 to 1982-06-12 (NODC Accession 8200126)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the YANKEE CLIPPER from 11 June 1982 to 12 June 1982. Data were collected by the National Marine Fisheries...

  17. Temperature profiles from XBT casts from the LASH TURKIYE as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1976-11-22 to 1976-11-23 (NODC Accession 7700127)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the LASH TURKIYE from 22 November 1976 to 23 November 1976. Data were collected by the US NAVY as part of...

  18. Temperature profiles from XBT casts from the LASH TURKIYE as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1977-01-30 to 1977-03-05 (NCEI Accession 7700259)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the LASH TURKIYE from 30 January 1977 to 05 March 1977. Data were collected by the National Marine Fisheries...

  19. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1979-11-10 to 1979-11-11 (NODC Accession 7900331)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the EDGAR M. QUEENY from 10 November 1979 to 11 November 1979. Data were collected by the National Marine...

  20. Temperature profiles from XBT casts from the DECATUR and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1969-08-30 to 1983-03-31 (NODC Accession 8300047)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the DECATUR and other platforms from 30 August 1969 to 31 March 1983. Data were collected by the National...

  1. Temperature profiles from XBT casts from NOAA Ship OREGON II as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1973-05-02 to 1973-06-09 (NODC Accession 7301215)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from NOAA Ship OREGON II from 02 May 1973 to 09 June 1973. Data were collected by the National Marine Fisheries...

  2. Temperature profiles from XBT casts from NOAA Ship DELAWARE II and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1971-04-01 to 1972-10-01 (NCEI Accession 7300061)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile were collected from XBT casts from NOAA Ship DELAWARE II and other platforms from 01 April 1971 to 01 October 1972. Data were collected by the...

  3. Temperature profiles from XBT casts from the MARINE EVANGELINE and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1979-06-03 to 1979-06-28 (NODC Accession 7900220)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the MARINE EVANGELINE and other platforms from 03 June 1979 to 28 June 1979. Data were collected by the...

  4. Temperature profiles from XBT casts from the CRUSADER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1977-03-15 to 1977-03-16 (NODC Accession 7700277)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the CRUSADER from 15 March 1977 to 16 March 1977. Data were collected by the National Marine Fisheries...

  5. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1979-09-27 to 1979-09-28 (NODC Accession 7900308)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the EDGAR M. QUEENY from 27 September 1979 to 28 September 1979. Data were collected by the National Marine...

  6. Temperature profiles from XBT casts from the WIECZNO as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1979-11-13 to 1979-11-14 (NODC Accession 7900334)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the WIECZNO from 13 November 1979 to 14 November 1979. Data were collected by the National Marine Fisheries...

  7. Temperature profiles from XBT casts from the AMERICAN ARGO as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1980-05-02 to 1980-06-02 (NODC Accession 8000380)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the AMERICAN ARGO from 02 May 1980 to 02 June 1980. Data were collected by Moore-McCormack Lines Inc. as part...

  8. Temperature profiles from XBT casts from the DELTA ECUADOR and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1978-09-30 to 1978-10-05 (NODC Accession 7800858)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the DELTA ECUADOR and other platforms from 30 September 1978 to 05 October 1978. Data were collected by the...

  9. Wind profiles in and over trees

    Institute of Scientific and Technical Information of China (English)

    ZHUJiao-jun; LIXiu-fen; GondaYutaka; MatsuzakiTakeshi

    2004-01-01

    One of the most important and frequently studied variable in forests and the most basic element in governing transport processes of airflow is wind speed. The study of wind profile, defined as the change of wind velocity with height, and wind velocity are important because of tree physiological and developmental responses. Generally, wind profiles above the ground or at a canopy surface follow classical logarithm law, but wind profiles in a single tree and in a forest stand are not logarithmic. This paper summarizes the results of wind profile studies within a single tree, in a forest stand, above the forest canopy and in a forest area from recent research in a coastal pine forest. The results demonstrate that: 1) wind profiles with in a single conifer tree crown showed an exponential function with height, 2) wind profiles in forest stands were able to be expressed by attenuation coefficient of wind, 3) wind profiles over a forest canopy could be determined using profile parameters (friction velocity, roughness length and displacement), and 4) for a forest area, the extreme wind speed could be predicted reasonably using the methods developed for the design of buildings. More research will be required to demonstrate: 1) relationships between wind profiles and tree or stand characteristics, 2) the simple methods for predicting wind profile parameters, and 3) the applications of wind profile in studies of tree physiology, forest ecology and management, and the detail ecological effects of wind on tree growth.

  10. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    2008-01-01

    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents experimentally based design parameters for Portland cement concretes with and without silica fume and fly ash...... in marine atmospheric and submersed South Scandinavian environment. The design parameters are based on sequential measurements of 86 chloride profiles taken over ten years from 13 different types of concrete. The design parameters provide the input for an analytical model for chloride profiles as function...

  11. PTRANSP Tests of TGLF and Predictions for ITER

    Energy Technology Data Exchange (ETDEWEB)

    Robert V. Budny, Xingqiu Yuan, S. Jardin, G. Hammett, G. Staebler, J. Kinsey, members of the ITPA Transport and Confinement Topical Group, and JET EFDA Contributors

    2012-09-23

    A new numerical solver for stiff transport predictions has been developed and implemented in the PTRANSP predictive transport code. The TGLF and GLF23 predictive codes have been incorporated in the solver, verified by comparisons with predictions from the XPTOR code, and validated by comparing predicted and measured profiles. Predictions for ITER baseline plasmas are presented.

  12. Criminal psychological profiling: validities and abilities.

    Science.gov (United States)

    Kocsis, Richard N

    2003-04-01

    Criminal psychological profiling has attained unprecedented recognition despite little empirical evidence to support its validity and the absence of any thorough exposition of the skills involved with the technique. This article reports on the empirically derived conclusions of studies that sought to examine the accuracy and skill of various groups performing a profiling task. The conclusions provide some support for the contention that professional profilers can produce a more accurate prediction of an unknown offender in comparison to other studied groups. The results also give an indication of the type of skills required for proficient profiling.

  13. Fetal Biophysical Profile Scoring

    Directory of Open Access Journals (Sweden)

    H.R. HaghighatKhah

    2009-01-01

    significance. Fetal breathing movements, amniotic fluid volume, and the non-stress test are the most powerful variables. For example, when the biophysical profile score is 2, the perinatal mortality varies between 428/1000 with only fetal movement present to 66/1000 if the non-stress test is reactive and all of the ultrasound parameters are absent (Manning 1990b. Some authors have, therefore, proposed utilization of a modified biophysical profile that incorporates only the non-stress test and amniotic fluid volume (Miller 1996. Although the positive predictive value of these 2 tests is equivalent to a biophysical profile score of 6, the perinatal mortality is still increased over a normal test score of 8 or 10 (Manning 1990b. The false positive rate with the modified biophysical profile score is also substantially higher. "nConclusions: The fetus expresses its well being or compromised status through a number of different biophysical activities that are controlled by different central nervous system centers. The utilization of the biophysical score for antepartum surveillance in high-risk patients has resulted in a reduction in perinatal mortality when compared to historical controls. The appropriate management of the viable fetus with an abnormal biophysical profile score may also decrease long-term neurological morbidity (Manning 1998. "nIt is unlikely that in the future additional variables will be added to the biophysical profile score. However, perhaps the incorporation of the fetal state (i.e., eye movements and Doppler flow studies of specific fetal vessels (umbilical artery, middle cerebral artery, ductus venosus will be incorporated into a complete assessment of the fetal condition "n "nTable 1. Components of the 30 Minute Biophysical Profile Score "nComponent "nDefinition "nFetal movements "n> 3 body or limb movements "nFetal tone "nOne episode of active extension and flexion of the limbs; opening and closing of hand "nFetal breathing movements "n>1

  14. Spiking the expectancy profiles

    DEFF Research Database (Denmark)

    Hansen, Niels Chr.; Loui, Psyche; Vuust, Peter

    Melodic expectations are generated with different degrees of certainty. Given distributions of expectedness ratings for multiple continuations of each context, as obtained with the probe-tone paradigm, this certainty can be quantified in terms of Shannon entropy. Because expectations arise from...... Kullback-Leibler or Jensen-Shannon Divergence) between listeners’ prior expectancy profiles and probability distributions of a musical style or of stimuli used in short-term experiments. Five previous probe-tone experiments with musicians and non-musicians were revisited. In Experiments 1-2 participants...... and relevance of musical training and within-participant decreases after short-term exposure to novel music. Thus, whereas inexperienced listeners make high-entropy predictions, statistical learning over varying timescales enables listeners to generate melodic expectations with reduced entropy...

  15. COMPENDEX Profiling Guide.

    Science.gov (United States)

    Standera, Oldrich

    This manual provides instructions for completing the COMPENDEX (Computerized Engineering Index) Profile Submission Form used to prepare Current Information Selection (CIS) profiles. An annotated bibliography lists nine items useful in searching for proper profile words. (AB)

  16. Predicting future of predictive analysis

    OpenAIRE

    Piyush, Duggal

    2014-01-01

    With enormous growth in analytical data and insight about advantage of managing future brings Predictive Analysis in picture. It really has potential to be called one of efficient and competitive technologies that give an edge to business operations. The possibility to predict future market conditions and to know customers’ needs and behavior in advance is the area of interest of every organization. Other areas of interest may be maintenance prediction where we tend to predict when and where ...

  17. Overlap in Facebook Profiles Reflects Relationship Closeness.

    Science.gov (United States)

    Castañeda, Araceli M; Wendel, Markie L; Crockett, Erin E

    2015-01-01

    We assessed the association between self-reported Inclusion of Other in the Self (IOS) and Facebook overlap. Ninety-two participants completed online measures of IOS and investment model constructs. Researchers then recorded Facebook data from participants' profile pages. Results from multilevel models revealed that IOS predicted Facebook overlap. Furthermore, Facebook overlap was associated with commitment and investment in ways comparable to self-reported IOS. These findings suggest that overlap in Facebook profiles can be used to measure relationship closeness.

  18. An empirical assessment of content in criminal psychological profiles.

    Science.gov (United States)

    Kocsis, Richard N

    2003-02-01

    Although criminal psychological profiling has been in use by law enforcement agencies for almost three decades, there is a paucity of empirical research examining the technique. A fundamental issue that has received little attention is the empirical evaluation of information contained in profiles composed by professional profilers. In this study, a group of profilers, police officers, psychologists, college students, and self-declared psychics were given information from a solved murder investigation, after which the participants composed a written profile predicting the probable offender. Professional profilers tended to write more lengthy profiles that contained more information about the nonphysical attributes of the offender and more information about the crime scene or the offender's behavior before, during, and after the crime. These results are discussed in terms of their implication for our broader understanding of the technique of profiling and future directions for research into profiling.

  19. Parametric dependencies of JET electron temperature profiles

    Energy Technology Data Exchange (ETDEWEB)

    Schunke, B. [Commission of the European Communities, Abingdon (United Kingdom). JET Joint Undertaking; Imre, K.; Riedel, K. [New York Univ., NY (United States)

    1994-07-01

    The JET Ohmic, L-Mode and H-Mode electron temperature profiles obtained from the LIDAR Thomson Scattering Diagnostic are parameterized in terms of the normalized flux parameter and a set of the engineering parameters like plasma current, toroidal field, line averages electron density... It is shown that the electron temperature profiles fit a log-additive model well. It is intended to use the same model to predict the profile shape for D-T discharges in JET and in ITER. 2 refs., 5 figs.

  20. HMMEditor: a visual editing tool for profile hidden Markov model

    Directory of Open Access Journals (Sweden)

    Cheng Jianlin

    2008-03-01

    Full Text Available Abstract Background Profile Hidden Markov Model (HMM is a powerful statistical model to represent a family of DNA, RNA, and protein sequences. Profile HMM has been widely used in bioinformatics research such as sequence alignment, gene structure prediction, motif identification, protein structure prediction, and biological database search. However, few comprehensive, visual editing tools for profile HMM are publicly available. Results We develop a visual editor for profile Hidden Markov Models (HMMEditor. HMMEditor can visualize the profile HMM architecture, transition probabilities, and emission probabilities. Moreover, it provides functions to edit and save HMM and parameters. Furthermore, HMMEditor allows users to align a sequence against the profile HMM and to visualize the corresponding Viterbi path. Conclusion HMMEditor provides a set of unique functions to visualize and edit a profile HMM. It is a useful tool for biological sequence analysis and modeling. Both HMMEditor software and web service are freely available.

  1. HOPWA Performance Profiles

    Data.gov (United States)

    Department of Housing and Urban Development — HOPWA Performance Profiles are generated quarterly for all agencies receiving HOPWA formula or competitive grants. Performance Profiles are available at the national...

  2. DNA profiles from fingermarks.

    Science.gov (United States)

    Templeton, Jennifer E L; Linacre, Adrian

    2014-11-01

    Criminal investigations would be considerably improved if DNA profiles could be routinely generated from single fingermarks. Here we report a direct DNA profiling method that was able to generate interpretable profiles from 71% of 170 fingermarks. The data are based on fingermarks from all 5 digits of 34 individuals. DNA was obtained from the fingermarks using a swab moistened with Triton-X, and the fibers were added directly to one of two commercial DNA profiling kits. All profiles were obtained without increasing the number of amplification cycles; therefore, our method is ideally suited for adoption by the forensic science community. We indicate the use of the technique in a criminal case in which a DNA profile was generated from a fingermark on tape that was wrapped around a drug seizure. Our direct DNA profiling approach is rapid and able to generate profiles from touched items when current forensic practices have little chance of success.

  3. Microwave Radiometer Profiler

    Data.gov (United States)

    Oak Ridge National Laboratory — The microwave radiometer profiler (MWRP) provides vertical profiles of temperature, humidity, and cloud liquid water content as a function of height or pressure at...

  4. Predictive medicine

    NARCIS (Netherlands)

    Boenink, Marianne; Have, ten Henk

    2015-01-01

    In the last part of the twentieth century, predictive medicine has gained currency as an important ideal in biomedical research and health care. Research in the genetic and molecular basis of disease suggested that the insights gained might be used to develop tests that predict the future health sta

  5. Ligand efficiency-based support vector regression models for predicting bioactivities of ligands to drug target proteins.

    Science.gov (United States)

    Sugaya, Nobuyoshi

    2014-10-27

    The concept of ligand efficiency (LE) indices is widely accepted throughout the drug design community and is frequently used in a retrospective manner in the process of drug development. For example, LE indices are used to investigate LE optimization processes of already-approved drugs and to re-evaluate hit compounds obtained from structure-based virtual screening methods and/or high-throughput experimental assays. However, LE indices could also be applied in a prospective manner to explore drug candidates. Here, we describe the construction of machine learning-based regression models in which LE indices are adopted as an end point and show that LE-based regression models can outperform regression models based on pIC50 values. In addition to pIC50 values traditionally used in machine learning studies based on chemogenomics data, three representative LE indices (ligand lipophilicity efficiency (LLE), binding efficiency index (BEI), and surface efficiency index (SEI)) were adopted, then used to create four types of training data. We constructed regression models by applying a support vector regression (SVR) method to the training data. In cross-validation tests of the SVR models, the LE-based SVR models showed higher correlations between the observed and predicted values than the pIC50-based models. Application tests to new data displayed that, generally, the predictive performance of SVR models follows the order SEI > BEI > LLE > pIC50. Close examination of the distributions of the activity values (pIC50, LLE, BEI, and SEI) in the training and validation data implied that the performance order of the SVR models may be ascribed to the much higher diversity of the LE-based training and validation data. In the application tests, the LE-based SVR models can offer better predictive performance of compound-protein pairs with a wider range of ligand potencies than the pIC50-based models. This finding strongly suggests that LE-based SVR models are better than pIC50-based

  6. Personality Profiles and Frequent Heavy Drinking in Young Adulthood.

    Science.gov (United States)

    Zhang, Jieting; Bray, Bethany C; Zhang, Minqiang; Lanza, Stephanie T

    2015-07-01

    Few studies examining the link between personality and alcohol use have adopted a comprehensive modeling framework to take into account individuals' profiles across multiple personality traits. In this study, latent profile analysis (LPA) was applied to a national sample of young adults in the United States to identify subgroups defined by their profiles of mean scores on the Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness personality factors. Personality profiles were then used to predict heavy drinking. Five profiles were identified: Reserved, Rigid, Confident, Ordinary, and Resilient. Compared to individuals in the Ordinary profile, those with Reserved and Resilient profiles were at increased risk of frequent heavy drinking. These findings suggest which comprehensive personality profiles may place individuals at risk for problematic alcohol-related outcomes.

  7. Evoked emotions predict food choice.

    Directory of Open Access Journals (Sweden)

    Jelle R Dalenberg

    Full Text Available In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA and apply Multinomial Logit Models (MLM to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively. After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

  8. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach

    Directory of Open Access Journals (Sweden)

    Niu AQ

    2016-07-01

    Full Text Available Ai-qin Niu,1 Liang-jun Xie,2 Hui Wang,1 Bing Zhu,1 Sheng-qi Wang3 1Department of Gynecology, the First People’s Hospital of Shangqiu, Shangqiu, Henan, People’s Republic of China; 2Department of Image Diagnoses, the Third Hospital of Jinan, Jinan, Shandong, People’s Republic of China; 3Department of Mammary Disease, Guangdong Provincial Hospital of Chinese Medicine, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China Background: Estrogen receptors (ERs are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Methods: Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML methods. Results: The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior

  9. LocTree3 prediction of localization

    DEFF Research Database (Denmark)

    Goldberg, T.; Hecht, M.; Hamp, T.

    2014-01-01

    The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria...

  10. Extremal periodic wave profiles

    Directory of Open Access Journals (Sweden)

    E. van Groesen

    2007-01-01

    Full Text Available As a contribution to deterministic investigations into extreme fluid surface waves, in this paper wave profiles of prescribed period that have maximal crest height will be investigated. As constraints the values of the momentum and energy integrals are used in a simplified description with the KdV model. The result is that at the boundary of the feasible region in the momentum-energy plane, the only possible profiles are the well known cnoidal wave profiles. Inside the feasible region the extremal profiles of maximal crest height are "cornered" cnoidal profiles: cnoidal profiles of larger period, cut-off and periodically continued with the prescribed period so that at the maximal crest height a corner results.

  11. Coupled Thermodynamic Behavior of New Screw Compressors Rotors Profile

    Directory of Open Access Journals (Sweden)

    Arístides Rivera Torres

    2010-05-01

    Full Text Available The article displays an evaluation of the thermodynamic behavior of screw compressor rotors with new profiles, obtained with the help of the Scorpath 2000 software. This allows predicting precisely the operation of the compressor, as well as its thermodynamic evaluation, under equal conditions, with the work of other compressors fitted with rotor profiles of other kinds.

  12. YOUNG ATHLETES' MOTIVATIONAL PROFILES

    Directory of Open Access Journals (Sweden)

    Juan Antonio Moreno Murcia

    2007-06-01

    Full Text Available The aim of this study was to examine the relationship between motivational characteristics and dispositional flow. In order to accomplish this goal, motivational profiles emerging from key constructs within Achievement Goal Theory and Self-Determination Theory were related to the dispositional flow measures. A sample of 413 young athletes (Age range 12 to 16 years completed the PMCSQ-2, POSQ, SMS and DFS measures. Cluster analysis results revealed three profiles: a "self-determined profile" characterised by higher scores on the task-involving climate perception and on the task orientation; a "non-self-determined profile", characterised by higher scores on ego-involving climate perception and ego orientation; and a "low self-determined and low non-self-determined profile" which had the lowest dispositional flow. No meaningful differences were found between the "self-determined profile" and the "non-self-determined profile" in dispositional flow. The "self-determined profile" was more commonly associated with females, athletes practising individual sports and those training more than three days a week. The "non-self-determined profile" was more customary of males and athletes practising team sports as well as those training just two or three days a week

  13. Prediction Markets

    DEFF Research Database (Denmark)

    Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael

    2014-01-01

    In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...

  14. Household electricity demand profiles

    DEFF Research Database (Denmark)

    Marszal, Anna Joanna; Heiselberg, Per Kvols; Larsen, Olena Kalyanova

    2016-01-01

    Highlights •A 1-min resolution household electricity load model is presented. •Model adapts a bottom-up approach with single appliance as the main building block. •Load profiles are used to analyse the flexibility potential of household appliances. •Load profiles can be applied in other domains, e...

  15. Spiking the expectancy profiles

    DEFF Research Database (Denmark)

    Hansen, Niels Chr.; Loui, Psyche; Vuust, Peter

    Melodic expectations have long been quantified using expectedness ratings. Motivated by statistical learning and sharper key profiles in musicians, we model musical learning as a process of reducing the relative entropy between listeners' prior expectancy profiles and probability distributions...... learning over varying timescales enables listeners to generate expectations with reduced entropy....

  16. Reinforced aerodynamic profile

    DEFF Research Database (Denmark)

    2010-01-01

    The present invention relates to the prevention of deformations in an aerodynamic profile caused by lack of resistance to the bending moment forces that are created when such a profile is loaded in operation. More specifically, the invention relates to a reinforcing element inside an aerodynamic...

  17. Profiling the Mobile Customer

    DEFF Research Database (Denmark)

    Jessen, Pernille Wegener; King, Nancy J.

    2010-01-01

    of significant concerns about privacy and data protection. This second article in a two part series on "Profiling the Mobile Customer" explores how to best protect consumers' privacy and personal data through available mechanisms that include industry self-regulation, privacy-enhancing technologies......Mobile customers are increasingly being tracked and profiled by behavioural advertisers to enhance delivery of personalized advertising. This type of profiling relies on automated processes that mine databases containing personally-identifying or anonymous consumer data, and it raises a host...... discusses the current limitations of using technology to protect consumers from privacy abuses related to profiling. Concluding that industry self-regulation and available privacy-enhancing technologies will not be adequate to close important privacy gaps related to consumer profiling without legislative...

  18. Estimating Cognitive Profiles Using Profile Analysis via Multidimensional Scaling (PAMS)

    Science.gov (United States)

    Kim, Se-Kang; Frisby, Craig L.; Davison, Mark L.

    2004-01-01

    Two of the most popular methods of profile analysis, cluster analysis and modal profile analysis, have limitations. First, neither technique is adequate when the sample size is large. Second, neither method will necessarily provide profile information in terms of both level and pattern. A new method of profile analysis, called Profile Analysis via…

  19. Biomarkers of Fatigue: Metabolomics Profiles Predictive of Cognitive Performance

    Science.gov (United States)

    2013-05-01

    homovallinate, 3-hydroxyisovalerate, alanine, 2,2-dimethylsuccinate and taurine . Tyrosine and homovanillate are metabolites associated with the dopaminergic...2,2- dimethylsuccinate and taurine were elevated in the urine of fatigue-sensitive subjects and can be linked to high percentage dietary...to show how they compare. Thus PCA models were constructed to maximize visualization of specific responses based upon the nature of the effects

  20. Gene expression profiling predicts clinical outcome of breast cancer

    NARCIS (Netherlands)

    Veer, L.J. van 't; Dai, H.; Vijver, H. van de; He, Y.D.; Hart, A.A.M.; Mao, M.; Peterse, H.L.; Kooy, K. van der; Marton, M.J.; Witteveen, A.T.; Schreiber, G.J.; Kerkhoven, R.M.; Roberts, C.; Linsley, P.S.; Bernards, R.A.; Friend, S.H.

    2002-01-01

    Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour.

  1. First trimester maternal urinary metabolomic profile to predict macrosomia

    LENUS (Irish Health Repository)

    Walshe, J

    2011-02-01

    Institute of Obstetricians & Gynaecologists, RCPI Four Provinces Meeting, Junior Obstetrics & Gynaecology Society Annual Scientific Meeting, Royal Academy of Medicine in Ireland Dublin Maternity Hospitals Reports Meeting, Nov 2010

  2. Genetic risk profiling for prediction of type 2 diabetes

    NARCIS (Netherlands)

    R. Mihaescu (Raluca); J.B. Meigs (James); E.J.G. Sijbrands (Eric); A.C.J.W. Janssens (Cécile)

    2011-01-01

    textabstractType 2 diabetes (T2D) is a common disease caused by a complex interplay between many genetic and environmental factors. Candidate gene studies and recent collaborative genome-wide association efforts revealed at least 38 common single nucleotide polymorphisms (SNPs) associated with incre

  3. Predicting Web Page Accesses, using Users’ Profile and Markov Models

    OpenAIRE

    Zeynab Fazelipour

    2016-01-01

    Nowadays web is an important source for information retrieval, the sources on WWW are constantly increasing and the users accessing the web have different backgrounds. Consequently, finding the information which satisfies the personal users needs is not so easy. Exploration of users behaviors in the web, as a method for extracting the knowledge lying behind the way of how the users interact with the web, is considered as an important tool in the field of web mining. By identifying user's beha...

  4. Prediction of wine color from phenolic profiles of red grapes

    DEFF Research Database (Denmark)

    Jensen, Jacob Skibsted

    2008-01-01

    afhandlingen påviste de fremsatte hypoteser og ser lovende ud med henblik på at introducere hurtige og objektive målinger af drue phenoler til at forudsige farve parametre i rødvin. Resultaterne var også lovende med henblik på at anvende FT-MIR spektroskopi til at kvantificere tannin i rødvin og druer....

  5. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    2008-01-01

    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents the state-of-the art: an analytical model which describes chloride profiles in concrete as function of depth...... makes physical sense for the design engineer, i.e. the achieved chloride diffusion coefficients at 1 year and 100 years, D1 and D100 respectively, and the corresponding achieved chloride concentrations at the exposed concrete surface, C1 and C100. Data from field exposure supports the assumption of time...... dependent surface chloride concentrations and the diffusion coefficients. Model parameters for Portland cement concretes with and without silica fume and fly ash in marine atmospheric and submerged South Scandinavian environment are suggested in a companion paper based on 10 years field exposure data....

  6. Profiles in Cancer Research

    Science.gov (United States)

    These articles put a face to some of the thousands of individuals who contribute to NCI’s cancer research efforts. The profiles highlight the work of scientists and clinicians and describe the circumstances and motivation behind their work.

  7. Fishing Community Profiles

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — To enable fisheries managers to comply with National Standard 8 (NS8), NMFS social scientists around the nation are preparing fishing community profiles that present...

  8. Wind Profiling Radar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Clutter present in radar return signals as used for wind profiling is substantially removed by carrying out a Daubechies wavelet transformation on a time series of...

  9. Beach Profile Locations

    Data.gov (United States)

    California Department of Resources — Beaches are commonly characterized by cross-shore surveys. The resulting profiles represent the elevation of the beach surface and nearshore seabed from the back of...

  10. Qualitative Value Profiling

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen; Bjerre, Mogens

    2015-01-01

    Qualitative value profiling (QVP) is a relatively unknown method of strategic analysis for companies in international business-to-business settings. The purpose of QVP is to reduce the information complexity that is faced by international companies in dealing with business partners. The QVP method...... allows the development of 1) profiles of the target country in which operations are to take place, 2) profiles of the buying center (i.e. the group of decision makers) in the partner company, and 3) profiles of the product/service offering. It also allows the development of a semantic scaling method...... for deeper analysis of all involved factors. This paper presents the method and compares and contrasts it with other similar methods like the PESTELE method known from corporate strategy, the STEEPAL method known from scenario analysis, and the Politics-Institutions-Economy (PIE) framework known from...

  11. Profile of Older Americans

    Science.gov (United States)

    ... covers 15 topical areas, including population, income and poverty, living arrangements, education, health, and caregiving. A Profile ... Elder Justice Innovation Grants Late Life Domestic Violence World Elder Abuse Awareness Day State Grants to Enhance ...

  12. Prescription Drug Profiles PUF

    Data.gov (United States)

    U.S. Department of Health & Human Services — This release contains the Prescription Drug Profiles Public Use Files (PUFs) drawn from Medicare prescription drug claims for the year of the date on which the...

  13. Modeling dune response using measured and equilibrium bathymetric profiles

    Science.gov (United States)

    Fauver, Laura A.; Thompson, David M.; Sallenger, Asbury H.

    2007-01-01

    Coastal engineers typically use numerical models such as SBEACH to predict coastal change due to extreme storms. SBEACH model inputs include pre-storm profiles, wave heights and periods, and water levels. This study focuses on the sensitivity of SBEACH to the details of pre-storm bathymetry. The SBEACH model is tested with two initial conditions for bathymetry, including (1) measured bathymetry from lidar, and (2) calculated equilibrium profiles. Results show that longshore variability in the predicted erosion signal is greater over measured bathymetric profiles, due to longshore variations in initial surf zone bathymetry. Additionally, patterns in predicted erosion can be partially explained by the configuration of the inner surf zone from the shoreline to the trough, with surf zone slope accounting for 67% of the variability in predicted erosion volumes.

  14. Accelerating the Original Profile Kernel.

    Directory of Open Access Journals (Sweden)

    Tobias Hamp

    Full Text Available One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.

  15. Accelerated Profile HMM Searches.

    Directory of Open Access Journals (Sweden)

    Sean R Eddy

    2011-10-01

    Full Text Available Profile hidden Markov models (profile HMMs and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.

  16. Country profile: Hungary

    Energy Technology Data Exchange (ETDEWEB)

    1991-09-01

    Country Profile: Hungary has been prepared as a background document for use by US Government agencies and US businesses interested in becoming involved with the new democracies of Eastern Europe as they pursue sustainable economic development. The focus of the Profile is on energy and highlights information on Hungary`s energy supply, demand, and utilization. It identifies patterns of energy usage in the important economic sectors, especially industry, and provides a preliminary assessment for opportunities to improve efficiencies in energy production, distribution and use by introducing more efficient technologies. The use of more efficient technologies would have the added benefit of reducing the environmental impact which, although is not the focus of the report, is an issue that effects energy choices. The Profile also presents considerable economic information, primarily in the context of how economic restructuring may affect energy supply, demand, and the introduction of more efficient technologies.

  17. Country profile: Hungary

    Energy Technology Data Exchange (ETDEWEB)

    1991-09-01

    Country Profile: Hungary has been prepared as a background document for use by US Government agencies and US businesses interested in becoming involved with the new democracies of Eastern Europe as they pursue sustainable economic development. The focus of the Profile is on energy and highlights information on Hungary's energy supply, demand, and utilization. It identifies patterns of energy usage in the important economic sectors, especially industry, and provides a preliminary assessment for opportunities to improve efficiencies in energy production, distribution and use by introducing more efficient technologies. The use of more efficient technologies would have the added benefit of reducing the environmental impact which, although is not the focus of the report, is an issue that effects energy choices. The Profile also presents considerable economic information, primarily in the context of how economic restructuring may affect energy supply, demand, and the introduction of more efficient technologies.

  18. Detonation Wave Profile

    Energy Technology Data Exchange (ETDEWEB)

    Menikoff, Ralph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-12-14

    The Zel’dovich-von Neumann-Doering (ZND) profile of a detonation wave is derived. Two basic assumptions are required: i. An equation of state (EOS) for a partly burned explosive; P(V, e, λ). ii. A burn rate for the reaction progress variable; d/dt λ = R(V, e, λ). For a steady planar detonation wave the reactive flow PDEs can be reduced to ODEs. The detonation wave profile can be determined from an ODE plus algebraic equations for points on the partly burned detonation loci with a specified wave speed. Furthermore, for the CJ detonation speed the end of the reaction zone is sonic. A solution to the reactive flow equations can be constructed with a rarefaction wave following the detonation wave profile. This corresponds to an underdriven detonation wave, and the rarefaction is know as a Taylor wave.

  19. Predicting risky behavior in social communities

    CERN Document Server

    Simpson, Olivia

    2016-01-01

    Predicting risk profiles of individuals in networks (e.g.~susceptibility to a particular disease, or likelihood of smoking) is challenging for a variety of reasons. For one, `local' features (such as an individual's demographic information) may lack sufficient information to make informative predictions; this is especially problematic when predicting `risk,' as the relevant features may be precisely those that an individual is disinclined to reveal in a survey. Secondly, even if such features are available, they still may miss crucial information, as `risk' may be a function not just of an individual's features but also those of their friends and social communities. Here, we predict individual's risk profiles as a function of both their local features and those of their friends. Instead of modeling influence from the social network directly (which proved difficult as friendship links may be sparse and partially observed), we instead model influence by discovering social communities in the network that may be ...

  20. Constructing Data Curation Profiles

    Directory of Open Access Journals (Sweden)

    Michael Witt

    2009-12-01

    Full Text Available This paper presents a brief literature review and then introduces the methods, design, and construction of the Data Curation Profile, an instrument that can be used to provide detailed information on particular data forms that might be curated by an academic library. These data forms are presented in the context of the related sub-disciplinary research area, and they provide the flow of the research process from which these data are generated. The profiles also represent the needs for data curation from the perspective of the data producers, using their own language. As such, they support the exploration of data curation across different research domains in real and practical terms. With the sponsorship of the Institute of Museum and Library Services, investigators from Purdue University and the University of Illinois interviewed 19 faculty subjects to identify needs for discovery, access, preservation, and reuse of their research data. For each subject, a profile was constructed that includes information about his or her general research, data forms and stages, value of data, data ingest, intellectual property, organization and description of data, tools, interoperability, impact and prestige, data management, and preservation. Each profile also presents a specific dataset supplied by the subject to serve as a concrete example. The Data Curation Profiles are being published to a public wiki for questions and discussion, and a blank template will be disseminated with guidelines for others to create and share their own profiles. This study was conducted primarily from the viewpoint of librarians interacting with faculty researchers; however, it is expected that these findings will complement a wide variety of data curation research and practice outside of librarianship and the university environment.

  1. Country Profiles, Malaysia.

    Science.gov (United States)

    Marzuki, Ariffin Bin; Peng, J. Y.

    A profile of Malaysia is sketched in this paper. Emphasis is placed on the nature, scope, and accomplishments of population activities in the country. Topics and sub-topics include: location and description of the country; population (size, growth patterns, age structure, urban/rural distribution, ethnic and religious composition, migration,…

  2. English Teaching Profile: Mexico.

    Science.gov (United States)

    British Council, London (England). English Language and Literature Div.

    This profile of the English language teaching situation in Mexico examines the role of English in society and in the educational system. It is noted that the extent to which English is used in Mexico is affected by the country's proximity to the United States. The educational system is described, with emphasis on English instruction which begins…

  3. Country Profiles, Pakistan.

    Science.gov (United States)

    Hardee, J. Gilbert; Satterthwaite, Adaline P.

    A profile of Pakistan is sketched in this paper. Emphasis is placed on the nature, scope, and accomplishments of population activities in the country. Topics and sub-topics include: location and description of the country; population (size, growth patterns, age structure, urban/rural distribution, ethnic and religious composition, migration,…

  4. Country Education Profiles: Algeria.

    Science.gov (United States)

    International Bureau of Education, Geneva (Switzerland).

    One of a series of profiles prepared by the Cooperative Educational Abstracting Service, this brief outline provides basic background information on educational principles, system of administration, structure and organization, curricula, and teacher training in Algeria. Statistics provided by the Unesco Office of Statistics show enrollment at all…

  5. Cohort Profile Update

    DEFF Research Database (Denmark)

    Omland, Lars Haukali; Ahlström, Magnus Glindvad; Obel, Niels

    2014-01-01

    The DHCS is a cohort of all HIV-infected individuals seen in one of the eight Danish HIV centres after 31 December 1994. Here we update the 2009 cohort profile emphasizing the development of the cohort. Every 12-24 months, DHCS is linked with the Danish Civil Registration System (CRS) in order...

  6. Sensing the wind profile

    DEFF Research Database (Denmark)

    Pena Diaz, Alfredo

    prole. The boundary-layer height is derived in nearneutral and stable conditions based on turbulent momentum uxes only and in unstable conditions based on profiles of aerosol backscatter from ceilometer measurements. The lidar measuring technique is used to estimate momentum flux, showing high agreement...

  7. COMPENDEX Profile Adjustment Manual.

    Science.gov (United States)

    Standera, Oldrich

    If an information system is to survive, the users must be satisfied that it meets their needs promptly and consistently. It is essential to react quickly to any undesired result such as an extemely high or low output, too low a relevance or recall, or both. The search editor should feel responsbile not only for the profile setup but also for its…

  8. Gaussian Random Field: Physical Origin of Sersic Profiles

    Science.gov (United States)

    Cen, Renyue

    2014-08-01

    While the Sersic profile family provides adequate fits for the surface brightness profiles of observed galaxies, its physical origin is unknown. We show that if the cosmological density field is seeded by random Gaussian fluctuations, as in the standard cold dark matter model, galaxies with steep central profiles have simultaneously extended envelopes of shallow profiles in the outskirts, whereas galaxies with shallow central profiles are accompanied by steep density profiles in the outskirts. These properties are in accord with those of the Sersic profile family. Moreover, galaxies with steep central profiles form their central regions in smaller denser subunits that possibly merge subsequently, which naturally leads to the formation of bulges. In contrast, galaxies with shallow central profiles form their central regions in a coherent fashion without significant substructure, a necessary condition for disk galaxy formation. Thus, the scenario is self-consistent with respect to the correlation between observed galaxy morphology and the Sersic index. We further predict that clusters of galaxies should display a similar trend, which should be verifiable observationally.

  9. Distributed user profiling via spectral methods

    Directory of Open Access Journals (Sweden)

    Dan-Cristian Tomozei

    2014-09-01

    Full Text Available User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local information exchanges between users. We compute a profile vector for each user (i.e., a low-dimensional vector that characterises her taste via spectral transformation of observed user-produced ratings for items. Our two main contributions follow: (i We consider a low-rank probabilistic model of user taste. More specifically, we consider that users and items are partitioned in a constant number of classes, such that users and items within the same class are statistically identical. We prove that without prior knowledge of the compositions of the classes, based solely on few random observed ratings (namely O(N log N such ratings for N users, we can predict user preference with high probability for unrated items by running a local vote among users with similar profile vectors. In addition, we provide empirical evaluations characterising the way in which spectral profiling performance depends on the dimension of the profile space. Such evaluations are performed on a data set of real user ratings provided by Netflix. (ii We develop distributed algorithms which provably achieve an embedding of users into a low-dimensional space, based on spectral transformation. These involve simple message passing among users, and provably converge to the desired embedding. Our method essentially relies on a novel combination of gossiping and the algorithm proposed by Oja and Karhunen.

  10. Statistical ensembles of virialized halo matter density profiles

    CERN Document Server

    Carron, Julien

    2013-01-01

    We define and study statistical ensembles of matter density profiles describing spherically symmetric, virialized dark matter haloes of finite extent with a given mass and total gravitational potential energy. We provide an exact solution for the grand canonical partition functional, and show its equivalence to that of the microcanonical ensemble. We obtain analytically the mean profiles that correspond to an overwhelming majority of micro-states. All such profiles have an infinitely deep potential well, with the singular isothermal sphere arising in the infinite temperature limit. Systems with virial radius larger than gravitational radius exhibit a localization of a finite fraction of the energy in the very center. The universal logarithmic inner slope of unity of the NFW haloes is predicted at any mass and energy if an upper bound is set to the maximal depth of the potential well. In this case, the statistically favored mean profiles compare well to the NFW profiles. For very massive haloes the agreement b...

  11. High throughput drug profiling

    OpenAIRE

    Entzeroth, Michael; Chapelain, Béatrice; Guilbert, Jacques; Hamon, Valérie

    2000-01-01

    High throughput screening has significantly contributed to advances in drug discovery. The great increase in the number of samples screened has been accompanied by increases in costs and in the data required for the investigated compounds. High throughput profiling addresses the issues of compound selectivity and specificity. It combines conventional screening with data mining technologies to give a full set of data, enabling development candidates to be more fully compared.

  12. Wide HI profile galaxies

    CERN Document Server

    Brosch, Noah; Zitrin, Adi

    2011-01-01

    We investigate the nature of objects in a complete sample of 28 galaxies selected from the first sky area fully covered by ALFALFA, being well-detected and having HI profiles wider than 550 km/s. The selection does not use brightness, morphology, or any other property derived from optical or other spectral bands. We investigate the degree of isolation, the morphology, and other properties gathered or derived from open data bases and show that some objects have wide HI profiles probably because they are disturbed or are interacting, or might be confused in the ALFALFA beam. We identify a sub-sample of 14 galaxies lacking immediate interacting neighbours and showing regular, symmetric, two-horned HI profiles that we propose as candidate high-mass disk systems (CHMDs). We measure the net-Halpha emission from the CHMDs and combine this with public multispectral data to model the global star formation (SF) properties of each galaxy. The Halpha observations show SFRs not higher than a few solar masses per year. Sim...

  13. Practical Differential Profiling

    Energy Technology Data Exchange (ETDEWEB)

    Schulz, M; De Supinski, B R

    2007-02-04

    Comparing performance profiles from two runs is an essential performance analysis step that users routinely perform. In this work we present eGprof, a tool that facilitates these comparisons through differential profiling inside gprof. We chose this approach, rather than designing a new tool, since gprof is one of the few performance analysis tools accepted and used by a large community of users. eGprof allows users to 'subtract' two performance profiles directly. It also includes callgraph visualization to highlight the differences in graphical form. Along with the design of this tool, we present several case studies that show how eGprof can be used to find and to study the differences of two application executions quickly and hence can aid the user in this most common step in performance analysis. We do this without requiring major changes on the side of the user, the most important factor in guaranteeing the adoption of our tool by code teams.

  14. Leflunomide : a manageable safety profile

    NARCIS (Netherlands)

    Riel, P.L.C.M. van; Smolen, J.S.; Emery, P.; Kalden, J.R.; Dougados, M.; Strand, C.V.; Breedveld, F.C.

    2004-01-01

    The safety profile of leflunomide in the treatment of rheumatoid arthritis has been well documented in clinical trials, postmarketing surveillance, and epidemiological studies. Both postmarketing surveillance and epidemiological study results are consistent with the safety profile of leflunomide rep

  15. Time profile of the slowly extracted beam

    CERN Document Server

    Pullia, M

    1997-01-01

    An important spin-off from accelerators is the use of synchrotrons for cancer therapy. For this application a precise control of the slow extraction is needed to satisfy the medical specifications for the online measurement and control of the delivered dose. This has led to a renewed interest in the basic theory of third-order resonance extraction. In the present paper, an analytic study of the time profile of the extracted beam is made by first considering the time profile of an elementary strip of monoenergetic particles from the side of the shrinking stable triangle. This basic result is then used to predict the characteristics of the spills for the most common extraction configurations. The influence of ripples whose period is comparable to the transit time of a particle in the resonance is also analyzed. Simulations of the extraction process that confirm the analytic study are included.

  16. The Trajectory Synthesizer Generalized Profile Interface

    Science.gov (United States)

    Lee, Alan G.; Bouyssounouse, Xavier; Murphy, James R.

    2010-01-01

    The Trajectory Synthesizer is a software program that generates aircraft predictions for Air Traffic Management decision support tools. The Trajectory Synthesizer being used by researchers at NASA Ames Research Center was restricted in the number of trajectory types that could be generated. This limitation was not sufficient to support the rapidly changing Air Traffic Management research requirements. The Generalized Profile Interface was developed to address this issue. It provides a flexible approach to describe the constraints applied to trajectory generation and may provide a method for interoperability between trajectory generators. It also supports the request and generation of new types of trajectory profiles not possible with the previous interface to the Trajectory Synthesizer. Other enhancements allow the Trajectory Synthesizer to meet the current and future needs of Air Traffic Management research.

  17. Hanford Site Ecological Quality Profile

    Energy Technology Data Exchange (ETDEWEB)

    Bilyard, Gordon R.; Sackschewsky, Michael R.; Tzemos, Spyridon

    2002-02-17

    This report reviews the ecological quality profile methodology and results for the Hanford Site. It covers critical ecological assets and terrestrial resources, those in Columbia River corridor and those threatened and engdangered, as well as hazards and risks to terrestrial resources. The features of a base habitat value profile are explained, as are hazard and ecological quality profiles.

  18. Oceanographic station, temperature profiles, meteorological, and other data from XBT and bottle casts from NOAA Ship OREGON II as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1972-07-13 to 1972-08-08 (NODC Accession 7300271)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic station, temperature profiles, meteorological, and other data were collected from bottle and XBT casts from NOAA Ship OREGON II from 13 July 1972 to 08...

  19. Oceanographic Station Data and temperature profiles from CTD, XBT, and bottle casts from NOAA Ship ALBATROSS IV and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1973-01-01 to 1973-03-29 (NODC Accession 7300686)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from CTD, XBT, and bottle casts from NOAA Ship ALBATROSS IV and other platforms from 01 January...

  20. Oceanographic Station Data and temperature profiles from XBT, CTD, and bottle casts from NOAA Ship ALBATROSS IV as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1974-03-13 to 1975-05-12 (NODC Accession 7600874)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station Data and temperature profiles were collected from XBT, CTD, and bottle casts from NOAA Ship ALBATROSS IV from 13 March 1974 to 12 May 1975....

  1. Oceanographic station, temperature profiles, meteorological, and other data from bottle and XBT from the DOLPHIN and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1973-10-23 to 1973-11-16 (NODC Accession 7400207)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic station, temperature profiles, meteorological, and other data were collected from bottle and XBT casts from the DOLPHIN and other platforms from 23...

  2. Oceanographic Station, temperature profiles, and other data from CTD, XBT, and bottle casts from NOAA Ship DELAWARE II as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 1972-07-01 to 1972-08-13 (NODC Accession 7201299)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Station,temperature profiles, and other data were collected from CTD, XBT, and bottle casts from NOAA Ship DELAWARE II from 01 July 1972 to 13 August...

  3. Oceanographic station, temperature profile, meteorological, and other data from bottle and XBT casts from the ARGUS and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1977-10-18 to 1978-09-19 (NODC Accession 8500103)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic station, temperature profile, meteorological, and other data were collected from bottle and XBT casts from the ARGUS and other platforms from 18...

  4. Oceanographic station, temperature profile, meteorological, and other data from bottle and XBT casts from the DOLPHIN as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1973-05-15 to 1973-05-27 (NODC Accession 7400065)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic station, temperature profile, meteorological, and other data were collected from bottle and XBT casts from the DOLPHIN from 15 May 1973 to 27 May 1973....

  5. [Evaluation of nutrient release profiles from polymer coated fertilizers using Fourier transform mid-infrared photoacoustic spectroscopy].

    Science.gov (United States)

    Shen, Ya-zhen; Du, Chang-wen; Zhou, Jian-min; Wang, Huo-yan; Chen, Xiao-qin

    2012-02-01

    The acrylate-like materials were used to develop the polymer coated controlled release fertilizer, the nutrients release profiles were determined, meanwhile the Fourier transform mid-infrared photoacoustic spectra of the coatings were recorded and characterized; GRNN model was used to predict the nutrients release profiles using the principal components of the mid-infrared photoacoustic spectra as input. Results showed that the GRNN model could fast and effectively predict the nutrient release profiles, and the predicted calibration coefficients were more than 0.93; on the whole, the prediction errors (RMSE) were influenced by the profiling depth of the spectra, the average prediction error was 10.28%, and the spectra from the surface depth resulted in a lowest prediction error with 7.14%. Therefore, coupled with GRNN modeling, Fourier transform mid-infrared photoacoustic spectroscopy can be used as an alternative new technique in the fast and accurate prediction of nutrient release from polymer coated fertilizer.

  6. Transcript and protein profiling identify candidate gene sets of potential adaptive significance in New Zealand Pachycladon

    Directory of Open Access Journals (Sweden)

    Schmidt Silvia

    2010-05-01

    Full Text Available Abstract Background Transcript profiling of closely related species provides a means for identifying genes potentially important in species diversification. However, the predictive value of transcript profiling for inferring downstream-physiological processes has been unclear. In the present study we use shotgun proteomics to validate inferences from microarray studies regarding physiological differences in three Pachycladon species. We compare transcript and protein profiling and evaluate their predictive value for inferring glucosinolate chemotypes characteristic of these species. Results Evidence from heterologous microarrays and shotgun proteomics revealed differential expression of genes involved in glucosinolate hydrolysis (myrosinase-associated proteins and biosynthesis (methylthioalkylmalate isomerase and dehydrogenase, the interconversion of carbon dioxide and bicarbonate (carbonic anhydrases, water use efficiency (ascorbate peroxidase, 2 cys peroxiredoxin, 20 kDa chloroplastic chaperonin, mitochondrial succinyl CoA ligase and others (glutathione-S-transferase, serine racemase, vegetative storage proteins, genes related to translation and photosynthesis. Differences in glucosinolate hydrolysis products were directly confirmed. Overall, prediction of protein abundances from transcript profiles was stronger than prediction of transcript abundance from protein profiles. Protein profiles also proved to be more accurate predictors of glucosinolate profiles than transcript profiles. The similarity of species profiles for both transcripts and proteins reflected previously inferred phylogenetic relationships while glucosinolate chemotypes did not. Conclusions We have used transcript and protein profiling to predict physiological processes that evolved differently during diversification of three Pachycladon species. This approach has also identified candidate genes potentially important in adaptation, which are now the focus of ongoing study

  7. A PROSPECTIVE TRIAL OF THE FETAL BIOPHYSICAL PROFILE VERSUS MODIFIED BIOPHYSICAL PROFILE IN THE MANAGEMENT OF HIGH RISK PREGNANCIES

    Directory of Open Access Journals (Sweden)

    A. Jamal

    2007-07-01

    Full Text Available "nThe original biophysical profile is time consuming and costly. This study was performed to compare diagnostic value of the original fetal biophysical profile to the modified biophysical profile. Patients were selected from high risk pregnancies referred for fetal assessment and were randomly assigned to two groups. The measures of outcomes were perinatal mortality, Cesarean section for abnormal test, meconium-stained amniotic fluid and 5-minute Apgar score < 7. Diagnostic values of tests were assessed in terms of the incidence of abnormal outcome. In addition comparisons between the positive and negative predictive values of each of these tests as well as the sensitivity and specificity of the tests were reviewed. A total of 200 patients were entered into the study; 104 pregnancies were managed by the original biophysical profile and 96 pregnancies by the modified biophysical profile. There were 30 abnormal (31.3% in modified biophysical profile and 24 (23.1% abnormal tests in original one. There was significant difference in the incidence of meconium passage between two groups. Cesarean section for abnormal tests was 27 of 30 abnormal test (90% in modified and 22 of 24 (91.6% in original profile that was similar in both groups. There was not significant difference in Apgar score < 7 between two groups. We did not find significant difference with comparison of the sensitivity, specificity and negative predictive value of two tests for all measures of outcome except the positive predictive value of meconium passage. Original biophysical profile is more costly and time consuming than modified one.

  8. Surface tension profiles in vertical soap films

    Science.gov (United States)

    Adami, N.; Caps, H.

    2015-01-01

    Surface tension profiles in vertical soap films are experimentally investigated. Measurements are performed by introducing deformable elastic objets in the films. The shape adopted by those objects once set in the film is related to the surface tension value at a given vertical position by numerically solving the adapted elasticity equations. We show that the observed dependency of the surface tension versus the vertical position is predicted by simple modeling that takes into account the mechanical equilibrium of the films coupled to previous thickness measurements.

  9. Atypical Log D profile of rifampicin

    Directory of Open Access Journals (Sweden)

    Mariappan T

    2007-01-01

    Full Text Available The distribution coefficient (log D values of rifampicin, an essential first-line antitubercular drug, at gastrointestinal pH conditions are not reported in literature. Hence determinations were made using n-octanol and buffers ranging between pH 1-7. Also, log D values were predicted using Prolog D. Both the determinations showed opposite behaviour. The atypical experimental log D profile of rifampicin could be attributed to its surface-active properties, which also explained the reported permeability behaviour of the drug in various gastrointestinal tract segments.

  10. Qualitative Value Profiling

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen; Bjerre, Mogens

    2015-01-01

    Qualitative value profiling (QVP) is a relatively unknown method of strategic analysis for companies in international business-to-business settings. The purpose of QVP is to reduce the information complexity that is faced by international companies in dealing with business partners. The QVP method...... for deeper analysis of all involved factors. This paper presents the method and compares and contrasts it with other similar methods like the PESTELE method known from corporate strategy, the STEEPAL method known from scenario analysis, and the Politics-Institutions-Economy (PIE) framework known from...

  11. Technological requirements of profile machining

    Institute of Scientific and Technical Information of China (English)

    PARK Sangchul; CHUNG Yunchan

    2006-01-01

    The term ‘profile machining’is used to refer to the milling of vertical surfaces described by profile curves. Profile machining requires higher precision (1/1000 mm) than regular 3D machining (1/100 mm) with the erosion of sharp vertices should being especially avoided. Although, profile machining is very essential for making trimming and flangedies, it seldom brought into focus. This paper addresses the technological requirements of profile machining including machining width and depth control,minimizing toolware, and protecting sharp vertices. Issues of controller alarms are also addressed.

  12. Integrative structural modeling with small angle X-ray scattering profiles

    Directory of Open Access Journals (Sweden)

    Schneidman-Duhovny Dina

    2012-07-01

    Full Text Available Abstract Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types.

  13. Modified power law equations for vertical wind profiles. [in investigation of windpower plant siting

    Science.gov (United States)

    Spera, D. A.; Richards, T. R.

    1979-01-01

    In an investigation of windpower plant siting, equations are presented and evaluated for a wind profile model which incorporates both roughness and wind speed effects, while retaining the basic simplicity of the Hellman power law. These equations recognize the statistical nature of wind profiles and are compatible with existing analytical models and recent wind profile data. Predictions of energy output based on the proposed profile equations are 10% to 20% higher than those made with the 1/7 power law. In addition, correlation between calculated and observed blade loads is significantly better at higher wind speeds when the proposed wind profile model is used than when a constant power model is used.

  14. Stratigraphic Profiles for Selected Hanford Site Seismometer Stations and Other Locations

    Energy Technology Data Exchange (ETDEWEB)

    Last, George V.

    2014-02-01

    Stratigraphic profiles were constructed for eight selected Hanford Site seismometer stations, five Hanford Site facility reference locations, and seven regional three-component broadband seismometer stations. These profiles provide interpretations of the subsurface layers to support estimation of ground motions from past earthquakes, and the prediction of ground motions from future earthquakes. In most cases these profiles terminated at the top of the Wanapum Basalt, but at selected sites profiles were extended down to the top of the crystalline basement. The composite one-dimensional stratigraphic profiles were based primarily on previous interpretations from nearby boreholes, and in many cases the nearest deep borehole is located kilometers away.

  15. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  16. Deflagration Wave Profiles

    Energy Technology Data Exchange (ETDEWEB)

    Menikoff, Ralph [Los Alamos National Laboratory

    2012-04-03

    Shock initiation in a plastic-bonded explosives (PBX) is due to hot spots. Current reactive burn models are based, at least heuristically, on the ignition and growth concept. The ignition phase occurs when a small localized region of high temperature (or hot spot) burns on a fast time scale. This is followed by a growth phase in which a reactive front spreads out from the hot spot. Propagating reactive fronts are deflagration waves. A key question is the deflagration speed in a PBX compressed and heated by a shock wave that generated the hot spot. Here, the ODEs for a steady deflagration wave profile in a compressible fluid are derived, along with the needed thermodynamic quantities of realistic equations of state corresponding to the reactants and products of a PBX. The properties of the wave profile equations are analyzed and an algorithm is derived for computing the deflagration speed. As an illustrative example, the algorithm is applied to compute the deflagration speed in shock compressed PBX 9501 as a function of shock pressure. The calculated deflagration speed, even at the CJ pressure, is low compared to the detonation speed. The implication of this are briefly discussed.

  17. Concentration profiles for fine and coarse sediments suspended by waves over ripples: An analytical study with the 1-DV gradient diffusion model

    CERN Document Server

    Absi, Rafik

    2010-01-01

    Field and laboratory measurements of suspended sediments over wave ripples show, for time-averaged concentration profiles in semi-log plots, a contrast between upward convex profiles for fine sand and upward concave profiles for coarse sand. Careful examination of experimental data for coarse sand shows a near-bed upward convex profile beneath the main upward concave profile. Available models fail to predict these two profiles for coarse sediments. The 1-DV gradient diffusion model predicts the main upward concave profile for coarse sediments thanks to a suitable $\\beta$(y)-function (where $\\beta$ is the inverse of the turbulent Schmidt number and y is the distance from the bed). In order to predict the near-bed upward convex profile, an additional parameter {\\alpha} is needed. This parameter could be related to settling velocity ($\\alpha$ equal to inverse of dimensionless settling velocity) or to convective sediment entrainment process. The profiles are interpreted by a relation between second derivative of ...

  18. Prognostic Gene Expression Profiles in Breast Cancer

    DEFF Research Database (Denmark)

    Sørensen, Kristina Pilekær

    Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... and the time of event. Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent...

  19. Gaussian mixture models as flux prediction method for central receivers

    Science.gov (United States)

    Grobler, Annemarie; Gauché, Paul; Smit, Willie

    2016-05-01

    Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.

  20. Outsmarting cancer: the power of hybrid genomic/proteomic biomarkers to predict drug response.

    Science.gov (United States)

    Rexer, Brent N; Arteaga, Carlos L

    2014-01-01

    A recent study by Niepel and colleagues describes a novel approach to predicting response to targeted anti-cancer therapies. The authors used biochemical profiling of signaling activity in basal and ligand-stimulated states for a panel of receptor and intracellular kinases to develop predictive models of drug sensitivity. In some cases, the response to ligand stimulation predicted drug response better than did target abundance or genomic alterations in the targeted pathway. Furthermore, combining biochemical profiles with genomic information was better at predicting drug response. This work suggests that incorporating biochemical signaling profiles with genomic alterations should provide powerful predictors of response to molecularly targeted therapies.

  1. The effects of profiles on supersonic jet noise

    Science.gov (United States)

    Tiwari, S. N.; Bhat, T. R. S.

    1994-01-01

    The effect of velocity profiles on supersonic jet noise are studied by using stability calculations made for a shock-free coannular jet, with both the inner and outer flows supersonic. The Mach wave emission process is modeled as the noise generated by the large scale turbulent structures or the instability waves in the mixing region. Both the vortex-sheet and the realistic finite thickness shear layer models are considered. The stability calculations were performed for both inverted and normal velocity profiles. Comparisons are made with the results for an equivalent single jet, based on equal thrust, mass flow rate and exit area to that of the coannular jet. The advantages and disadvantages of these velocity profiles as far as noise radiation is concerned are discussed. It is shown that the Rayleigh's model prediction of the merits and demerits of different velocity profiles are in good agreement with the experimental data.

  2. Losartan: Comprehensive Profile.

    Science.gov (United States)

    Al-Majed, Abdul-Rahman A; Assiri, Ebrahim; Khalil, Nasr Y; Abdel-Aziz, Hatem A

    2015-01-01

    Losartan (Cozaar™) is an angiotensin II receptor antagonist with antihypertensive activity. It is used in the management of hypertension and heart failure. Nomenclature, formulae, elemental analysis, and appearance of the drug are included in this review. The uses, applications, and the variety of synthetic pathways of this drug are outlined. Physical characteristics including: ionization constant, solubility, X-ray powder diffraction pattern, thermal methods of analysis, UV spectrum, IR spectrum, mass spectrum with fragmentation patterns, and NMR (1H and 13C) spectra of losartan together with the corresponding figures and/or tables are all produced. This profile also includes the monograph of British Pharmacopoeia, together with several reported analytical methods including: spectrophotometric, electrochemical, chromatographic, and capillary electrophoretic methods. The stability, the pharmacokinetic behavior and the pharmacology of the drug are also provided.

  3. Profiling Expelled Students

    Directory of Open Access Journals (Sweden)

    Warnie Richardson

    2010-05-01

    Full Text Available The purpose of this study was to determine what, if any, demographic trends exist respecting students expelled for violent behavior. The data collected from 104 confidential student files were used to profile each of the following: A. The violent student, B. The nature of school violence, and C. How schools are dealing with violent students. The student expelled for violent behavior is typically male, between the ages of 15 and 18, has a history of previous suspension and has average to below-average academic skills. The incidents of violence occur in common areas of the school, are rarely directed toward staff and teachers, involve a weapon, and are classified as aggravated assaults. Schools are directly involving the police, expelling students for extended periods of time

  4. Structures and Functions Prediction and Expression Profiles of Calreticulin as Calcium Binding Chaperones in Chicken%鸡钙离子结合分子伴侣Calreticulin的结构与功能预测及组织表达特性

    Institute of Scientific and Technical Information of China (English)

    王丽丽; 李楠; 曹嫦妤; 龚都强; 于东; 王伟; 李金龙

    2014-01-01

    内的终端非还原性α-L-阿拉伯呋喃糖苷残基的水解,作用于α-L-阿拉伯呋喃糖苷、含(1,3)和/或(1,5)糖苷键的阿拉伯聚糖、阿拉伯木聚糖和阿拉伯半乳聚糖,能与糖类分子及Ca2+特异性结合,可监控糖蛋白组装折叠及Ca2+调控,且在消化系统中发挥重要作用。%[Objective] The aim of the current study is to reveal the evolutionary relationships, and investigate the protein structure and functions and the expression profiles of calreticulin (CRT) as a key Ca2+ binding molecular chaperone within the endoplasmic reticulum (ER) of chicken.[Method]The nucleotides and amino acids of CRT in 12 species of vertebrates recorded in Gene bank were analyzed for evolutionary relationships by Laser Gene, and the structures and functions of CRT protein in chicken were predicted by bioinformatics, and the expression profiles of CRT in 30 organizations of chicken was analyzed by real-time PCR.[Result]Results of homology analysis showed that compared with the other 11 species of nucleotide sequences of CRT gene in chicken, gallus gallus and oryctolagus cuniculus had the highest nucleotide sequence homology, which was 78.7%, in addition, gallus gallus and oncorhynchus mykiss had the lowest homology, which was 70.5%. In the homology of amino acid sequences, the relationship between gallus gallus and crotalus adamanteus cadam is the closest by 85.0%, and the furthest relationships with gallus gallus is oncorhynchus mykiss which was 69.0% in amino acid sequence, besides, the homology of gallus gallus with cricetulus griseus, macaca mulatta, homo sapiens, oryctolagus cuniculus, sus scrofa, bos taurus, and xenopus (silurana) tropicalisis relatively close to almost above 80.1%. The protein structure and function prediction revealed that the CRT of chicken was constitute with 404 amino acids, and had a relative molecular mass of 46.8802 kD and a theoretical isoelectric point of 4.41, moreover, the negative charge

  5. Distributed User Profiling via Spectral Methods

    CERN Document Server

    Tomozei, Dan-Cristian

    2011-01-01

    User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local information exchanges between users. We compute a profile vector for each user (i.e., a low-dimensional vector that characterises her taste) via spectral transformation of observed user-produced ratings for items. Our two main contributions follow: i) We consider a low-rank probabilistic model of user taste. More specifically, we consider that users and items are partitioned in a constant number of classes, such that users and items within the same class are statistically identical. We prove that without prior knowledge of the compositions of the classes, based solely on few random observed ratings (namely $O(N\\log N)$ such ratings for $N$ users), we can predict user preference with high probability for unrated items by running a local vote among users with similar pr...

  6. Metabolomic profiling in LRRK2-related Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Krisztina K Johansen

    Full Text Available BACKGROUND: Mutations in LRRK2 gene represent the most common known genetic cause of Parkinson's disease (PD. METHODOLOGY/PRINCIPAL FINDINGS: We used metabolomic profiling to identify biomarkers that are associated with idiopathic and LRRK2 PD. We compared plasma metabolomic profiles of patients with PD due to the G2019S LRRK2 mutation, to asymptomatic family members of these patients either with or without G2019S LRRK2 mutations, and to patients with idiopathic PD, as well as non-related control subjects. We found that metabolomic profiles of both idiopathic PD and LRRK2 PD subjects were clearly separated from controls. LRRK2 PD patients had metabolomic profiles distinguishable from those with idiopathic PD, and the profiles could predict whether the PD was secondary to LRRK2 mutations or idiopathic. Metabolomic profiles of LRRK2 PD patients were well separated from their family members, but there was a slight overlap between family members with and without LRRK2 mutations. Both LRRK2 and idiopathic PD patients showed significantly reduced uric acid levels. We also found a significant decrease in levels of hypoxanthine and in the ratios of major metabolites of the purine pathway in plasma of PD patients. CONCLUSIONS/SIGNIFICANCE: These findings show that LRRK2 patients with the G2019S mutation have unique metabolomic profiles that distinguish them from patients with idiopathic PD. Furthermore, asymptomatic LRRK2 carriers can be separated from gene negative family members, which raises the possibility that metabolomic profiles could be useful in predicting which LRRK2 carriers will eventually develop PD. The results also suggest that there are aberrations in the purine pathway in PD which may occur upstream from uric acid.

  7. On the Density profile slope of Clusters of Galaxies

    CERN Document Server

    Del Popolo, A

    2012-01-01

    The present paper extends to clusters of galaxies the study of Del Popolo (2012), concerning how the baryon-dark matter (DM) interplay shapes the density profile of dwarf galaxies. Cluster density profiles are determined taking into account dynamical friction, random and ordered angular momentum and the response of dark matter halos to condensation of baryons. We find that halos containing only DM are characterized by Einasto's profiles, and that the profile flattens with increasing content of baryons, and increasing values of random angular momentum. The analytical results obtained in the first part of the paper were applied to well studied clusters whose inner profiles have slopes flatter than NFW predictions (A611, A383) or are characterized by profiles in agreement with the NFW model (MACS J1423.8+2404, RXJ1133). By using independently-measured baryonic fraction, a typical spin parameter value $\\lambda \\simeq 0.03$, and adjusting the random angular momentum, we re-obtain the mass and density profiles of t...

  8. The Opportunities and Barriers of User Profiling in the Public Sector

    NARCIS (Netherlands)

    Pieterson, Willem; Ebbers, Wolfgang; Dijk, van Jan

    2005-01-01

    Like the private sector, the public sector makes more and more use of user profiling to personalize the electronic services that are being offered to citizens. User profiling offers great opportunities to make communication more effective and efficient, to infer and predict citizens’ behavior and to

  9. [Legal implication of DNA profiling].

    Science.gov (United States)

    Doutremepuich, Christian

    2012-06-01

    In recent years, DNA profiling has been used regularly by the justice system, and has seen a number of improvements, with the need for fewer cells, more efficient DNA extraction and purification, and more rapid genotyping. These methods can now identify an individual more rapidly, from a corpse, blood stain, sperm or epithelial cells, by comparison with familial profiles. In France, DNA profiling can only be ordered by a judge.

  10. Racial Profiling as Collective Definition

    Directory of Open Access Journals (Sweden)

    Trevor G. Gardner

    2014-09-01

    Full Text Available Economists and other interested academics have committed significant time and effort to developing a set of circumstances under which an intelligent and circumspect form of racial profiling can serve as an effective tool in crime finding–the specific objective of finding criminal activity afoot. In turn, anti-profiling advocates tend to focus on the immediate efficacy of the practice, the morality of the practice, and/or the legality of the practice. However, the tenor of this opposition invites racial profiling proponents to develop more surgical profiling techniques to employ in crime finding. In the article, I review the literature on group distinction to discern its relevance to the practice and study of racial profiling. I argue that the costs of racial profiling extend beyond inefficient policing and the humiliation of law-abiding minority pedestrians and drivers. Racial profiling is simultaneously a process of perception and articulation of relative human characteristics (both positive and negative; it binds and reifies the concepts of race and criminality, fixing them into the subconscious of the profiled, the profiler, and society at large.

  11. Sensing the wind profile

    Energy Technology Data Exchange (ETDEWEB)

    Pena, A.

    2009-03-15

    This thesis consists of two parts. The first is a synopsis of the theoretical progress of the study that is based on a number of journal papers. The papers, which constitute the second part of the report, aim to analyze, measure, and model the wind prole in and beyond the surface layer by combining observations from cup anemometers with lidars. The lidar is necessary to extend the measurements on masts at the Horns Rev offshore wind farm and over at land at Hoevsoere, Denmark. Both sensing techniques show a high degree of agreement for wind speed measurements performed at either sites. The wind speed measurements are averaged for several stability conditions and compare well with the surface-layer wind profile. At Hoevsoere, it is sufficient to scale the wind speed with the surface friction velocity, whereas at Horns Rev a new scaling is added, due to the variant roughness length. This new scaling is coupled to wind prole models derived for flow over the sea and tested against the wind proles up to 160 m at Horns Rev. The models, which account for the boundary-layer height in stable conditions, show better agreement with the measurements than compared to the traditional theory. Mixing-length parameterizations for the neutral wind prole compare well with length-scale measurements up to 300 m at Hoevsoere and 950 m at Leipzig. The mixing-length-derived wind proles strongly deviate from the logarithmic wind prole, but agree better with the wind speed measurements. The length-scale measurements are compared to the length scale derived from a spectral analysis performed up to 160 m at Hoevsoere showing high agreement. Mixing-length parameterizations are corrected to account for stability and used to derive wind prole models. These compared better to wind speed measurements up to 300 m at Hoevsoere than the surface-layer wind prole. The boundary-layer height is derived in nearneutral and stable conditions based on turbulent momentum uxes only and in unstable conditions

  12. Halo Scale Predictions of Symmetron Modified Gravity

    CERN Document Server

    Clampitt, Joseph; Khoury, Justin

    2011-01-01

    We offer predictions of symmetron modified gravity in the neighborhood of realistic dark matter halos. The predictions for the fifth force are obtained by solving the nonlinear symmetron equation of motion in the spherical NFW approximation. In addition, we compare the three major known screening mechanisms: Vainshtein, Chameleon, and Symmetron around such dark matter sources, emphasizing the significant differences between them and highlighting observational tests which exploit these differences. Finally, we demonstrate the host halo environmental screening effect ("blanket screening") on smaller satellite halos by solving for the modified forces around a density profile which is the sum of satellite and approximate host components.

  13. Aliskiren: a clinical profile

    Directory of Open Access Journals (Sweden)

    Roland E Schmieder

    2006-06-01

    Full Text Available Aliskiren is a novel oral antihypertensive agent, and the first in the new class of direct renin inhibitors. Here we review the key criteria that a new antihypertensive drug should possess, notably effective blood pressure lowering as monotherapy and combination therapy, 24-hour blood pressure control, safety and tolerability, end-organ protective effects, minimal drug interaction and efficacy during long-term use.Aliskiren fulfils key criteria for a new antihypertensive agent.The drug demonstrates effective blood lowering in a number of studies as monotherapy and in combination with a thiazide diuretic (hydrochlorothiazide, an angiotensin-converting enzyme inhibitor (ramipril and a calcium channel blocker (amlodipine. Other studies applying ambulatory blood pressure monitoring show that aliskiren maintains blood pressure control for more than 24 hours. Aliskiren, 150 mg and 300 mg have demonstrated a placebo-like safety and tolerability profile, with no interactions with a wide range of commonly used drugs. Three studies (AVOID, ALOFT and ALLAY are ongoing properties. with aliskiren to assess end-organ protective properties.

  14. The worker profile autocontrolled

    Directory of Open Access Journals (Sweden)

    Jairo Omar Delgado Mora

    2015-06-01

    Full Text Available This document is part of two deliveries. In this first paper is to make an approach to the concept of self-control from the very beginning with Sakichi Toyoda, founder of what the industry Toyota Motor Company, additionally taking some excerpts of the concept issued by teachers and the psychologist Henry Murray, a professor at the university Harvard precursor test TAT personality test creator, pen applied world wide by psychologists David McCllelan, also a psychologist and a pioneer in the study of human needs and the concept of competence; Professor Jeffrey Pfeffer of Stanford University organizational behavior and theory, Frederick Hertzberg, Psychologist and strong influential in business management, Kronfly Cruz, lawyer and investigator of social and administrative sciences, Charles Perrow, a sociologist at Yale University and Stanford , who studies the impact of large organizations in society, among others. The study reflects the need to meet organizational objectives related to the physicochemical characteristics of the finished product in a plant of the company’s main beers in the country. In this paper, we intend to make an approximation of worker self -controlled, which when compared with the powers, generic, specific and technical area established by the brewery, will allow generating a methodology to adjust these competencies and to obtain the target profile drawn. This comparison and development of the methodology proposed is the subject of the second work planned.

  15. Doing Business Economy Profile 2016

    OpenAIRE

    World Bank Group

    2015-01-01

    This economy profile for Doing Business 2016 presents the 11 Doing Business indicators for India. To allow for useful comparison, the profile also provides data for other selected economies (comparator economies) for each indicator. Doing Business 2016 is the 13th edition in a series of annual reports measuring the regulations that enhance business activity and those that constrain it. Eco...

  16. Steel Energy and Environmental Profile

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2000-08-01

    Major steelmaking processes (from ironmaking through fabrication and forming) and their associated energy requirements have been profiled in this 2001 report (PDF 582 KB). This profile by Energetics, Inc. also describes the waste streams generated by each process and estimates annual emissions of CO2 and criteria pollutants.

  17. Advanced Multiple Aperture Seeing Profiler

    Science.gov (United States)

    Ren, Deqing; Zhao, Gang

    2016-10-01

    Measurements of the seeing profile of the atmospheric turbulence as a function of altitude are crucial for solar astronomical site characterization, as well as the optimized design and performance estimation of solar Multi-Conjugate Adaptive Optics (MCAO). Knowledge of the seeing distribution, up to 30 km, with a potential new solar observation site, is required for future solar MCAO developments. Current optical seeing profile measurement techniques are limited by the need to use a large facility solar telescope for such seeing profile measurements, which is a serious limitation on characterizing a site's seeing conditions in terms of the seeing profile. Based on our previous work, we propose a compact solar seeing profiler called the Advanced Multiple Aperture Seeing Profile (A-MASP). A-MASP consists of two small telescopes, each with a 100 mm aperture. The two small telescopes can be installed on a commercial computerized tripod to track solar granule structures for seeing profile measurement. A-MASP is extreme simple and portable, which makes it an ideal system to bring to a potential new site for seeing profile measurements.

  18. Linguistic Profiling of Language Disorders

    Science.gov (United States)

    Karanth, Prathibha

    2010-01-01

    The history of the evolution of language assessments for children and adults with language disorders is described briefly. This is followed by a discussion on language assessment of the clinical population with an emphasis on linguistic profiling, illustrated through the Linguistic Profile Test. Discourse analysis, in particular, is highlighted…

  19. Steroid profiling in doping analysis

    NARCIS (Netherlands)

    Kerkhof, Daniël Henri van de

    2002-01-01

    Profiling androgens in urine samples is used in doping analysis for the detection of abused steroids of endogenous origin. These profiling techniques were originally developed for the analysis of testosterone, mostly by means of the ratio of testosterone to epitestosterone (T/E ratio). A study was p

  20. The relationship between fetal biophysical profile and cord blood PH

    Directory of Open Access Journals (Sweden)

    Valadan M

    2009-02-01

    Full Text Available "nBackground: The Biophysical Profile (BPP is a noninvasive test that predicts the presence or absence of fetal asphyxia and, ultimately, the risk of fetal death in the antenatal period. Intervention on the basis of an abnormal biophysical profile result has been reported to yield a significant reduction in prenatal mortality, and an association exists between biophysical profile scoring and a decreased cerebral palsy rate in a given population. The BPP evaluates five characteristics: fetal movement, tone, breathing, heart reactivity, and amniotic fluid (AF volume estimation. The purpose of study was to determine whether there are different degree of acidosis at which the biophysical activity (acute marker are affected. "nMethods: In a prospective study of 140 patients undergoing cesarean section before onset of labor, the fetal biophysical profile was performed 24h before the time of cesarean and was matched with cord arterial PH that was obtained from a cord segment (10-20cm that was double clamped after delivery of newborn. (using cord arterial PH less than 7.20 for the diagnosis of acidosis. "nResults: The fetal biophysical profile was found to have a significant relationship with umbilical blood PH. The sensitivity, specificity, positive predictive value, negative predictive value of fetal biophysical profile score were: 88.9%, 88.6%, 50%, 98.1%. "nConclusion: The first manifestations of fetal acidosis are nonreactive nonstress testing and fetal breathing loss; in advanced acidemia fetal movements and fetal tone are compromised. A protocol of antepartum fetal evaluation is suggested based upon the individual biophysical components rather than the score alone.

  1. In Silico Approaches for Predicting Adme Properties

    Science.gov (United States)

    Madden, Judith C.

    A drug requires a suitable pharmacokinetic profile to be efficacious in vivo in humans. The relevant pharmacokinetic properties include the absorption, distribution, metabolism, and excretion (ADME) profile of the drug. This chapter provides an overview of the definition and meaning of key ADME properties, recent models developed to predict these properties, and a guide as to how to select the most appropriate model(s) for a given query. Many tools using the state-of-the-art in silico methodology are now available to users, and it is anticipated that the continual evolution of these tools will provide greater ability to predict ADME properties in the future. However, caution must be exercised in applying these tools as data are generally available only for "successful" drugs, i.e., those that reach the marketplace, and little supplementary information, such as that for drugs that have a poor pharmacokinetic profile, is available. The possibilities of using these methods and possible integration into toxicity prediction are explored.

  2. Searching mixed DNA profiles directly against profile databases.

    Science.gov (United States)

    Bright, Jo-Anne; Taylor, Duncan; Curran, James; Buckleton, John

    2014-03-01

    DNA databases have revolutionised forensic science. They are a powerful investigative tool as they have the potential to identify persons of interest in criminal investigations. Routinely, a DNA profile generated from a crime sample could only be searched for in a database of individuals if the stain was from single contributor (single source) or if a contributor could unambiguously be determined from a mixed DNA profile. This meant that a significant number of samples were unsuitable for database searching. The advent of continuous methods for the interpretation of DNA profiles offers an advanced way to draw inferential power from the considerable investment made in DNA databases. Using these methods, each profile on the database may be considered a possible contributor to a mixture and a likelihood ratio (LR) can be formed. Those profiles which produce a sufficiently large LR can serve as an investigative lead. In this paper empirical studies are described to determine what constitutes a large LR. We investigate the effect on a database search of complex mixed DNA profiles with contributors in equal proportions with dropout as a consideration, and also the effect of an incorrect assignment of the number of contributors to a profile. In addition, we give, as a demonstration of the method, the results using two crime samples that were previously unsuitable for database comparison. We show that effective management of the selection of samples for searching and the interpretation of the output can be highly informative.

  3. IPACT: Improved Web Page Recommendation System Using Profile Aggregation Based On Clustering of Transactions

    Directory of Open Access Journals (Sweden)

    Yahya AlMurtadha

    2011-01-01

    Full Text Available Problem statement: Recently, Web usage mining techniques have been widely used to build recommendation systems especially for anonymous users. Approach: Assigning the current user to the best web navigation profile with similar navigation activities will improve the ability of the prediction engine to produce a recommendation list then introduce it to the user. This study presents iPACT an improved recommendation system using Profile Aggregation based on Clustering of Transactions (PACT. Results: iPACT shows better prediction accuracy than the previous methods PACT and Hypergraph. Conclusion: The users interests change over time; hence an incremental and adaptive web navigation profiling is a key feature for the future works.

  4. Scaling Evolution of Universal Dark-Matter Halo Density Profiles

    CERN Document Server

    Raig, A; Salvador-Solé, E

    1998-01-01

    Dark-matter halos show a universal density profile with a scaling such that less massive systems are typically denser. This mass-density relation is well described by a proportionality between the characteristic density of halos and the mean cosmic density at halo formation time. It has recently been shown that this proportionality could be the result of the following simple evolutionary picture. Halos form in major mergers with essentially the same, cosmogony-dependent, dimensionless profile, and then grow inside-outside, as a consequence of accretion. Here we verify the consistency of this picture and show that it predicts the correct zero point of the mass-density relation.

  5. Agricultural Pilot's Audiological Profile

    Directory of Open Access Journals (Sweden)

    Foltz, Lucas

    2010-09-01

    Full Text Available Introduction: The agricultural airplane pilot are daily exposed to intense noises, being susceptible to the noise-induced hearing loss (NIHL and its auditory and extra auditory effects. Objective: To analyze the audiological profile of this population, verifying the work's influence on its hearing. Method: It was realized a retrospective, individual, observational, and cross-sectional study through the data obtained by means of a questionnaire and audiometric thresholds of 41 agricultural pilots. To the statistical analysis were utilized the chi-square, Spearman, and Wilcoxon tests with significance level of 5%. Results: It was verified that 95,1% of the pilots use PPE ( personal protective equipment during flight and 58,5% have contact with pesticides. More than half of individuals referred to feel auditory and extra auditory symptoms, being the buzz the more frequent (29,1%. It has the occurrence of 29,3% of NIHL suggestive hearing loss and 68,3% of normality, taking this presence of unilateral notch in 24,4% and bilateral notch in 31,7%. It was found correlation statistically significant in the associations between time of service and the average of the acute frequencies in the right ear (p=0038, and in the left ear (p=0,010. It has a statistical tendency in the association between audiometric configuration and contact with pesticides (p=0,088. Conclusion: The hearing loss prevalence in this study was showed high. More than half of the sample has normal audiometric thresholds with notch configuration. Such data lead to the conclusion that the agricultural pilots, even with PPE use, they still suffer with the damages caused by noise, needing best proposals of hearing loss prevention.

  6. Neonatal Neurobehavior Predicts Medical and Behavioral Outcome

    Science.gov (United States)

    Liu, J.; Bann, C.; Lester, B.; Tronick, E.; Abhik, D.; Lagasse, L.; Bauer, C.; Shankaran, S.; Bada, H.

    2010-01-01

    Objective This study examined the NICU Network Neurobehavioral Scale (NNNS) as a predictor of negative medical and behavioral findings one month to 4½ years of age. Methods . The sample included 1248 mother-infant dyads (42% born <37 weeks’ gestational age) participating in a longitudinal study of the effects of prenatal substance exposure on child development. Mothers were recruited at 4 urban university-based centers and were mostly African-American and on public assistance. At 1 month of age, infants were tested with the NICU Network Neurobehavioral Scale (NNNS). Latent Profile Analysis (LPA) was carried out on NNNS summary scales to identify discrete behavioral profiles. The validity of the NNNS was examined using logistic regression to predict prenatal drug exposure, medical and developmental outcomes through 4½ years of age including adjustment for gestational age and socioeconomic status (SES). Results . Five discrete behavioral profiles were reliably identified with the most extreme negative profile found in 5.8% of the infants. The profiles showed statistically significant associations with prenatal drug exposure, gestational age and birthweight, head ultrasound, neurological and brain disease findings and abnormal scores on measures of behavior problems, school readiness and IQ through 4½ years of age. Conclusions The NNNS may be useful to identify infant behavioral needs to be targeted in well-baby pediatric care, as well as for referrals to community based early intervention services. PMID:19969621

  7. Evaluation of vertical profiles to design continuous descent approach procedure

    Science.gov (United States)

    Pradeep, Priyank

    The current research focuses on predictability, variability and operational feasibility aspect of Continuous Descent Approach (CDA), which is among the key concepts of the Next Generation Air Transportation System (NextGen). The idle-thrust CDA is a fuel economical, noise and emission abatement procedure, but requires increased separation to accommodate for variability and uncertainties in vertical and speed profiles of arriving aircraft. Although a considerable amount of researches have been devoted to the estimation of potential benefits of the CDA, only few have attempted to explain the predictability, variability and operational feasibility aspect of CDA. The analytical equations derived using flight dynamics and Base of Aircraft and Data (BADA) Total Energy Model (TEM) in this research gives insight into dependency of vertical profile of CDA on various factors like wind speed and gradient, weight, aircraft type and configuration, thrust settings, atmospheric factors (deviation from ISA (DISA), pressure and density of the air) and descent speed profile. Application of the derived equations to idle-thrust CDA gives an insight into sensitivity of its vertical profile to multiple factors. This suggests fixed geometric flight path angle (FPA) CDA has higher degree of predictability and lesser variability at the cost of non-idle and low thrust engine settings. However, with optimized design this impact can be overall minimized. The CDA simulations were performed using Future ATM Concept Evaluation Tool (FACET) based on radar-track and aircraft type data (BADA) of the real air-traffic to some of the busiest airports in the USA (ATL, SFO and New York Metroplex (JFK, EWR and LGA)). The statistical analysis of the vertical profiles of CDA shows 1) mean geometric FPAs derived from various simulated vertical profiles are consistently shallower than 3° glideslope angle and 2) high level of variability in vertical profiles of idle-thrust CDA even in absence of

  8. Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity.

    Science.gov (United States)

    Ng, Kenney; Sun, Jimeng; Hu, Jianying; Wang, Fei

    2015-01-01

    Personalized predictive models are customized for an individual patient and trained using information from similar patients. Compared to global models trained on all patients, they have the potential to produce more accurate risk scores and capture more relevant risk factors for individual patients. This paper presents an approach for building personalized predictive models and generating personalized risk factor profiles. A locally supervised metric learning (LSML) similarity measure is trained for diabetes onset and used to find clinically similar patients. Personalized risk profiles are created by analyzing the parameters of the trained personalized logistic regression models. A 15,000 patient data set, derived from electronic health records, is used to evaluate the approach. The predictive results show that the personalized models can outperform the global model. Cluster analysis of the risk profiles show groups of patients with similar risk factors, differences in the top risk factors for different groups of patients and differences between the individual and global risk factors.

  9. Gravitational lensing properties of an isothermal universal halo profile

    Institute of Scientific and Technical Information of China (English)

    Xin-Zhong Er

    2013-01-01

    N-body simulations predict that dark matter halos with different mass scales are described by a universal model,the Navarro-Frenk-White (NFW) density profiles.As a consequence of baryonic cooling effects,these halos will become more concentrated,and similar to an isothermal sphere over a large range in radii (~ 300 h-1 kpc).The singular isothermal sphere (SIS) model however has to be truncated artificially at large radii since it extends to infinity.We model a massive galaxy halo as a combination of an isothermal sphere and an NFW density profile.We give an approximation for the mass concentration at different baryon fractions and present exact expressions for the weak lensing shear and flexion for such a halo.We compare the lensing properties with the SIS and NFW profiles.We find that the combined profile can generate higher order lensing signals at small radii and is more efficient in generating strong lensing events.In order to distinguish such a halo profile from the SIS or NFW profiles,one needs to combine strong and weak lensing constraints for small and large radii.

  10. Modeling and Experimental Tests of a Mechatronic Device to Measure Road Profiles Considering Impact Dynamics

    DEFF Research Database (Denmark)

    Souza, A.; Santos, Ilmar

    2002-01-01

    predicts well the mechanism movements. However it was also experimentally observed that the contact between the wheels and the road profile is not permanent. To analyze the non-contact between the wheels and the road, the Newton-Euler´s Method is used to calculate forces and moments of reactions between...... profile by means of gravitational and spring forces. Accelerometers are attached above the rolling wheels and the wheels follow the profiles of a rough ground. After integrating the acceleration signal twice and measuring the vehicle displacement the road profiles can be achieved. It is important...

  11. Are Psychotherapeutic Changes Predictable? Comparison of a Chicago Counseling Center Project with a Penn Psychotherapy Project.

    Science.gov (United States)

    Luborsky, Lester; And Others

    1979-01-01

    Compared studies predicting outcomes of psychotherapy. Level of prediction success in both projects was modest. Particularly for the rated benefits score, the profile of variables showed similar levels of success between the projects. Successful predictions were based on adequacy of personality functioning, match on marital status, and length of…

  12. On the density profile of dark matter substructure in gravitational lens galaxies

    CERN Document Server

    Vegetti, Simona

    2014-01-01

    We consider three extensions of the Navarro, Frenk and White (NFW) profile and investigate the intrinsic degeneracies among the density profile parameters on the gravitational lensing effect of satellite galaxies on highly magnified Einstein rings. In particular, we find that the gravitational imaging technique can be used to exclude specific regions of the considered parameter space, and therefore, models that predict a large number of satellites in those regions. By comparing the lensing degeneracy with the intrinsic density profile degeneracies, we show that theoretical predictions based on fits that are dominated by the density profile at larger radii may significantly over- or underestimate the number of satellites that are detectable with gravitational lensing. Finally, using the previously reported detection of a satellite in the gravitational lens system JVAS B1938+666 as an example, we derive for this detected satellite values of r_max and v_max that are, for each considered profile, consistent withi...

  13. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D;

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribut...

  14. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D;

    2015-01-01

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribut...

  15. Statistical learning for predictive targeting in online advertising

    DEFF Research Database (Denmark)

    Fruergaard, Bjarne Ørum

    . We also present variations of Bayesian generative models for stochastic blockmodeling for inference of structure based on browsing patterns. Applying this structural information to improve click-through rate prediction becomes a two-step procedure; 1) learn user and URL profiles from browsing...... patterns, 2) use the profiles as additional features in a click-through rate prediction model. The assumption we implicitly make is reasonable: Users and URLs that are grouped together based on browsing patterns will have similar responses to ads, e.g., can be used as predictors of clicks. We report...

  16. Profile Viewer (ProVu)

    Data.gov (United States)

    Department of Transportation — ProVu is a viewer which allows Federal, State, and private industry users to electronically analyze standard motor carrier safety profile reports available from the...

  17. CDBG Performance Profiles - PY12

    Data.gov (United States)

    Department of Housing and Urban Development — These profiles significantly increase the amount of information that is available about the performance of CDBG grantees. It is important that our grantees, all our...

  18. Distinguishing ichthyoses by protein profiling.

    Directory of Open Access Journals (Sweden)

    Robert H Rice

    Full Text Available To explore the usefulness of protein profiling for characterization of ichthyoses, we here determined the profile of human epidermal stratum corneum by shotgun proteomics. Samples were analyzed after collection on tape circles from six anatomic sites (forearm, palm, lower leg, forehead, abdomen, upper back, demonstrating site-specific differences in profiles. Additional samples were collected from the forearms of subjects with ichthyosis vulgaris (filaggrin (FLG deficiency, recessive X-linked ichthyosis (steroid sulfatase (STS deficiency and autosomal recessive congenital ichthyosis type lamellar ichthyosis (transglutaminase 1 (TGM1 deficiency. The ichthyosis protein expression patterns were readily distinguishable from each other and from phenotypically normal epidermis. In general, the degree of departure from normal was lower from ichthyosis vulgaris than from lamellar ichthyosis, parallel to the severity of the phenotype. Analysis of samples from families with ichthyosis vulgaris and concomitant modifying gene mutations (STS deficiency, GJB2 deficiency permitted correlation of alterations in protein profile with more complex genetic constellations.

  19. Distinguishing ichthyoses by protein profiling.

    Science.gov (United States)

    Rice, Robert H; Bradshaw, Katie M; Durbin-Johnson, Blythe P; Rocke, David M; Eigenheer, Richard A; Phinney, Brett S; Schmuth, Matthias; Gruber, Robert

    2013-01-01

    To explore the usefulness of protein profiling for characterization of ichthyoses, we here determined the profile of human epidermal stratum corneum by shotgun proteomics. Samples were analyzed after collection on tape circles from six anatomic sites (forearm, palm, lower leg, forehead, abdomen, upper back), demonstrating site-specific differences in profiles. Additional samples were collected from the forearms of subjects with ichthyosis vulgaris (filaggrin (FLG) deficiency), recessive X-linked ichthyosis (steroid sulfatase (STS) deficiency) and autosomal recessive congenital ichthyosis type lamellar ichthyosis (transglutaminase 1 (TGM1) deficiency). The ichthyosis protein expression patterns were readily distinguishable from each other and from phenotypically normal epidermis. In general, the degree of departure from normal was lower from ichthyosis vulgaris than from lamellar ichthyosis, parallel to the severity of the phenotype. Analysis of samples from families with ichthyosis vulgaris and concomitant modifying gene mutations (STS deficiency, GJB2 deficiency) permitted correlation of alterations in protein profile with more complex genetic constellations.

  20. Feeding profiles of tame moose

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This report is on the feeding profiles of tame moose. 3 moose were observed for 99 hours while in natural range, each bite plant species, browse conditions and size...

  1. State Cancer Profiles Web site

    Data.gov (United States)

    U.S. Department of Health & Human Services — The State Cancer Profiles (SCP) web site provides statistics to help guide and prioritize cancer control activities at the state and local levels. SCP is a...

  2. Monitor of SC beam profiles

    CERN Multimedia

    1977-01-01

    A high-resolution secondary emission grid for the measurement of SC beam profiles. Modern techniques of metal-ceramic bonding, developed for micro-electronics, have been used in its construction. (See Annual Report 1977 p. 105 Fig. 12.)

  3. Gene expression profiles in irradiated cancer cells

    Science.gov (United States)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C.

    2013-07-01

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.

  4. Gene expression profiles in irradiated cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C. [IBFM CNR - LATO, Cefalù, Segrate (Italy)

    2013-07-26

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.

  5. Metropolitan Lima: area profile.

    Science.gov (United States)

    Hakkert, R

    1986-11-01

    This profile of metropolitan Lima, Peru, covers administrative divisions; population growth; age distribution; ethnicity and religion; housing and households; education and health care; economic activity, income, and consumption; transport and communication; and sources of information. Nearly 30% of Peru's entire population and 42% of its urban population live in Lima. The trend continues, yet Lima's urban primacy is waning due to the growth of some regional centers like Trujillo and Chimbote. Lima is still almost 10 times as large as the country's next ranking cities, Trujillo on the northern coast and Arequipa in the south. Peru's main administrative divisions are the 24 departments, of which the Department of Lima is one. These departments are further divided into 156 provinces. Greater Lima consists of 2 such provinces, the province of Lima and the constitutional province of Callao. Although the population of Lima continues to grow, its rate of growth slowed from about 5.5% during the 1960s to about 3.9% in the 1970s. Current projections estimate a metropolitan population of 6.7 million by 1990. On the whole, Lima's age structure is somewhat older than that of the rest of Peru. The median age of the population is 22.3 years, compared to a national figure of 20.4. The proportion of persons over age 65 is only 3.6%, lower than the national average of 4.1%, due to the tendency of in-migration to concentrate people of intermediate ages in the cities. Almost 400,000 inhabitants of greater Lima are bilingual in Spanish and an indigenous language. As elsewhere in Peru, the dominant religion is Roman Catholicism. Lima is a spread out city with few high rise buildings due to the danger of earthquakes. Only 12% of Lima's households are found in apartment buildings. As in other cities of Latin America, the formal housing market is beyond the reach of a major segment of the population. Consequently, much of the urban settlement has occurred through informal self

  6. Applied predictive control

    CERN Document Server

    Sunan, Huang; Heng, Lee Tong

    2002-01-01

    The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

  7. USING SENTIMENT ANALYSIS FOR STOCK EXCHANGE PREDICTION

    Directory of Open Access Journals (Sweden)

    Milson L. Lima

    2016-01-01

    Full Text Available The economic growth is a consensus in any country. To grow economically, it is necessary to channel the revenues for investment. One way of raising is the capital market and the stock exchanges. In this context, predicting the behavior of shares in the stock exchange is not a simple task, as itinvolves variables not always known and can undergo various influences, from the collective emotion to high-profile news. Such volatility can represent considerable financial losses for investors. In order to anticipate such changes in the market, it has been proposed various mechanisms trying to predict the behavior of an asset in the stock market, based on previously existing information. Such mechanisms include statistical data only, without considering the collective feeling. This paper is going to use natural language processing algorithms (LPN to determine the collective mood on assets and later with the help of the SVM algorithm to extract patterns in an attempt to predict the active behaviour.

  8. Racial Profiling and Criminal Justice

    DEFF Research Database (Denmark)

    Ryberg, Jesper

    2011-01-01

    According to the main argument in favour of the practice of racial profiling as a low enforcement tactic, the use of race as a targeting factor helps the police to apprehend more criminals. In the following, this argument is challenged. It is argued that, given the assumption that criminals...... are currently being punished too severely in Western countries, the apprehension of more criminals may not constitute a reason in favour of racial profiling at all....

  9. The influence of humidity fluxes on offshore wind speed profiles

    Directory of Open Access Journals (Sweden)

    R. J. Barthelmie

    2010-05-01

    Full Text Available Wind energy developments offshore focus on larger turbines to keep the relative cost of the foundation per MW of installed capacity low. Hence typical wind turbine hub-heights are extending to 100 m and potentially beyond. However, measurements to these heights are not usually available, requiring extrapolation from lower measurements. With humid conditions and low mechanical turbulence offshore, deviations from the traditional logarithmic wind speed profile become significant and stability corrections are required. This research focuses on quantifying the effect of humidity fluxes on stability corrected wind speed profiles. The effect on wind speed profiles is found to be important in stable conditions where including humidity fluxes forces conditions towards neutral. Our results show that excluding humidity fluxes leads to average predicted wind speeds at 150 m from 10 m which are up to 4% higher than if humidity fluxes are included, and the results are not very sensitive to the method selected to estimate humidity fluxes.

  10. Parametric Jominy profiles predictor based on neural networks

    Directory of Open Access Journals (Sweden)

    Valentini, R.

    2005-12-01

    Full Text Available The paper presents a method for the prediction of the Jominy hardness profiles of steels for microalloyed Boron steel which is based on neural networks. The Jominy profile has been parameterized and the parameters, which are a sort of "compact representation" of the profile itself, are linked to the steel chemical composition through a neural network. Numerical results are presented and discussed.

    El trabajo presenta un método de estimación de perfiles de dureza Jominy para aceros microaleados al boro basado en redes neuronales. Los parámetros de perfil Jominy, que constituyen una especie de "representación compacta" del perfil mismo, son determinados y puestos en relación con la composición química del acero mediante una red neuronal. Los resultados numéricos son expuestos y discutidos.

  11. The influence of humidity fluxes on offshore wind speed profiles

    DEFF Research Database (Denmark)

    Barthelmie, Rebecca Jane; Sempreviva, Anna Maria; Pryor, Sara

    2010-01-01

    Wind energy developments offshore focus on larger turbines to keep the relative cost of the foundation per MW of installed capacity low. Hence typical wind turbine hub-heights are extending to 100 m and potentially beyond. However, measurements to these heights are not usually available, requiring...... extrapolation from lower measurements. With humid conditions and low mechanical turbulence offshore, deviations from the traditional logarithmic wind speed profile become significant and stability corrections are required. This research focuses on quantifying the effect of humidity fluxes on stability corrected...... wind speed profiles. The effect on wind speed profiles is found to be important in stable conditions where including humidity fluxes forces conditions towards neutral. Our results show that excluding humidity fluxes leads to average predicted wind speeds at 150 m from 10 m which are up to 4% higher...

  12. Galactic cannibalism and CDM density profiles

    CERN Document Server

    Nipoti, C; Ciotti, L; Stiavelli, M

    2004-01-01

    Using N-body simulations we show that the process of formation of the brightest cluster galaxy through dissipationless galactic cannibalism can affect the inner cluster dark matter density profile. In particular, we use as realistic test case the dynamical evolution of the galaxy cluster C0337-2522 at redshift z=0.59, hosting in its centre a group of five elliptical galaxies which are likely to be the progenitor of a central giant elliptical. After the formation of the brightest cluster galaxy, the inner cluster dark matter density profile is significantly flatter (logarithmic slope 0.48predicted by cosmological simulations.

  13. HPLC profiling of Phellinus linteus.

    Science.gov (United States)

    Kojima, Kazuo; Ogihara, Yukio; Sakai, Yoshimichi; Mizukami, Hajime; Nagatsu, Akito

    2008-10-01

    HPLC chromatograms of MeOH extracts from a fruit body of the wild-grown P. linteus (natural fruit body), from cultivated fungus (cultivated fruit body), and from the cultured mycelia were compared. The extract prepared from the natural fruit bodies revealed a typical HPLC profile referred to as type 1 with a major peak corresponding to meshimakobnol A (1) together with two minor peaks of hypholomine B (3) and inoscavin A (4); the cultivated fruit bodies exhibited a profile referred to as type 2 with major peaks corresponding to 3 and 4 and a minor peak of 1, and the cultured mycelia showed a profile referred to as type 3 without any of these peaks. We also analyzed HPLC chromatograms of commercial products of P. linteus obtained in the markets. Most of the products claimed to be natural fruit bodies exhibited type 1 profiles, except for one product having an intermediate HPLC profile between type 1 and type 2. The products claimed to be cultivated fruit bodies and cultured mycelia revealed type 2 and type 3 profiles, respectively. The present results indicate that the HPLC chromatogram of the methanol extract of P. linteus can be used as a fingerprint to identify whether the product is from natural fruit bodies, cultivated fruit bodies, or cultured mycelia.

  14. Towards Social Profile Based Overlays

    CERN Document Server

    Wolinsky, David Isaac; Boykin, P Oscar; Figueiredo, Renato

    2010-01-01

    Online social networking has quickly become one of the most common activities of Internet users. As social networks evolve, they encourage users to share more information, requiring the users, in turn, to place more trust into social networks. Peer-to-peer (P2P) overlays provide an environment that can return ownership of information, trust, and control to the users, away from centralized third-party social networks. In this paper, we present a novel concept, social profile overlays, which enable users to share their profile only with trusted peers in a scalable, reliable, and private manner. Each user's profile consists of a unique private, secure overlay, where members of that overlay have a friendship with the overlay owner. Profile data is made available without regard to the online state of the profile owner through the use of the profile overlay's distributed data store. Privacy and security are enforced through the use of a public key infrastructure (PKI), where the role of certificate authority (CA) i...

  15. Profiling critical cancer gene mutations in clinical tumor samples.

    Directory of Open Access Journals (Sweden)

    Laura E MacConaill

    Full Text Available BACKGROUND: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. METHODOLOGY: We developed and implemented an optimized mutation profiling platform ("OncoMap" to interrogate approximately 400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. CONCLUSIONS: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of "actionable" cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents.

  16. Pulsar polarisation below 200 MHz: Average profiles and propagation effects

    CERN Document Server

    Noutsos, A; Kondratiev, V I; Weltevrede, P; Verbiest, J P W; Karastergiou, A; Kramer, M; Kuniyoshi, M; Alexov, A; Breton, R P; Bilous, A V; Cooper, S; Falcke, H; Grießmeier, J -M; Hassall, T E; Hessels, J W T; Keane, E F; Osłowski, S; Pilia, M; Serylak, M; Stappers, B W; ter Veen, S; van Leeuwen, J; Zagkouris, K; Anderson, K; Bähren, L; Bell, M; Broderick, J; Carbone, D; Cendes, Y; Coenen, T; Corbel, S; Eislöffel, J; Fender, R; Garsden, H; Jonker, P; Law, C; Marko, S; Masters, J; Miller-Jones, J; Molenaar, G; Osten, R; Pietka, M; Rol, E; Rowlinson, A; Scheers, B; Spreeuw, H; Staley, T; Stewart, A; Swinbank, J; Wijers, R; Wijnands, R; Wise, M; Zarka, P; van der Horst, A

    2015-01-01

    We present the highest-quality polarisation profiles to date of 16 non-recycled pulsars and four millisecond pulsars, observed below 200 MHz with the LOFAR high-band antennas. Based on the observed profiles, we perform an initial investigation of expected observational effects resulting from the propagation of polarised emission in the pulsar magnetosphere and the interstellar medium. The predictions of magnetospheric birefringence in pulsars have been tested using spectra of the pulse width and fractional polarisation from multifrequency data. The derived spectra offer only partial support for the expected effects of birefringence on the polarisation properties, with only about half of our sample being consistent with the model's predictions. It is noted that for some pulsars these measurements are contaminated by the effects of interstellar scattering. For a number of pulsars in our sample, we have observed significant variations in the amount of Faraday rotation as a function of pulse phase, which is possi...

  17. Simulations of Line Profile Structure in Shell Galaxies

    CERN Document Server

    Jilkova, L; Krizek, M; Ebrova, I; Stoklasova, I; Bartakova, T; Bartoskova, K

    2009-01-01

    In the context of exploring mass distributions of dark matter haloes in giant ellipticals, we extend the analysis carried out Merrifield and Kuijken (1998) for stellar line profiles of shells created in nearly radial mergers of galaxies. We show that line-of-sight velocity distributions are more complex than previously predicted. We simulate shell formation and analyze the detectability of spectroscopic signatures of shells after convolution with spectral PSFs.

  18. ChemProt: A disease chemical biology database

    DEFF Research Database (Denmark)

    Taboureau, Olivier; Oprea, Tudor I.

    2013-01-01

    The integration of chemistry, biology, and informatics to study drug actions across multiple biological targets, pathways, and biological systems is an emerging paradigm in drug discovery. Rather than reducing a complex system to simplistic models, fields such as chemogenomics and translational...... chemical biology, drug repurposing, and off-target effects prediction....

  19. 基于混合效应模型及EBLUP预测美国黄松林分优势木树高生长过程%Based on Mixed-Effects Model and Empirical Best Linear Unbiased Predictor to Predict Growth Profile of Dominant Height

    Institute of Scientific and Technical Information of China (English)

    祖笑锋; 倪成才; Gorden Nigh; 覃先林

    2015-01-01

    【目的】基于加拿大哥伦比亚省美国黄松79株解析木数据,研究如何用经验线性无偏最优预测法( EBLUP)预测优势木树高生长过程,并分析预测精度与观测次数、观测间隔和预测时长的关系。【方法】随机抽取49株解析木数据拟合树高生长混合效应模型,30株解析木数据用于 EBLUP 的预测分析。树高生长模型以Richards,Logistic,Korf等为基础模型,选用AIC,BIC及Loglik 3个统计量评价模型的拟合效果。模型拟合用R软件的 nlme函数实现,预测分析以预测误差均方( MSPE)为评价标准。在分析观测间隔、观测次数和预测时长对 MSPE的影响时,为分离出1个因素的影响效果,将2个因素保持不变,以分析第3个因素的影响作用。在 R 软件拟合结果的基础上,用SAS的IML过程进行EBLUP预测分析。【结果】拟合结果表明,Logistic方程的拟合精度最高,选为EBLUP预测分析的基本模型。预测分析结果表明,观测次数、观测间隔和预测时长对预测精度均有显著影响。随着观测次数的增加,MSPE一般表现出减少的趋势,但下降幅度与观测间隔有关:当间隔较大时,不同的观测值可以提供更充分的生长过程信息,因而可以显著降低 MSPE 值;但当间隔较小时,观测值所提供的生长信息相互重叠,对提高预测精度的增益有限。从预测时长角度看,在观测值附近一定区域内,EBLUP预测结果非常精确,但随着预测时长增加,预测误差呈逐渐增加的趋势。【结论】EBLUP 预测相当于两阶段拟合过程的第二阶段。第一阶段拟合为估计混合参数模型确定参数的过程,而第二阶段则是在第一阶段拟合结果的基础上,依据一个特定林分的若干树高观测值用 EBLUP法预测此林分的随机效应值,并进一步预测树高生长过程。%Objective] This study analyzed prediction accuracy of

  20. Protein secondary structure prediction using deep convolutional neural fields

    OpenAIRE

    Sheng Wang; Jian Peng; Jianzhu Ma; Jinbo Xu

    2015-01-01

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF)...

  1. Predictive systems ecology.

    Science.gov (United States)

    Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

    2013-11-22

    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

  2. Predictability of conversation partners

    CERN Document Server

    Takaguchi, Taro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-01-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information theoretic method to the spatiotemporal data of cell-phone locations, Song et al. (2010) found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between close sensor nodes. We find t...

  3. Distribution Free Prediction Bands

    CERN Document Server

    Lei, Jing

    2012-01-01

    We study distribution free, nonparametric prediction bands with a special focus on their finite sample behavior. First we investigate and develop different notions of finite sample coverage guarantees. Then we give a new prediction band estimator by combining the idea of "conformal prediction" (Vovk et al. 2009) with nonparametric conditional density estimation. The proposed estimator, called COPS (Conformal Optimized Prediction Set), always has finite sample guarantee in a stronger sense than the original conformal prediction estimator. Under regularity conditions the estimator converges to an oracle band at a minimax optimal rate. A fast approximation algorithm and a data driven method for selecting the bandwidth are developed. The method is illustrated first in simulated data. Then, an application shows that the proposed method gives desirable prediction intervals in an automatic way, as compared to the classical linear regression modeling.

  4. Predictability of Conversation Partners

    Science.gov (United States)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  5. Solar Cycle Predictions

    Science.gov (United States)

    Pesnell, William Dean

    2012-01-01

    Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

  6. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    -case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only......Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst...... compare the worst-case execution time bounds of different architectures....

  7. Friedreich ataxia: dysarthria profile and clinical data.

    Science.gov (United States)

    Brendel, Bettina; Ackermann, Hermann; Berg, Daniela; Lindig, Tobias; Schölderle, Theresa; Schöls, Ludger; Synofzik, Matthis; Ziegler, Wolfram

    2013-08-01

    Friedreich ataxia (FRDA) is the most frequent recessive ataxia in the Western world. Dysarthria is a cardinal feature of FRDA, often leading to severe impairments in daily functioning, but its exact characteristics are only poorly understood so far. We performed a comprehensive evaluation of dysarthria severity and the profile of speech motor deficits in 20 patients with a genetic diagnosis of FRDA based on a carefully selected battery of speaking tasks and two widely used paraspeech tasks, i.e., oral diadochokinesis and sustained vowel productions. Perceptual ratings of the speech samples identified respiration, voice quality, voice instability, articulation, and tempo as the most affected speech dimensions. Whereas vocal instability predicted ataxia severity, tempo turned out as a significant correlate of disease duration. Furthermore, articulation predicted the overall intelligibility score as determined by a systematic speech pathology assessment tool. In contrast, neurologists' ratings of intelligibility--a component of the "Scale for the Assessment and Rating of Ataxia"--were found to be related to perceived speech tempo. Obviously, clinicians are more sensitive to slowness of speech than to any other feature of spoken language during dysarthria evaluation. Our results suggest that different components of speech production and trunk/limb motor functions are differentially susceptible to FRDA pathology. Furthermore, evidence emerged that paraspeech tasks do not allow for an adequate scaling of speech deficits in FRDA.

  8. Density profiles of LCDM clusters

    CERN Document Server

    Tasitsiomi, A; Gottlöber, S; Klypin, A A; Tasitsiomi, Argyro; Kravtsov, Andrey V.; Gottloeber, Stefan; Klypin, Anatoly A.

    2004-01-01

    We analyze the mass accretion histories (MAHs) and density profiles of cluster- size halos with virial masses of 0.6-2.5x10^14/h Msun in a flat LCDM cosmology. In agreement with previous studies,we find that the concentration of the density distribution is tightly correlated with the halo's MAH and its formation redshift.During the period of fast mass growth the concentration remains approximately constant and low c_v~3-4,while during the slow accretion stages it increases with decreasing redshift as c_v~(1+z)^-1.We consider fits of three widely discussed analytic density profiles to the simulated clusters focusing on the most relaxed inner regions.We find that there is no unique best fit analytic profile for all the systems.If,however,a cluster is best fit by a particular analytic profile at z=0,the same is usually true at earlier epochs out to z~1-2.The local logarithmic slope of the density profiles at 3% of the virial radius ranges from -1.2 to -2.0,a remarkable diversity for the relatively narrow mass ra...

  9. Betweenness centrality profiles in trees

    CERN Document Server

    Fish, Benjamin; Turan, Gyorgy

    2016-01-01

    Betweenness centrality of a vertex in a graph measures the fraction of shortest paths going through the vertex. This is a basic notion for determining the importance of a vertex in a network. The k-betweenness centrality of a vertex is defined similarly, but only considers shortest paths of length at most k. The sequence of k-betweenness centralities for all possible values of k forms the betweenness centrality profile of a vertex. We study properties of betweenness centrality profiles in trees. We show that for scale-free random trees, for fixed k, the expectation of k-betweenness centrality strictly decreases as the index of the vertex increases. We also analyze worst-case properties of profiles in terms of the distance of profiles from being monotone, and the number of times pairs of profiles can cross. This is related to whether k-betweenness centrality, for small values of k, may be used instead of having to consider all shortest paths. Bounds are given that are optimal in order of magnitude. We also pre...

  10. Structure-templated predictions of novel protein interactions from sequence information.

    Directory of Open Access Journals (Sweden)

    Doron Betel

    2007-09-01

    Full Text Available The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain-motif interactions from structural topology (D-MIST for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.

  11. Structure-templated predictions of novel protein interactions from sequence information.

    Science.gov (United States)

    Betel, Doron; Breitkreuz, Kevin E; Isserlin, Ruth; Dewar-Darch, Danielle; Tyers, Mike; Hogue, Christopher W V

    2007-09-01

    The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain-motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.

  12. Early Brain changes May Help Predict Autism Among High-Risk Infants

    Science.gov (United States)

    ... Media Resources Interviews & Selected Staff Profiles Multimedia Early brain changes may help predict autism among high-risk ... Share this: Page Content NIH-funded researchers link brain changes at 6 and 12 months of age ...

  13. Predicting protein structure classes from function predictions

    DEFF Research Database (Denmark)

    Sommer, I.; Rahnenfuhrer, J.; de Lichtenberg, Ulrik;

    2004-01-01

    We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories; for given...... query sequences these probabilities are obtained by a neural net that has previously been trained on a variety of functionally important features. On a training set of sequences we assess the relevance of individual functional categories for identifying a given structural family. Using a combination...... of the most relevant categories, the likelihood of a query sequence to belong to a specific family can be estimated. Results: The performance of the method is evaluated using cross-validation. For a fixed structural family and for every sequence, a score is calculated that measures the evidence for family...

  14. 'Red Flag' Predictions

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    -generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external...

  15. Improved nonlinear prediction method

    Science.gov (United States)

    Adenan, Nur Hamiza; Md Noorani, Mohd Salmi

    2014-06-01

    The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.

  16. Predicting AD conversion

    DEFF Research Database (Denmark)

    Liu, Yawu; Mattila, Jussi; Ruiz, Miguel �ngel Mu�oz

    2013-01-01

    To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI...

  17. The Prediction Value

    NARCIS (Netherlands)

    Koster, M.; Kurz, S.; Lindner, I.; Napel, S.

    2013-01-01

    We introduce the prediction value (PV) as a measure of players’ informational importance in probabilistic TU games. The latter combine a standard TU game and a probability distribution over the set of coalitions. Player i’s prediction value equals the difference between the conditional expectations

  18. Learning profiles of Master students

    DEFF Research Database (Denmark)

    Sprogøe, Jonas; Hemmingsen, Lis

    2005-01-01

    at DPU in 2001 several evaluations and research have been carried out on several topics relating to form, content, and didactics, but one important focus is missing: the research about the psychological profile and learning style of the master student. Knowledge is lacking on how teaching methods...... and programme designs relate to and support the learning profiles and learning styles of the master students. In other words: What are the consequences of the students' learning styles in terms of planning and teaching in the master programme?...

  19. RATIONAL STEEL CORRUGATED PROFILE DESIGN

    Directory of Open Access Journals (Sweden)

    V. V. Kachurenko

    2015-08-01

    Full Text Available Purpose. The work sets forth the search results of new, more efficient design solutions for metal silos, namely, the analysis of existing types of profiles cross-section in a steel wall of such silo and development of less material-intensive section of corrugated profile.Methodology. To achieve the set goal there were researched the existing types of capacitive structure profiles and their strain-stress state under the load. The analysis was performed on the results of computational experiments. The prototype object was mathematical computer models. The calculations were made using the finite-element method. For computational experiment there was used the design-computing system Structure CAD for Windows. Findings. In this work there were obtained the data allowing to assess work of the profiles and to find more effective type of cross-section in terms of its material consumption. In the process of joint study of the authors a new type of profile for capacitive structures was developed; it has higher utilization efficiency and the attachment point of individual steel sheets with this type of profile. Both solutions are easy to install, reliable in operation and can be manufactured in the conditions of modern industrial production using standard equipment, materials and components. Originality. A new type of corrugated profile cross-section for steel silo walls was proposed; it has higher load carrying capacity and rigidity and allows reducing the metal thickness without changing the structure carrying capacity that results in material consumption reduction of the whole structure.For this and similar types of profiles there was designed and proposed the attachment point of individual corrugated sheets screwed with extending flange, which enables the unit connection in case of small size corrugations, where the distance is not sufficient to accommodate the bolt cap between the individual corrugations. Practical value.Application of the proposed

  20. Minimal dispersion refractive index profiles.

    Science.gov (United States)

    Feit, M D

    1979-09-01

    The analogy between optics and quantum mechanics is exploited by considering a 2-D quantum system whose Schroedinger equation is closely related to the wave equation for light propagation in an optical fiber. From this viewpoint, Marcatili's condition for minimal-dispersion-refractive-index profiles, and the Olshansky- Keck formula for rms pulse spreading in an alpha-profile fiber may be derived without recourse to the WKB approximation. Besides affording physical insight into these results, the present approach points out a possible limitation in their application to real fibers.

  1. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...

  2. Well-log based prediction of thermal conductivity

    DEFF Research Database (Denmark)

    Fuchs, Sven; Förster, Andrea

    Rock thermal conductivity (TC) is paramount for the determination of heat flow and the calculation of temperature profiles. Due to the scarcity of drill cores compared to the availability of petrophysical well logs, methods are desired to indirectly predict TC in sedimentary basins. Most...

  3. Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations

    NARCIS (Netherlands)

    Shah, Sonia; Bonder, Marc J.; Marioni, Riccardo E.; Zhu, Zhihong; McRae, Allan F.; Zhernakova, Alexandra; Harris, Sarah E.; Liewald, Dave; Henders, Anjali K.; Mendelson, Michael M.; Liu, Chunyu; Joehanes, Roby; Liang, Liming; Levy, Daniel; Martin, Nicholas G.; Starr, John M.; Wijmenga, Cisca; Wray, Naomi R.; Yang, Jian; Montgomery, Grant W.; Franke, Lude; Deary, Ian J.; Visscher, Peter M.

    2015-01-01

    We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association stud

  4. Prediction by Compression

    CERN Document Server

    Ratsaby, Joel

    2010-01-01

    It is well known that text compression can be achieved by predicting the next symbol in the stream of text data based on the history seen up to the current symbol. The better the prediction the more skewed the conditional probability distribution of the next symbol and the shorter the codeword that needs to be assigned to represent this next symbol. What about the opposite direction ? suppose we have a black box that can compress text stream. Can it be used to predict the next symbol in the stream ? We introduce a criterion based on the length of the compressed data and use it to predict the next symbol. We examine empirically the prediction error rate and its dependency on some compression parameters.

  5. Structural prediction in aphasia

    Directory of Open Access Journals (Sweden)

    Tessa Warren

    2015-05-01

    Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

  6. Prediction of offshore risks

    Energy Technology Data Exchange (ETDEWEB)

    Castro, J.A.A.

    1979-09-01

    Topographic and geophysical surveys of offshore drilling sites taken prior to platform installation or the commencement of drilling operations can warn operators of the presence of hazardous subsea structures or soil conditions. As illustrated by operations in Campeche Bay, the use of sonar, sidescanners, and shallow and deep profiling systems can produce reliable marine surveys that greatly reduce the risks related to offshore operations.

  7. Parâmetros antropométricos e de composição corporal na predição do percentual de gordura e perfil lipídico em escolares Parámetros antropométricos y de composición corporal en la predicción del porcentaje de grasa y perfil lipídico en escolares Anthropometric and body composition parameters to predict body fat percentage and lipid profile in schoolchildren

    Directory of Open Access Journals (Sweden)

    Lorena Barbosa

    2012-12-01

    percentage and lipid profile in schoolchildren. METHODS: Cross-sectional study with 209 schoolchildren aged between seven and nine years old. The following variables were evaluated: weight, height, body mass index, percentage of body fat, arm and waist circumferences, conicity index, waist-to-height ratio, waist-to-hip ratio, total cholesterol, triglycerides, and high and low density lipoproteins. Statistic treatment included the use of Kolmogorov-Smirnov, Student's t and Mann-Whitney tests, and Spearman and Pearson's correlations. Receiver Operating Characteristic curves were used to identify the predictors of elevated body fat percentage and lipid alterations. RESULTS: Body fat percentage was the variable with the largest number of correlations, especially with weight, body mass index, and arm circumference in both genders, and with waist circumference and waist-to-hip ratio among males. Body mass index, arm and waist circumferences in both genders and waist-to-hip ratio for males showed good discriminatory power for predicting high body fat percentage. Anthropometric and body composition parameters were not able to predict lipid profile alterations, except for body fat percentage, arm and waist circumferences and waist-to-hip ratio, which were good predictors of triglycerides alterations in males. CONCLUSIONS: Dyslipidemia could not be predicted by anthropometric and body composition measurements in children, especially among females, suggesting the need for investigating lipid profile by laboratorial exams.

  8. Teachers' Entrepreneurial Profile: Case Study

    Science.gov (United States)

    Stettiner, Caio Flavio; Formigoni, Alexandre; Filho, Mário Pereira Roque; de Camargo, Mauricio Ortiz; Moia, Roberto Padilha

    2015-01-01

    This article was prepared in order to investigate whether the teachers working in a Business Administration BA degree have an entrepreneurial profile, with the aim of finding whether such teachers are able to support the Pedagogical Proposal of the Institution to which they belong to in what concerns the requirement of the course and also the…

  9. Motivational Profiles of Adult Learners

    Science.gov (United States)

    Rothes, Ana; Lemos, Marina S.; Gonçalves, Teresa

    2017-01-01

    This study investigated profiles of autonomous and controlled motivation and their effects in a sample of 188 adult learners from two Portuguese urban areas. Using a person-centered approach, results of cluster analysis and multivariate analysis of covariance revealed four motivational groups with different effects in self-efficacy, engagement,…

  10. Doing Business Economy Profile 2017

    OpenAIRE

    World Bank Group

    2016-01-01

    This economy profile presents the Doing Business indicators for India. To allow useful comparison, it also provides data for other selected economies (comparator economies) for each indicator. Doing Business 2017 is the 14th in a series of annual reports investigating the regulations that enhance business activity and those that constrain it. Economies are ranked on their ease of doing bus...

  11. Cognitive Profile of Turner Syndrome

    Science.gov (United States)

    Hong, David; Kent, Jamie Scaletta; Kesler, Shelli

    2009-01-01

    Turner syndrome (TS) is a relatively common neurogenetic disorder characterized by complete or partial monosomy-X in a phenotypic female. TS is associated with a cognitive profile that typically includes intact intellectual function and verbal abilities with relative weaknesses in visual-spatial, executive, and social cognitive domains. In this…

  12. English Teaching Profile (Provisional): Venezuela.

    Science.gov (United States)

    British Council, London (England). English Language and Literature Div.

    This profile of the English language teaching situation in Venezuela discusses the status of English in society and in the educational system. It also gives an account of Venezuelan political, economic, and social life. A description is given of the education system and reforms that have been proposed for nursery school through higher education.…

  13. White Light Interferometric Surface Profiler

    OpenAIRE

    Toal, Vincent; Bowe, Brian

    1998-01-01

    We describe an optical system for 3-D profilometry based on the white light interferometer. We detail a simple way to construct a profiler that uses two simple algorithms which deal efficiently and quickly with the data. The system has a theoretically unlimited range and can deal with rough and smooth surfaces

  14. English Language Teaching Profile: Uruguay.

    Science.gov (United States)

    British Council, London (England). English-Teaching Information Centre.

    This profile in outline form of the English language teaching situation in Uruguay discusses the role of English within Uruguayan society and within the educational system. Though English is quite widely used for reading scientific, technical and medical publications, and while it is considered important culturally in higher professions, it is not…

  15. Ascidian gene-expression profiles

    OpenAIRE

    Jeffery, William R.

    2002-01-01

    With the advent of gene-expression profiling, a large number of genes can now be investigated simultaneously during critical stages of development. This approach will be particularly informative in studies of ascidians, basal chordates whose genomes and embryology are uniquely suited for mapping developmental gene networks.

  16. Autonomous vertical profiler data management

    Digital Repository Service at National Institute of Oceanography (India)

    Afzulpurkar, S.; Navelkar, G.S.; Desa, E.S.; Madhan, R.; Dabholkar, N; Prabhudesai, S.P.; Mascarenhas, A.A

    The Autonomous Vertical Profiler (AVP), developed at NIO [1] [2], collects position and water column data over a period of 3 days and transmits through a satellite modem which is collated and stored on a PC. Data includes GPS positions, water column...

  17. Renewable Energy Country Profiles. Caribbean

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-09-15

    IRENA Renewable Energy Country Profiles take stock of the latest developments in the field of renewables at country level around the world. Each profile combines analysis by IRENA's specialists with the latest available country data and additional information from a wide array of sources. The resulting reports provide a brief yet comprehensive picture of the situation with regard to renewable energy, including energy supply, electrical generation and grid capacity, and access. Energy policies, targets and projects are also considered, along with each country's investment climate and endowment with renewable energy resources. The energy statistics presented here span the period from 2009 until 2012, reflecting varying timelines in the source material. Since data availability differs from country to country, wider regional comparisons are possible only for the latest year with figures available for every country included. Despite the time lag in some cases, the evident differences and disparities between countries and regions around the world remain striking. The current package of country profiles is just a starting point. The geographic scope will continue to expand, and existing profiles will be enhanced with new indicators, with the whole series maintained as a live product on the IRENA website (www.irena.org)

  18. 3D terahertz beam profiling

    DEFF Research Database (Denmark)

    Pedersen, Pernille Klarskov; Strikwerda, Andrew; Wang, Tianwu

    2013-01-01

    We present a characterization of THz beams generated in both a two-color air plasma and in a LiNbO3 crystal. Using a commercial THz camera, we record intensity images as a function of distance through the beam waist, from which we extract 2D beam profiles and visualize our measurements into 3D beam...

  19. Country Energy Profile, South Africa

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-08-01

    This country energy profile provides energy and economic information about South Africa. Areas covered include: Economics, demographics, and environment; Energy situation; Energy structure; Energy investment opportunities; Department of Energy (DOE) programs in South Africa; and a listing of International aid to South Africa.

  20. Profiling Mobile English Language Learners

    Science.gov (United States)

    Byrne, Jason; Diem, Robert

    2014-01-01

    The purpose of this study was to use an app-embedded survey to profile language learner demographics. A total of 3,759 EFL language learners from primarily eight L1 backgrounds (French, German, Italian, Japanese, Korean, Russian, Spanish and Thai) responded to the survey embedded within a popular English grammar app. This app has over 500,000…