WorldWideScience

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. PMID:26541648

  2. 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.

  3. 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.

  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. Chemogenomics of allosteric binding sites in GPCRs

    DEFF Research Database (Denmark)

    Gloriam, David E.

    2013-01-01

    profiling. This review describes recent developments structured into ligand-, target- and combined chemogenomic techniques and applications to allosteric GPCR ligands. It also outlines relative strengths and limitations of these techniques and the impact of the increasing crystallographic data....

  6. A Chemogenomic Analysis of Ionization Constants - Implications for Drug Discovery

    OpenAIRE

    David T. Manallack; Prankerd, Richard J.; Nassta, Gemma C.; Ursu, Oleg; Oprea, Tudor I.; Chalmers, David K.

    2013-01-01

    Chemogenomics methods seek to characterize the interaction between drugs and biological systems and are an important guide for the selection of screening compounds. The acid/base character of drugs has a profound influence on their affinity for the receptor, on their absorption, distribution, metabolism, excretion and toxicity (ADMET) profile and the way the drug can be formulated. In particular, the charge state of a molecule greatly influences its lipophilicity and biopharmaceutical charact...

  7. A systematic study of chemogenomics of carbohydrates.

    Science.gov (United States)

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

    2014-03-01

    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.

  8. 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

  9. Small and colorful stones make beautiful mosaics: fragment-based chemogenomics.

    Science.gov (United States)

    de Graaf, Chris; Vischer, Henry F; de Kloe, Gerdien E; Kooistra, Albert J; Nijmeijer, Saskia; Kuijer, Martien; Verheij, Mark H P; England, Paul J; van Muijlwijk-Koezen, Jacqueline E; Leurs, Rob; de Esch, Iwan J P

    2013-04-01

    Smaller stones with a wide variety of colors make a higher resolution mosaic. In much the same way, smaller chemical entities that are structurally diverse are better able to interrogate protein binding sites. This feature article describes the construction of a diverse fragment library and an analysis of the screening of six representative protein targets belonging to three diverse target classes (G protein-coupled receptors ADRB2, H1R, H3R, and H4R, the ligand-gated ion channel 5-HT3R, and the kinase PKA) using chemogenomics approaches. The integration of experimentally determined bioaffinity profiles across related and unrelated protein targets and chemogenomics analysis of fragment binding and protein structure allow the identification of: (i) unexpected similarities and differences in ligand binding properties, and (ii) subtle ligand affinity and selectivity cliffs. With a wealth of fragment screening data being generated in industry and academia, such approaches will contribute to a more detailed structural understanding of ligand-protein interactions. PMID:23266367

  10. Semantic inference using chemogenomics data for drug discovery

    Directory of Open Access Journals (Sweden)

    Ding Ying

    2011-06-01

    Full Text Available Abstract Background Semantic Web Technology (SWT makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, and Chem2Bio2RDF. Integration of these sets creates large networks of information. We have previously described a tool called WENDI for aggregating information pertaining to new chemical compounds, effectively creating evidence paths relating the compounds to genes, diseases and so on. In this paper we examine the utility of automatically inferring new compound-disease associations (and thus new links in the network based on semantically marked-up versions of these evidence paths, rule-sets and inference engines. Results Through the implementation of a semantic inference algorithm, rule set, Semantic Web methods (RDF, OWL and SPARQL and new interfaces, we have created a new tool called Chemogenomic Explorer that uses networks of ontologically annotated RDF statements along with deductive reasoning tools to infer new associations between the query structure and genes and diseases from WENDI results. The tool then permits interactive clustering and filtering of these evidence paths. Conclusions We present a new aggregate approach to inferring links between chemical compounds and diseases using semantic inference. This approach allows multiple evidence paths between compounds and diseases to be identified using a rule-set and semantically annotated data, and for these evidence paths to be clustered to show overall evidence linking the compound to a disease. We believe this is a powerful approach, because it allows compound-disease relationships to be ranked by the amount of evidence supporting them.

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

    OpenAIRE

    Jaime Maria DLA; Lopez-Llorca Luis; Conesa Ana; Lee Anna Y; Proctor Michael; Heisler Lawrence E; Gebbia Marinella; Giaever Guri; Westwood J; Nislow Corey

    2012-01-01

    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...

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

    Directory of Open Access Journals (Sweden)

    Bruno J Neves

    2015-01-01

    Full Text Available 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.

  13. 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

  14. A predictable Java profile - rationale and implementations

    DEFF Research Database (Denmark)

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

    2009-01-01

    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......, 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...

  15. 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...

  16. Predicting aquaplaning performance from tyre profile images with machine learning

    OpenAIRE

    Weyde, T.; Slabaugh, G.G.; Fontaine, G.; Bederna, C.

    2013-01-01

    The tread of a tyre consists of a profile (pattern of grooves, sipes, and blocks) mainly designed to improve wet performance and inhibit aquaplaning by providing a conduit for water to be expelled underneath the tyre as it makes contact with the road surface. Testing different tread profile designs is time consuming, as it requires fabrication and physical measurement of tyres. We propose a supervised machine learning method to predict tyres’ aquaplaning performance based on the tread profile...

  17. Gene Expression Profiling Predicts the Development of Oral Cancer

    OpenAIRE

    Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

    2011-01-01

    Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer develo...

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. Predictive Models for Fast and Effective Profiling of Kinase Inhibitors.

    Science.gov (United States)

    Bora, Alina; Avram, Sorin; Ciucanu, Ionel; Raica, Marius; Avram, Stefana

    2016-05-23

    In this study we developed two-dimensional pharmacophore-based random forest models for the effective profiling of kinase inhibitors. One hundred seven prediction models were developed to address distinct kinases spanning over all kinase groups. Rigorous external validation demonstrates excellent virtual screening and classification potential of the predictors and, more importantly, the capacity to prioritize novel chemical scaffolds in large chemical libraries. The models built upon more diverse and more potent compounds tend to exert the highest predictive power. The analysis of ColBioS-FlavRC (Collection of Bioselective Flavonoids and Related Compounds) highlighted several potentially promiscuous derivatives with undesirable selectivity against kinases. The prediction models can be downloaded from www.chembioinf.ro . PMID:27064988

  3. Prediction of flash flood hazard impact from Himalayan river profiles

    Science.gov (United States)

    Devrani, R.; Singh, V.; Mudd, S. M.; Sinclair, H. D.

    2015-07-01

    To what extent can we treat topographic metrics such as river long profiles as a long-term record of multiple extreme geomorphic events and hence use them for hazard prediction? We demonstrate that in an area of rapid mountain erosion where the landscape is highly reactive to extreme events, channel steepness measured by integrating area over upstream distance (chi analysis) can be used as an indicator of geomorphic change during flash floods. We compare normalized channel steepness to the impact of devastating floods in the upper Ganga Basin in Uttarakhand, northern India, in June 2013. The pattern of sediment accumulation and erosion is broadly predictable from the distribution of normalized channel steepness; in reaches of high steepness, channel lowering up to 5 m undercut buildings causing collapse; in low steepness reaches, channels aggraded up to 30 m and widened causing flooding and burial by sediment. Normalized channel steepness provides a first-order prediction of the signal of geomorphic change during extreme flood events. Sediment aggradation in lower gradient reaches is a predictable characteristic of floods with a proportion of discharge fed by point sources such as glacial lakes.

  4. 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.

  5. 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. PMID:26548639

  6. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  7. 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.

  8. 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.

  9. Colon cancer prediction with genetic profiles using intelligent techniques

    Science.gov (United States)

    Alladi, Subha Mahadevi; P, Shinde Santosh; Ravi, Vadlamani; Murthy, Upadhyayula Suryanarayana

    2008-01-01

    Micro array data provides information of expression levels of thousands of genes in a cell in a single experiment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. In our present study we have used the benchmark colon cancer data set for analysis. Feature selection is done using t‐statistic. Comparative study of class prediction accuracy of 3 different classifiers viz., support vector machine (SVM), neural nets and logistic regression was performed using the top 10 genes ranked by the t‐statistic. SVM turned out to be the best classifier for this dataset based on area under the receiver operating characteristic curve (AUC) and total accuracy. Logistic Regression ranks as the next best classifier followed by Multi Layer Perceptron (MLP). The top 10 genes selected by us for classification are all well documented for their variable expression in colon cancer. We conclude that SVM together with t-statistic based feature selection is an efficient and viable alternative to popular techniques. PMID:19238250

  10. 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.

  11. 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.

  12. 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

  13. 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...... phylogenetic profiles often require very different RT sets to support high prediction accuracy....

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

    DEFF Research Database (Denmark)

    Fruergaard, Bjarne Ørum; Hansen, Lars Kai

    2014-01-01

    In real time advertising we are interested in finding features that improve click-through rate prediction. One source of available information is the bipartite graph of websites previously engaged by identifiable users. In this work, we investigate three different decompositions of such a graph w...

  15. A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

    OpenAIRE

    Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

    2011-01-01

    Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to N...

  16. 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.

  17. A lifetime prediction method for LEDs considering mission profiles

    DEFF Research Database (Denmark)

    Qu, Xiaohui; Wang, Huai; Zhan, Xiaoqing;

    2016-01-01

    Light-Emitting Diodes (LEDs) 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. 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...... available from accelerated degradation testing. It identifies also the key variables (e.g., heat sink parameters and lifetime-matching of LED drivers) that can be designed to achieve a specified lifetime and reliability level. Two case studies of an indoor residential lighting and an outdoor street lighting...

  18. The prediction of interferon treatment effects based on time series microarray gene expression profiles

    OpenAIRE

    Wei Chao-Chun; Shyr Yu; Tu Kang; Huang Tao; Xie Lu; Li Yi-Xue

    2008-01-01

    Abstract Background The status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study. Methods In the published study, 33 African-American (AA) and 36 Caucasian American (CA) patients with chroni...

  19. Predicting temperature profiles in producing oil wells using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Farshad, F.F.; Garber, J.D.; Lorde, J.N. [Louisiana Univ., Lafayette, LA (United States)

    2000-10-19

    A novel approach using artificial neural networks (ANNs) for predicting temperature profiles evaluated 27 wells in the Gulf of Mexico. Two artificial neural network models were developed that predict the temperature of the flowing fluid at any depth in flowing oil wells. Back propagation was used in training the networks. The networks were tested using measured temperature profiles from the 27 oil wells. Both neural network models successfully mapped the general temperature-profile trends of naturally flowing oil wells. The highest accuracy was achieved with a mean absolute relative percentage error of 6.0 per cent. The accuracy of the proposed neural network models to predict the temperature profile is compared to that of existing correlations. Many correlations to predict temperature profiles of the wellbore fluid, for single-phase or multiphase flow, in producing oil wells have been developed using theoretical principles such as energy, mass and momentum balances coupled with regression analysis. The Neural Network 2 model exhibited significantly lower mean absolute relative percentage error than other correlations. Furthermore, in order to test the accuracy of the neural network models to that of Kirkpatrick's correlation, a mathematical model was developed for Kirkpatrick's flowing temperature gradient chart. (Author)

  20. 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...

  1. Predicting enzyme targets for cancer drugs by profiling human Metabolic reactions in NCI-60 cell lines

    Directory of Open Access Journals (Sweden)

    Ching Wai-Ki

    2010-10-01

    Full Text Available Abstract Background Drugs can influence the whole metabolic system by targeting enzymes which catalyze metabolic reactions. The existence of interactions between drugs and metabolic reactions suggests a potential way to discover drug targets. Results In this paper, we present a computational method to predict new targets for approved anti-cancer drugs by exploring drug-reaction interactions. We construct a Drug-Reaction Network to provide a global view of drug-reaction interactions and drug-pathway interactions. The recent reconstruction of the human metabolic network and development of flux analysis approaches make it possible to predict each metabolic reaction's cell line-specific flux state based on the cell line-specific gene expressions. We first profile each reaction by its flux states in NCI-60 cancer cell lines, and then propose a kernel k-nearest neighbor model to predict related metabolic reactions and enzyme targets for approved cancer drugs. We also integrate the target structure data with reaction flux profiles to predict drug targets and the area under curves can reach 0.92. Conclusions The cross validations using the methods with and without metabolic network indicate that the former method is significantly better than the latter. Further experiments show the synergism of reaction flux profiles and target structure for drug target prediction. It also implies the significant contribution of metabolic network to predict drug targets. Finally, we apply our method to predict new reactions and possible enzyme targets for cancer drugs.

  2. 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

    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......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...... 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...

  3. Predicting Low Energy Dopant Implant Profiles in Semiconductors using Molecular Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Beardmore, K.M.; Gronbech-Jensen, N.

    1999-05-02

    The authors present a highly efficient molecular dynamics scheme for calculating dopant density profiles in group-IV alloy, and III-V zinc blende structure materials. Their scheme incorporates several necessary methods for reducing computational overhead, plus a rare event algorithm to give statistical accuracy over several orders of magnitude change in the dopant concentration. The code uses a molecular dynamics (MD) model to describe ion-target interactions. Atomic interactions are described by a combination of 'many-body' and pair specific screened Coulomb potentials. Accumulative damage is accounted for using a Kinchin-Pease type model, inelastic energy loss is represented by a Firsov expression, and electronic stopping is described by a modified Brandt-Kitagawa model which contains a single adjustable ion-target dependent parameter. Thus, the program is easily extensible beyond a given validation range, and is therefore truly predictive over a wide range of implant energies and angles. The scheme is especially suited for calculating profiles due to low energy and to situations where a predictive capability is required with the minimum of experimental validation. They give examples of using the code to calculate concentration profiles and 2D 'point response' profiles of dopants in crystalline silicon and gallium-arsenide. Here they can predict the experimental profile over five orders of magnitude for <100> and <110> channeling and for non-channeling implants at energies up to hundreds of keV.

  4. Chemogenomic analysis of G-protein coupled receptors and their ligands deciphers locks and keys governing diverse aspects of signalling.

    Directory of Open Access Journals (Sweden)

    Jörg D Wichard

    Full Text Available Understanding the molecular mechanism of signalling in the important super-family of G-protein-coupled receptors (GPCRs is causally related to questions of how and where these receptors can be activated or inhibited. In this context, it is of great interest to unravel the common molecular features of GPCRs as well as those related to an active or inactive state or to subtype specific G-protein coupling. In our underlying chemogenomics study, we analyse for the first time the statistical link between the properties of G-protein-coupled receptors and GPCR ligands. The technique of mutual information (MI is able to reveal statistical inter-dependence between variations in amino acid residues on the one hand and variations in ligand molecular descriptors on the other. Although this MI analysis uses novel information that differs from the results of known site-directed mutagenesis studies or published GPCR crystal structures, the method is capable of identifying the well-known common ligand binding region of GPCRs between the upper part of the seven transmembrane helices and the second extracellular loop. The analysis shows amino acid positions that are sensitive to either stimulating (agonistic or inhibitory (antagonistic ligand effects or both. It appears that amino acid positions for antagonistic and agonistic effects are both concentrated around the extracellular region, but selective agonistic effects are cumulated between transmembrane helices (TMHs 2, 3, and ECL2, while selective residues for antagonistic effects are located at the top of helices 5 and 6. Above all, the MI analysis provides detailed indications about amino acids located in the transmembrane region of these receptors that determine G-protein signalling pathway preferences.

  5. Children's Reading Profiles on Exiting the Reading Recovery Programme: Do They Predict Sustained Progress?

    Science.gov (United States)

    Holliman, Andrew J.; Hurry, Jane; Bodman, Sue

    2016-01-01

    The aim of this study was to identify reading profiles, which predict the literacy progress of Reading Recovery graduates. Reading Recovery is an intensive remediation for children after the first year of school. Children were assessed at exit from the programme and at 3-month, 6-month and 12-month follow-up points. Text Reading Level made unique…

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

    NARCIS (Netherlands)

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

    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

  7. 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.

  8. 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.

  9. 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

  10. Prediction of jominy hardness profiles of steels using artificial neural networks

    Science.gov (United States)

    Vermeulen, W. G.; van der Wolk, P. J.; de Weijer, A. P.; van der Zwaag, S.

    1996-02-01

    Jominy hardness profiles of steels were predicted from chemical composition and austenitizing temperature using an artificial neural network. The neural network was trained using some 4000 examples, covering a wide range of steel compositions. The performance of the neural network is examined as a function of the network architecture, the number of alloying elements, and the number of data sets used for training. A well-trained network predicts the Jominy hardness profile with an average error of about 2 HRC. Special attention was devoted to the effect of boron on hardenability. A network trained using data only from boron steels produced results similar to those of a network trained using all data available. The accuracy of the predictions of the model is compared with that of an analytical model for hardenability and with that of a partial least- squares model using the same set of data.

  11. 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

  12. The prediction of interferon treatment effects based on time series microarray gene expression profiles

    Directory of Open Access Journals (Sweden)

    Wei Chao-Chun

    2008-08-01

    Full Text Available Abstract Background The status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study. Methods In the published study, 33 African-American (AA and 36 Caucasian American (CA patients with chronic HCV genotype 1 infection received pegylated interferon and ribavirin therapy for 28 days. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells (PBMC of all the patients on day 0 (pretreatment, 1, 2, 7, 14, and 28. According to the decrease of HCV RNA levels on day 28, two categories of responses were defined: good and poor. A voting method based on Student's t test, Wilcoxon test, empirical Bayes test and significance analysis of microarray was used to identify differentially expressed genes. A time-dependent diagnostic model based on C4.5 decision tree was constructed to predict the treatment outcome. This model not only utilized the gene expression profiles before the treatment, but also during the treatment. Leave-one-out cross validation was used to evaluate the performance of the model. Results The model could correctly predict all Caucasian American patients' treatment effects at very early time point. The prediction accuracy of African-American patients achieved 85.7%. In addition, thirty potential biomarkers which may play important roles in response to interferon and ribavirin were identified. Conclusion Our method provides a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatical strategies may be used to improve treatment decisions for

  13. 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. PMID:25071985

  14. 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.

  15. 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.

  16. A statistical approach for predicting thermal diffusivity profiles in fusion plasmas as a transport model

    International Nuclear Information System (INIS)

    A statistical approach is proposed to predict thermal diffusivity profiles as a transport “model” in fusion plasmas. It can provide regression expressions for the ion and electron heat diffusivities (χi and χe), separately, to construct their radial profiles. An approach that this letter is proposing outstrips the conventional scaling laws for the global confinement time (τE) since it also deals with profiles (temperature, density, heating depositions etc.). This approach has become possible with the analysis database accumulated by the extensive application of the integrated transport analysis suite to experiment data. In this letter, TASK3D-a analysis database for high-ion-temperature (high-Ti) plasmas in the LHD (Large Helical Device) is used as an example to describe an approach. (author)

  17. 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.

  18. Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates

    OpenAIRE

    Yabu, Julie M.; Siebert, Janet C.; Maecker, Holden T.

    2016-01-01

    Background Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profile...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Prediction profiles for nutritional supplement use among young German elite athletes.

    Science.gov (United States)

    Dietz, Pavel; Ulrich, Rolf; Niess, Andreas; Best, Raymond; Simon, Perikles; Striegel, Heiko

    2014-12-01

    Nutritional supplements (NS) are defined as concentrated sources of nutrients and other substances that have a nutritional or physiological effect and that are used in high frequency among athletes. The study aimed to create a prediction profile for young elite athletes to identify those athletes who have a higher relative risk for using NS. The second objective was to examine the hypothesis that the consumption of NS paves a gateway for the use of illicit drugs and doping substances. A self-designed anonymous paper-and-pencil questionnaire was used to examine the prevalence of NS consumption, doping, and illicit drug use in elite athletes with a mean age of 17 years (SD = 4 years). Logistic regression analysis was employed to assess whether NS consumption can be predicted by independent variables (e.g., biographical data, training characteristics, drug consumption behavior) to create the prediction profile for NS use. 55% and 5% of the athletes (n = 536) responded positively to having used NS and illicit drugs, respectively. Nutritional supplement consumption was positively correlated with age (OR: 1.92; CI: 1.21 to 3.05), the desire to enhance performance to become an Olympic or World Champion (OR: 3.72; CI: 2.33 to 6.01), and being educated about NS (OR: 2.76; CI: 1.73 to 4.45). It was negatively correlated with training frequency (OR: 0.55; CI: 0.35 to 0.86) and the use of nicotine (OR: 0.29; CI: 0.1 to 0.74) but did not correlate with illicit drug use and alcohol consumption. The present results show that NS are used on a large scale in elite sports. The prediction profile presented in this article may help to identify those athletes who have a high risk for using NS to plan potential education and prevention models more individually. PMID:24901677

  6. 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/.

  7. 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. PMID:27170644

  8. Protein profiling reveals consequences of lifestyle choices on predicted biological aging.

    Science.gov (United States)

    Enroth, Stefan; Enroth, Sofia Bosdotter; Johansson, Åsa; Gyllensten, Ulf

    2015-01-01

    Ageing is linked to a number of changes in how the body and its organs function. On a molecular level, ageing is associated with a reduction of telomere length, changes in metabolic and gene-transcription profiles and an altered DNA-methylation pattern. Lifestyle factors such as smoking or stress can impact some of these molecular processes and thereby affect the ageing of an individual. Here we demonstrate by analysis of 77 plasma proteins in 976 individuals, that the abundance of circulating proteins accurately predicts chronological age, as well as anthropometrical measurements such as weight, height and hip circumference. The plasma protein profile can also be used to identify lifestyle factors that accelerate and decelerate ageing. We found smoking, high BMI and consumption of sugar-sweetened beverages to increase the predicted chronological age by 2-6 years, while consumption of fatty fish, drinking moderate amounts of coffee and exercising reduced the predicted age by approximately the same amount. This method can be applied to dried blood spots and may thus be useful in forensic medicine to provide basic anthropometrical measures for an individual based on a biological evidence sample. PMID:26619799

  9. 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.

    2016-01-01

    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. PMID:27170644

  10. Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

    Science.gov (United States)

    Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

    2013-01-01

    Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032

  11. 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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

    Directory of Open Access Journals (Sweden)

    Joseph J Babcock

    Full Text Available Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

  15. 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...

  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. 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.

  18. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

    Directory of Open Access Journals (Sweden)

    Antanas Verikas

    2016-04-01

    Full Text Available This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each. The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG

  19. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

    Science.gov (United States)

    Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M Charlotte

    2016-01-01

    This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features

  20. 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. PMID:25060729

  1. 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.

  2. 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 . PMID:27167132

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

    Directory of Open Access Journals (Sweden)

    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.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. [Physico-chemical profiling of centrally acting molecules for prediction of pharmacokinetic properties].

    Science.gov (United States)

    Deák, Katalin

    2008-01-01

    Physico-chemical profiling is a fundamental tool at the early stage of drug discovery in screening drug-like candidates. Complex physico-chemical profiling, including molecular properties such as solubility, ionization, lipophilicity and permeability, has been found to be of predictive power in ADME (absorption, distribution, metabolism, elimination). In the present thesis work, the physico-chemical properties of centrally acting compounds were investigated. We determined the protonation constants (K), the partition coeffitient in octanol/water (Poct) and cyclohexane/water (Pch) systems of antidepressive sertraline and 15 antipsychotic piperidine and piperazine derivatives and calculated the delta logP (logPoct-logPch) values of the molecules. Due to the poor water solubility of the compounds potentiometry using the "co-solvent" technique was applied for the determination of the protonation constants. The logP values were measured by the dual-phase potentiometric titration in octanol/water system and the traditional shake-flask method was used in cyclohexane/water system. Highly precise physico-chemical data were obtained by these validated methods. The relationship between the structure of the molecules and the physico-chemical data was investigated. The pharmacokinetic properties of the compounds were predicted by the physico-chemical parameters. Linear relationship has been found between the brain penetration characterized by the logBB values and the delta logP values. The validity of the equation was controlled by the delta logP and the logBB values of sertraline. PMID:18986088

  7. 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.

  8. 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.

  9. Computational models for prediction of yeast strain potential for winemaking from phenotypic profiles.

    Directory of Open Access Journals (Sweden)

    Inês Mendes

    Full Text Available Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 °C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL, cycloheximide (0.1 µg/mL and potassium bisulphite (150 mg/mL that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain

  10. Computational models for prediction of yeast strain potential for winemaking from phenotypic profiles.

    Science.gov (United States)

    Mendes, Inês; Franco-Duarte, Ricardo; Umek, Lan; Fonseca, Elza; Drumonde-Neves, João; Dequin, Sylvie; Zupan, Blaz; Schuller, Dorit

    2013-01-01

    Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 °C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection

  11. 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

  12. 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.

  13. 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.

  14. Deep-sequence profiling of miRNAs and their target prediction in Monotropa hypopitys.

    Science.gov (United States)

    Shchennikova, Anna V; Beletsky, Alexey V; Shulga, Olga A; Mazur, Alexander M; Prokhortchouk, Egor B; Kochieva, Elena Z; Ravin, Nikolay V; Skryabin, Konstantin G

    2016-07-01

    Myco-heterotroph Monotropa hypopitys is a widely spread perennial herb used to study symbiotic interactions and physiological mechanisms underlying the development of non-photosynthetic plant. Here, we performed, for the first time, transcriptome-wide characterization of M. hypopitys miRNA profile using high throughput Illumina sequencing. As a result of small RNA library sequencing and bioinformatic analysis, we identified 55 members belonging to 40 families of known miRNAs and 17 putative novel miRNAs unique for M. hypopitys. Computational screening revealed 206 potential mRNA targets for known miRNAs and 31 potential mRNA targets for novel miRNAs. The predicted target genes were described in Gene Ontology terms and were found to be involved in a broad range of metabolic and regulatory pathways. The identification of novel M. hypopitys-specific miRNAs, some with few target genes and low abundances, suggests their recent evolutionary origin and participation in highly specialized regulatory mechanisms fundamental for non-photosynthetic biology of M. hypopitys. This global analysis of miRNAs and their potential targets in M. hypopitys provides a framework for further investigation of miRNA role in the evolution and establishment of non-photosynthetic myco-heterotrophs. PMID:27097902

  15. Urinary cell mRNA profiles predictive of human kidney allograft status.

    Science.gov (United States)

    Lee, John R; Muthukumar, Thangamani; Dadhania, Darshana; Ding, Ruchuang; Sharma, Vijay K; Schwartz, Joseph E; Suthanthiran, Manikkam

    2014-03-01

    Kidney allograft status is currently characterized using the invasive percutaneous needle core biopsy procedure. The procedure has become safer over the years, but challenges and complications still exist including sampling error, interobserver variability, bleeding, arteriovenous fistula, graft loss, and even death. Because the most common type of acute rejection is distinguished by inflammatory cells exiting the intravascular compartment and gaining access to the renal tubular space, we reasoned that a kidney allograft may function as an in vivo flow cytometer and sort cells involved in rejection into urine. To test this idea, we developed quantitative polymerase chain reaction (PCR) assays for absolute quantification of mRNA and pre-amplification protocols to overcome the low RNA yield from urine. Here, we review our single center urinary cell mRNA profiling studies that led to the multicenter Clinical Trials in Organ Transplantation (CTOT-04) study and the discovery and validation of a 3-gene signature of 18S rRNA-normalized measures of CD3ε mRNA and IP-10 mRNA and 18S rRNA that is diagnostic and predictive of acute cellular rejection in the kidney allograft. We also review our development of a 4-gene signature of mRNAs for vimentin, NKCC2, E-cadherin, and 18S rRNA diagnostic of interstitial fibrosis/tubular atrophy (IF/TA). PMID:24517436

  16. 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

  17. 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;

    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...

  18. MicroRNA expression profiles predict progression and clinical outcome in lung adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Lin K

    2016-09-01

    Full Text Available Kang Lin,1,* Tao Xu,1,* Bang-Shun He,1 Yu-Qin Pan,1 Hui-Ling Sun,1 Hong-Xin Peng,2 Xiu-Xiu Hu,2 Shu-Kui Wang1 1Central Laboratory, Nanjing First Hospital, Nanjing Medical University, 2Medical School, Southeast University, Nanjing, Jiangsu, People’s Republic of China *These authors contributed equally to this work Abstract: Lung cancer is one of the leading causes of cancer death worldwide. Accumulating evidence has indicated that microRNAs (miRNAs can be proposed as promising diagnostic and prognostic markers for various cancers. The current study analyzed the miRNA expression profiles of 418 lung adenocarcinoma (LUAD cases obtained from The Cancer Genome Atlas dataset, with the aim to investigate the relationship of miRNAs with progression and prognosis of LUAD. A total of 185 miRNAs were found to be differentially expressed between LUAD tumor tissues and adjacent normal tissues. Among them, 13, 10, 0, and 10 miRNAs were discovered to be associated with pathologic T, N, M, and Stage, respectively. Interestingly, mir-200 family (mir-200a, mir-200b, and mir-429 was shown to play a critical role in the progression of LUAD. In the multivariate Cox regression analysis, mir-1468 (P=0.009, mir-212 (P=0.026, mir-3653 (P=0.012, and mir-31 (P=0.002 were significantly correlated with recurrence-free survival. With regard to overall survival, mir-551b (P=0.011, mir-3653 (P=0.016, and mir-31 (P=0.001 were proven as independent prognostic markers. In summary, this study identified the cancer-specific miRNAs that may predict the progression and prognosis of LUAD. Keywords: microRNA, progression, prognosis, lung adenocarcinoma

  19. Comparison of Global versus Epidermal Growth Factor Receptor Pathway Profiling for Prediction of Lapatinib Sensitivity in Bladder Cancer

    Directory of Open Access Journals (Sweden)

    Dmytro M. Havaleshko

    2009-11-01

    Full Text Available Chemotherapy for metastatic bladder cancer is rarely curative. The recently developed small molecule, lapatinib, a dual epidermal growth factor receptor (EGFR/human epidermal growth factor receptor-2 receptor tyrosine kinase inhibitor, might improve this situation. Recent findings suggest that identifying which patients are likely to benefit from targeted therapies is beneficial, although controversy remains regarding what types of evaluation might yield optimal candidate biomarkers of sensitivity. Here, we address this issue by developing and comparing lapatinib sensitivity prediction models for human bladder cancer cells. After empirically determining in vitro sensitivities (drug concentration necessary to cause a 50% growth inhibition of a panel of 39 such lines to lapatinib treatment, we developed prediction models based on profiling the baseline transcriptome, the phosphorylation status of EGFR pathway signaling targets, or a combination of both data sets. We observed that models derived from microarray gene expression data showed better prediction performance (93%–98% accuracy compared with models derived from EGFR pathway profiling of 23 selected phosphoproteins known to be involved in EGFR-driven signaling (54%–61% accuracy or from a subset of the microarray data for transcripts in the EGFR pathway (86% accuracy. Combining microarray data and phosphoprotein profiling provided a combination model with 98% accuracy. Our findings suggest that transcriptome-wide profiling for biomarkers of lapatinib sensitivity in cancer cells provides models with excellent predictive performance and may be effectively combined with EGFR pathway phosphoprotein profiling data. These results have significant implications for the use of such tools in personalizing the approach to cancers treated with EGFR-directed targeted therapies.

  20. 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.

  1. 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

    2016-05-01

    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.

  2. Evaluation of the impact of AIRS profiles on prediction of Indian summer monsoon using WRF variational data assimilation system

    Science.gov (United States)

    Raju, Attada; Parekh, Anant; Kumar, Prashant; Gnanaseelan, C.

    2015-08-01

    This study investigates the impact of temperature and moisture profiles from Atmospheric Infrared Sounder (AIRS) on the prediction of the Indian summer monsoon, using the variational data assimilation system annexed to the Weather Research and Forecasting model. In this study, three numerical experiments are carried out. The first is the control and includes no assimilation; in the second, named Conv, assimilation of conventional Global Telecommunication System data is performed. The third one, named ConvAIRS, is identical to the Conv except that it also includes assimilation of AIRS profiles. The initial fields of tropospheric temperature and water vapor mixing ratio showed significant improvement over the model domain. Assimilation of AIRS profiles has significant impact on predicting the seasonal mean monsoon characteristics such as tropospheric temperature, low-level moisture distribution, easterly wind shear, and precipitation. The vertical structure of the root-mean-square error is substantially affected by the assimilation of AIRS profiles, with smaller errors in temperature, humidity, and wind magnitude. The consequent improved representation of moisture convergence in the boundary layer (deep convection as well) causes an increase in precipitation forecast skill. The fact that the monsoonal circulation is better captured, thanks to an improved representation of thermal gradients, which in turn leads to more realistic moisture transport, is particularly noteworthy. Several previous data impact studies with AIRS and other sensors have focused on the short or medium range of the forecast. The demonstrated improvement in all the predicted fields associated with the Indian summer monsoon, consequent to the month long assimilation of AIRS profiles, is an innovative finding with large implications to the operational seasonal forecasting capabilities over the Indian subcontinent.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

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

    OpenAIRE

    Lin, Jie; Dai, Yi; Guo, Ya-nan; Xu, Hai-Rong; Wang, Xiao-chang

    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 volati...

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

    OpenAIRE

    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-hou...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

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

    Science.gov (United States)

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

    2007-02-01

    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 the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution.The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data

  14. Prioritizing therapeutics for lung cancer: an integrative meta-analysis of cancer gene signatures and chemogenomic data.

    Directory of Open Access Journals (Sweden)

    Kristen Fortney

    2015-03-01

    Full Text Available Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain.

  15. 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…

  16. 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…

  17. 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…

  18. Protein profiling reveals consequences of lifestyle choices on predicted biological aging

    OpenAIRE

    Stefan Enroth; Sofia Bosdotter Enroth; Åsa Johansson; Ulf Gyllensten

    2015-01-01

    Ageing is linked to a number of changes in how the body and its organs function. On a molecular level, ageing is associated with a reduction of telomere length, changes in metabolic and gene-transcription profiles and an altered DNA-methylation pattern. Lifestyle factors such as smoking or stress can impact some of these molecular processes and thereby affect the ageing of an individual. Here we demonstrate by analysis of 77 plasma proteins in 976 individuals, that the abundance of circulatin...

  19. Taxonomic and predicted metabolic profiles of the human gut microbiome in pre-Columbian mummies.

    Science.gov (United States)

    Santiago-Rodriguez, Tasha M; Fornaciari, Gino; Luciani, Stefania; Dowd, Scot E; Toranzos, Gary A; Marota, Isolina; Cano, Raul J

    2016-11-01

    Characterization of naturally mummified human gut remains could potentially provide insights into the preservation and evolution of commensal and pathogenic microorganisms, and metabolic profiles. We characterized the gut microbiome of two pre-Columbian Andean mummies dating to the 10-15th centuries using 16S rRNA gene high-throughput sequencing and metagenomics, and compared them to a previously characterized gut microbiome of an 11th century AD pre-Columbian Andean mummy. Our previous study showed that the Clostridiales represented the majority of the bacterial communities in the mummified gut remains, but that other microbial communities were also preserved during the process of natural mummification, as shown with the metagenomics analyses. The gut microbiome of the other two mummies were mainly comprised by Clostridiales or Bacillales, as demonstrated with 16S rRNA gene amplicon sequencing, many of which are facultative anaerobes, possibly consistent with the process of natural mummification requiring low oxygen levels. Metagenome analyses showed the presence of other microbial groups that were positively or negatively correlated with specific metabolic profiles. The presence of sequences similar to both Trypanosoma cruzi and Leishmania donovani could suggest that these pathogens were prevalent in pre-Columbian individuals. Taxonomic and functional profiling of mummified human gut remains will aid in the understanding of the microbial ecology of the process of natural mummification. PMID:27559027

  20. 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.

  1. 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.

  2. Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

    Science.gov (United States)

    Kaye, S. M.; Guttenfelder, W.; Bell, R. E.; Gerhardt, S. P.; LeBlanc, B. P.; Maingi, R.

    2014-08-01

    A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as β e , νe ∗ , the MHD α parameter, and the gradient scale lengths of Te, Ti, and ne were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when βe and νe ∗ were relatively low, ballooning parity modes were dominant. As time progressed and both βe and νe ∗ increased, microtearing became the dominant low-kθ mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-kθ, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting Te for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.

  3. 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.

  4. 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

  5. Modeling of Mixolab Profiles by Nonlinear Curve Fitting and Prediction of Breadmaking Parameters

    Science.gov (United States)

    Prediction of breadmaking parameters is a crucial step in wheat quality evaluation for breeders and end-users. This research was performed to investigate the association of flour breadmaking parameters with mixing characteristics and the rheological property of dough subjected to thermal constraint....

  6. Gene Expression Profiling to Predict Outcome After Chemoradiation in Head and Neck Cancer

    International Nuclear Information System (INIS)

    Purpose: The goal of the present study was to improve prediction of outcome after chemoradiation in advanced head and neck cancer using gene expression analysis. Materials and Methods: We collected 92 biopsies from untreated head and neck cancer patients subsequently given cisplatin-based chemoradiation (RADPLAT) for advanced squamous cell carcinomas (HNSCC). After RNA extraction and labeling, we performed dye swap experiments using 35k oligo-microarrays. Supervised analyses were performed to create classifiers to predict locoregional control and disease recurrence. Published gene sets with prognostic value in other studies were also tested. Results: Using supervised classification on the whole series, gene sets separating good and poor outcome could be found for all end points. However, when splitting tumors into training and validation groups, no robust classifiers could be found. Using Gene Set Enrichment analysis, several gene sets were found to be enriched in locoregional recurrences, although with high false-discovery rates. Previously published signatures for radiosensitivity, hypoxia, proliferation, 'wound,' stem cells, and chromosomal instability were not significantly correlated with outcome. However, a recently published signature for HNSCC defining a 'high-risk' group was shown to be predictive for locoregional control in our dataset. Conclusion: Gene sets can be found with predictive potential for locoregional control after combined radiation and chemotherapy in HNSCC. How treatment-specific these gene sets are needs further study

  7. 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.

  8. Gestational hormone profiles predict human maternal behavior at 1-year postpartum.

    Science.gov (United States)

    Glynn, Laura M; Davis, Elysia Poggi; Sandman, Curt A; Goldberg, Wendy A

    2016-09-01

    In many non-human species, including primates, gestational reproductive hormones play an essential role in the onset of maternal motivation and behaviors. We investigated the associations between prepartum estradiol and progesterone and maternal behavior at 1-year postpartum in 177 women. Blood was obtained at five gestational time points and an index of quality of maternal care was determined using a well-validated mother-child interaction protocol. Women who exhibited higher quality maternal care at 1-year postpartum were characterized by unique gestational profiles of estradiol, progesterone and the estrogen to progesterone ratio; specifically by slower accelerations and levels of these hormone trajectories beginning in midgestation. Further, it appeared that both fetal sex and parity moderated these findings, with first time mothers and mothers of females showing stronger associations. In sum, these data document persisting associations between prepartum hormone profiles and human maternal behavior. More broadly, these findings add to the growing literature highlighting the perinatal period as one of critical neurodevelopment in the lifespan of the human female. PMID:27427279

  9. 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. PMID:18812437

  10. Increased Proportion of Variance Explained and Prediction Accuracy of Survival of Breast Cancer Patients with Use of Whole-Genome Multiomic Profiles.

    Science.gov (United States)

    Vazquez, Ana I; Veturi, Yogasudha; Behring, Michael; Shrestha, Sadeep; Kirst, Matias; Resende, Marcio F R; de Los Campos, Gustavo

    2016-07-01

    Whole-genome multiomic profiles hold valuable information for the analysis and prediction of disease risk and progression. However, integrating high-dimensional multilayer omic data into risk-assessment models is statistically and computationally challenging. We describe a statistical framework, the Bayesian generalized additive model ((BGAM), and present software for integrating multilayer high-dimensional inputs into risk-assessment models. We used BGAM and data from The Cancer Genome Atlas for the analysis and prediction of survival after diagnosis of breast cancer. We developed a sequence of studies to (1) compare predictions based on single omics with those based on clinical covariates commonly used for the assessment of breast cancer patients (COV), (2) evaluate the benefits of combining COV and omics, (3) compare models based on (a) COV and gene expression profiles from oncogenes with (b) COV and whole-genome gene expression (WGGE) profiles, and (4) evaluate the impacts of combining multiple omics and their interactions. We report that (1) WGGE profiles and whole-genome methylation (METH) profiles offer more predictive power than any of the COV commonly used in clinical practice (e.g., subtype and stage), (2) adding WGGE or METH profiles to COV increases prediction accuracy, (3) the predictive power of WGGE profiles is considerably higher than that based on expression from large-effect oncogenes, and (4) the gain in prediction accuracy when combining multiple omics is consistent. Our results show the feasibility of omic integration and highlight the importance of WGGE and METH profiles in breast cancer, achieving gains of up to 7 points area under the curve (AUC) over the COV in some cases. PMID:27129736

  11. A Gram-Negative Bacterial Secreted Protein Types Prediction Method Based on PSI-BLAST Profile

    Science.gov (United States)

    2016-01-01

    Prediction of secreted protein types based solely on sequence data remains to be a challenging problem. In this study, we extract the long-range correlation information and linear correlation information from position-specific score matrix (PSSM). A total of 6800 features are extracted at 17 different gaps; then, 309 features are selected by a filter feature selection method based on the training set. To verify the performance of our method, jackknife and independent dataset tests are performed on the test set and the reported overall accuracies are 93.60% and 100%, respectively. Comparison of our results with the existing method shows that our method provides the favorable performance for secreted protein type prediction.

  12. Cardiovascular Regulation Profile Predicts Developmental Trajectory of BMI and Pediatric Obesity

    OpenAIRE

    Graziano, Paulo A.; Calkins, Susan D.; Keane, Susan P.; O’Brien, Marion

    2011-01-01

    The present study examined the role of cardiovascular regulation in predicting pediatric obesity. Participants for this study included 268 children (141 girls) obtained from a larger ongoing longitudinal study. To assess cardiac vagal regulation, resting measures of respiratory sinus arrhythmia (RSA) and RSA change (vagal withdrawal) to three cognitively challenging tasks were derived when children were 5.5 years of age. Heart period (HP) and HP change (heart rate (HR) acceleration) were also...

  13. A validated miRNA profile predicts response to therapy in esophageal adenocarcinoma

    OpenAIRE

    SKINNER, HEATH D.; Lee, Jeffrey H.; Manoop S. Bhutani; Weston, Brian; Hofstetter, Wayne; Komaki, Ritsuko; Shiozaki, Hironori; Wadhwa, Roopma; Sudo, Kazuki; Elimova, Elena; Song, Shumei; Ye, Yuanqing; Huang, Maosheng; Ajani, Jaffer; Wu, Xifeng

    2014-01-01

    BACKGROUND In the current study we present a validated miRNA signature to predict pathologic complete response (pCR) to neoadjuvant chemoradiation in esophageal adenocarcinoma. METHODS Three patient cohorts (discovery, n = 10; model, n = 43; and validation, n = 65) with locally advanced esophageal adenocarcinoma were analyzed. In the discovery cohort 754 miRNAs were examined in pretreatment tumor biopsy specimens using a TaqMan array. Of these, the 44 most significantly altered between tumors...

  14. Gene expression profiles on predicting protein interaction network and exploring of new treatments for lung cancer.

    Science.gov (United States)

    Yang, Zehui; Zheng, Rui; Gao, Yuan; Zhang, Qiang

    2014-12-01

    In the present study, we aimed to explore disease-associated genes and their functions in lung cancer. We downloaded the gene expression profile GSE4115 from Gene Expression Omnibus (GEO) database. Total 97 lung cancer and 90 adjacent non-tumor lung tissue (normal) samples were applied to identify the differentially expressed genes (DEGs) by paired t test and variance analysis in spectral angle mapper (SAM) package in R. Gene Ontology (GO) functional enrichment analysis of DEGs were performed with Database for Annotation Visualization and Integrated Discovery, followed by construction of protein-protein interaction (PPI) network from Human Protein Reference Database (HPRD). Finally, network modules were analyzed by the MCODE algorithm to detect protein complexes in the PPI network. Total 3,102 genes were identified as DEGs at FDR normal and cancer tissues, and exploring new treatments for lung cancer. PMID:25205123

  15. CFD predictions of drilling fluid velocity and pressure profiles in laminar helical flow

    Directory of Open Access Journals (Sweden)

    F. A. R. Pereira

    2007-12-01

    Full Text Available Fluid flow in annular spaces has received a lot of attention from oil industries, both in drilling operations and in petroleum artificial rising. In this work, through numerical simulation using the computational fluid dynamics (CFD technique, the flow of non-Newtonian fluids through the annuli formed by two tubes in concentric and eccentric arrangements of a horizontal system has been investigated. The study analyzes the effects of viscosity, eccentricity, flow and shaft rotation on the tangential and axial velocity profiles and on the hydrodynamic losses. It evaluates the performance of the numerical method used, comparing the results obtained with those in other reported works, aiming to validate the simulation strategy by the interpolation routines as well as the couplings algorithms adopted.

  16. 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.

  17. Profiles of Genomic Instability in High-Grade Serous Ovarian Cancer Predict Treatment Outcome

    DEFF Research Database (Denmark)

    Wang, Zhigang C.; Birkbak, Nicolai Juul; Culhane, Aedín C.;

    2012-01-01

    uniparental deletions and loss of heterozygosity (LOH). Our purpose is to profile LOH in HGSC and correlate our findings to clinical outcome, and compare HGSC and high-grade breast cancers.Experimental Design: We examined LOH and copy number changes using single nucleotide polymorphism array data from three...... other high-grade breast cancers. Our analysis revealed an LOH cluster with lower treatment resistance and a significant correlation between LOH burden and PFS.Conclusions: Separating HGSC by LOH-based clustering produces remarkably stable subgroups in three different cohorts. Patients in the various LOH...... clusters differed with respect to chemotherapy resistance, and the extent of LOH correlated with PFS. LOH burden may indicate vulnerability to treatment targeting DNA repair, such as PARP1 inhibitors. Clin Cancer Res; 18(20); 5806–15. ©2012 AACR....

  18. 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

  19. 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.

  20. 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...

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

    Science.gov (United States)

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

    2011-06-01

    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 composition, and energy balance. The aim of this study was to evaluate extant rumen VFA stoichiometry models for their ability to predict in vivo VFA molar proportions. The models were evaluated using an independent data set consisting of 101 treatments from 24 peer-reviewed publications with lactating Holstein cows. All publications contained a full diet description, rumen pH, and rumen VFA molar proportions. Stoichiometric models were evaluated based on root mean squared prediction error (RMSPE) and concordance correlation coefficient (CCC) analysis. Of all models evaluated, the 1998 Friggens model had the lowest RMSPE for Ac and Bu (7.2 and 20.2% of observed mean, respectively). The 2006 Bannink model had the lowest RMSPE and highest CCC for Pr (14.4% and 0.70, respectively). The 2008 Bannink model had comparable predictive performance for Pr to that of the 2006 Bannink model but a larger error due to overall bias (26.2% of MSPE). The 1982 Murphy model provided the poorest prediction of Bu, with the highest RMSPE and lowest CCC (24.6% and 0.15, respectively). The 1988 Argyle and Baldwin model had the highest CCC for Ac with an intermediate RMSPE (0.47 and 8.0%, respectively). The 2006 Sveinbjörnsson model had the highest RMSPE (13.9 and 34.0%, respectively) and lowest CCC (0.31 and 0.40, respectively) for Ac and Pr. The NGR predictions had the lowest RMSPE and highest CCC in the 2 models of Bannink, whereas the lowest predictive performance was in the 2006 Sveinbjörnsson model. It appears that the type of VFA produced is not a simple linear relationship between substrate inputs and pH as currently represented. The analysis demonstrates that most rumen VFA

  2. 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.

  3. 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.

  4. Predicting the impact of vegetations in open channels with different distributaries' operations on water surface profile using artificial neural networks

    International Nuclear Information System (INIS)

    Most of the open water irrigation channels in Egypt suffer from the infestation of aquatic weeds, especially the submerged ones that cause numerous hydraulic problems for the open channels themselves and their water distributaries such as increasing water losses, obstructing water flow, and reducing channels' water distribution efficiencies. Accurate simulation and prediction of flow behavior in such channels is very essential for water distribution decision makers. Artificial neural networks (ANN) have proven to be very successful in the simulation of several physical phenomena, in general, and in the water research field in particular. Therefore, the current study aims towards introducing the utilization of ANN in simulating the impact of vegetation in main open channel, which supplies water to different distributaries, on the water surface profile in this main channel. Specifically, the study, presented in the current paper utilizes ANN technique for the development of various models to simulate the impact of different submerged weeds' densities, different flow discharges, and different distributaries operation scheduling on the water surface profile in an experimental main open channel that supplies water to different distributaries. In the investigated experiment, the submerged weeds were simulated as branched flexible elements. The investigated experiment was considered as an example for implementing the same methodology and technique in a real open channel system. The results showed that the ANN technique is very successful in simulating the flow behavior of the pre-mentioned open channel experiment with the existence of the submerged weeds. In addition, the developed ANN models were capable of predicting the open channel flow behavior in all the submerged weeds' cases that were considered in the ANN development process

  5. Dopamine Gene Profiling to Predict Impulse Control and Effects of Dopamine Agonist Ropinirole.

    Science.gov (United States)

    MacDonald, Hayley J; Stinear, Cathy M; Ren, April; Coxon, James P; Kao, Justin; Macdonald, Lorraine; Snow, Barry; Cramer, Steven C; Byblow, Winston D

    2016-07-01

    Dopamine agonists can impair inhibitory control and cause impulse control disorders for those with Parkinson disease (PD), although mechanistically this is not well understood. In this study, we hypothesized that the extent of such drug effects on impulse control is related to specific dopamine gene polymorphisms. This double-blind, placebo-controlled study aimed to examine the effect of single doses of 0.5 and 1.0 mg of the dopamine agonist ropinirole on impulse control in healthy adults of typical age for PD onset. Impulse control was measured by stop signal RT on a response inhibition task and by an index of impulsive decision-making on the Balloon Analogue Risk Task. A dopamine genetic risk score quantified basal dopamine neurotransmission from the influence of five genes: catechol-O-methyltransferase, dopamine transporter, and those encoding receptors D1, D2, and D3. With placebo, impulse control was better for the high versus low genetic risk score groups. Ropinirole modulated impulse control in a manner dependent on genetic risk score. For the lower score group, both doses improved response inhibition (decreased stop signal RT) whereas the lower dose reduced impulsiveness in decision-making. Conversely, the higher score group showed a trend for worsened response inhibition on the lower dose whereas both doses increased impulsiveness in decision-making. The implications of the present findings are that genotyping can be used to predict impulse control and whether it will improve or worsen with the administration of dopamine agonists. PMID:26942320

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. Prediction of protein structure classes using hybrid space of multi-profile Bayes and bi-gram probability feature spaces.

    Science.gov (United States)

    Hayat, Maqsood; Tahir, Muhammad; Khan, Sher Afzal

    2014-04-01

    Proteins are the executants of biological functions in living organisms. Comprehension of protein structure is a challenging problem in the era of proteomics, computational biology, and bioinformatics because of its pivotal role in protein folding patterns. Owing to the large exploration of protein sequences in protein databanks and intricacy of protein structures, experimental and theoretical methods are insufficient for prediction of protein structure classes. Therefore, it is highly desirable to develop an accurate, reliable, and high throughput computational model to predict protein structure classes correctly from polygenetic sequences. In this regard, we propose a promising model employing hybrid descriptor space in conjunction with optimized evidence-theoretic K-nearest neighbor algorithm. Hybrid space is the composition of two descriptor spaces including Multi-profile Bayes and bi-gram probability. In order to enhance the generalization power of the classifier, we have selected high discriminative descriptors from the hybrid space using particle swarm optimization, a well-known evolutionary feature selection technique. Performance evaluation of the proposed model is performed using the jackknife test on three low similarity benchmark datasets including 25PDB, 1189, and 640. The success rates of the proposed model are 87.0%, 86.6%, and 88.4%, respectively on the three benchmark datasets. The comparative analysis exhibits that our proposed model has yielded promising results compared to the existing methods in the literature. In addition, our proposed prediction system might be helpful in future research particularly in cases where the major focus of research is on low similarity datasets. PMID:24384128

  11. 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.

  12. COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated With Oxidation and Interdiffusion of Overlay-Coated Substrates

    Science.gov (United States)

    Nesbitt, James A.

    2001-01-01

    A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating life based on a concentration dependent failure criterion (e.g., surface solute content drops to 2%). The computer code is written in FORTRAN and employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

  13. 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

  14. miR expression profiling at diagnosis predicts relapse in pediatric precursor B-cell acute lymphoblastic leukemia.

    Science.gov (United States)

    Avigad, Smadar; Verly, Iedan R N; Lebel, Asaf; Kordi, Oshrit; Shichrur, Keren; Ohali, Anat; Hameiri-Grossman, Michal; Kaspers, Gertjan J L; Cloos, Jacqueline; Fronkova, Eva; Trka, Jan; Luria, Drorit; Kodman, Yona; Mirsky, Hadar; Gaash, Dafna; Jeison, Marta; Avrahami, Galia; Elitzur, Sarah; Gilad, Gil; Stark, Batia; Yaniv, Isaac

    2016-04-01

    Our aim was to identify miRNAs that can predict risk of relapse in pediatric patients with acute lymphoblastic leukemia (ALL). Following high-throughput miRNA expression analysis (48 samples), five miRs were selected for further confirmation performed by real time quantitative PCR on a cohort of precursor B-cell ALL patients (n = 138). The results were correlated with clinical parameters and outcome. Low expression of miR-151-5p, and miR-451, and high expression of miR-1290 or a combination of all three predicted inferior relapse free survival (P = 0.007, 0.042, 0.025, and <0.0001, respectively). Cox regression analysis identified aberrant expression of the three miRs as an independent prognostic marker with a 10.5-fold increased risk of relapse (P = 0.041) in PCR-MRD non-high risk patients. Furthermore, following exclusion of patients harboring IKZF1 deletion, the aberrant expression of all three miRs could identify patients with a 24.5-fold increased risk to relapse (P < 0.0001). The prognostic relevance of the three miRNAs was evaluated in a non-BFM treated precursor B-cell ALL cohort (n = 33). A significant correlation between an aberrant expression of at least one of the three miRs and poor outcome was maintained (P < 0.0001). Our results identify an expression profile of miR-151-5p, miR-451, and miR-1290 as a novel biomarker for outcome in pediatric precursor B-cell ALL patients, regardless of treatment protocol. The use of these markers may lead to improved risk stratification at diagnosis and allow early therapeutic interventions in an attempt to improve survival of high risk patients. PMID:26684414

  15. 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.

  16. 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

  17. HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors

    NARCIS (Netherlands)

    M.C. de Jong; J. Pramana; J.L. Knegjens; A.J.M. Balm; M.W.M. van den Brekel; M. Hauptmann; A.C. Begg; C.R.N. Rasch

    2010-01-01

    Purpose: The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. Material and methods: Gene expression data were available for a series of 92 advanced stage

  18. HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors.

    NARCIS (Netherlands)

    Jong, M.C.J. de; Pramana, J.; Knegjens, J.L.; Balm, A.J.; Brekel, M.W. van den; Hauptmann, M.; Begg, A.C.; Rasch, C.R.

    2010-01-01

    PURPOSE: The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. MATERIAL AND METHODS: Gene expression data were available for a series of 92 advanced stage

  19. 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

  20. 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. PMID:26802597

  1. 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.

  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

    BACKGROUND: Breast cancer is characterized by great molecular heterogeneity demonstrated, e.g. by the intrinsic subtypes. Administration of post-mastectomy radiotherapy (PMRT) does, however, not reflect this heterogeneity. A gene profile (DBCG-RT profile) has recently been developed and validated...... 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. 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...

  4. 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

  5. Predicting the educational performance of Isfahan University students of medical sciences based on their behaviour profile, mental health and demographic characteristic

    OpenAIRE

    Samouei, Rahele; Fooladvand, Maryam; Janghorban, Shahla; Khorvash, Fariba

    2015-01-01

    Background: The issue of students’ academic failure is one of the most important educational, economic, and social issues. Cognizance of the factors related to academic downfall is so efficient in its prevention and control and leads to protecting governmental assets and labor force. In order to achieve this goal, this study intends to determine the predictive factors of the students’ academic performance in Isfahan University of Medical Sciences in terms of their personality profile, mental ...

  6. The gut microbiome of the sea urchin, Lytechinus variegatus, from its natural habitat demonstrates selective attributes of microbial taxa and predictive metabolic profiles.

    Science.gov (United States)

    Hakim, Joseph A; Koo, Hyunmin; Kumar, Ranjit; Lefkowitz, Elliot J; Morrow, Casey D; Powell, Mickie L; Watts, Stephen A; Bej, Asim K

    2016-09-01

    In this paper, we describe the microbial composition and their predictive metabolic profile in the sea urchin Lytechinus variegatus gut ecosystem along with samples from its habitat by using NextGen amplicon sequencing and downstream bioinformatics analyses. The microbial communities of the gut tissue revealed a near-exclusive abundance of Campylobacteraceae, whereas the pharynx tissue consisted of Tenericutes, followed by Gamma-, Alpha- and Epsilonproteobacteria at approximately equal capacities. The gut digesta and egested fecal pellets exhibited a microbial profile comprised of Gammaproteobacteria, mainly Vibrio, and Bacteroidetes. Both the seagrass and surrounding sea water revealed Alpha- and Betaproteobacteria. Bray-Curtis distances of microbial communities indicated a clustering profile with low intrasample variation. Predictive metagenomics performed on the microbial communities revealed that the gut tissue had high relative abundances of metabolisms assigned to the KEGG-Level-2 designation of energy metabolisms compared to the gut digesta, which had higher carbohydrate, amino acid and lipid metabolisms. Overall, the results of this study elaborate the spatial distribution of microbial communities in the gut ecosystem of L. variegatus, and specifically a selective attribute for Campylobacteraceae in the gut tissue. Also, the predictive functional significance of bacterial communities in uniquely compartmentalized gut ecosystems of L. variegatus has been described. PMID:27368709

  7. Prediction of Clinical Outcomes by Chemokine and Cytokine Profiling In CSF from Radiation Treated Breast Cancer Primary with Brain Metastases

    Science.gov (United States)

    Lok, Edwin

    Whole brain radiation is the standard treatment for patients with brain metastasis but unfortunately tumors can recover from radiation-induced damage with the help of the immune system. The hypothesis that differences in immunokines in the cerebrospinal fluid (CSF) pre- and post-irradiation could reveal tumor biology and correlate with outcome of patients with metastatic breast cancer to the brain is tested. Collected CSF samples were analyzed using Luminex's multiplexing assays to survey global immunokine levels while Enzyme-Linked Immunosorbent Assays were used to quantify each individual immunokines. Cluster analysis was performed to segregate patients based on their common immunokine profile and each cluster was correlated with survival and other clinical parameters. Breast cancer brain metastasis was found to have altered immunokine profiles in the CSF, and that Interleukin-1α expression was elevated after irradiation. Therefore, immunokine profiling in the CSF could enable cancer physicians to monitor the status of brain metastases.

  8. 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

  9. 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.

  10. 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

  11. 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...

  12. Numerical predictions of flow boiling characteristics: Current status, model setup and CFD modeling for different non-uniform heating profiles

    International Nuclear Information System (INIS)

    A detailed analysis of two-phase flow boiling characteristics inside high pressure systems is presented focusing on non-uniform axial heating profiles. For this purpose, a detailed numerical model has been developed after presenting the current status of the use of CFD techniques in flow boiling predictions. User defined functions written in C++ were compiled and hooked to the software in order to account for mass interaction between phases using the Eulerian multiphase flow model. The modeled domain is a 2 m long stainless steel pipe with inside and outside diameters of 15.4 mm, 25.4 mm, respectively. The base imposed uniform heat flux was 345.6 kW/m2, for mass flow rate of water of 0.161 kg/s and at a temperature of 200 °C. The model was validated against range of experimental data and the results are very promising for the use of CFD in flow boiling characterization. Effects of increasing uniform heat flux were considered for different increments of 30, 50 and 75% as reference to the basic applied heat flux. The influences of heat flux profile in the axial direction were investigated while maintaining the same total power. Different heat flux profiles of linearly increasing, linearly decreasing, sine, and cosine shapes were considered. - Highlights: • Current status of CHF predictions using CFD modeling technique. • State of the art, flow boiling 2D-model for the applications of high pressure systems. • Validation of the model using the available experimental data in the literature. • Investigation of flow boiling in real systems for non-uniform heating profile. • Analysis of keeping the system away from the CHF conditions for non-uniform heating

  13. 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.

  14. 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.

  15. Cellular Defense System Gene Expression Profiling of Human Whole Blood: Opportunities to Predict Health Benefits in Response to Diet12

    OpenAIRE

    Drew, Janice E.

    2012-01-01

    Diet is a critical factor in the maintenance of human cellular defense systems, immunity, inflammation, redox regulation, metabolism, and DNA repair that ensure optimal health and reduce disease risk. Assessment of dietary modulation of cellular defense systems in humans has been limited due to difficulties in accessing target tissues. Notably, peripheral blood gene expression profiles associated with nonhematologic disease are detectable. Coupled with recent innovations in gene expression te...

  16. Gene Expression Profiling and Pathway Network Analysis Predicts a Novel Antitumor Function for a Botanical-Derived Drug, PG2

    OpenAIRE

    Kuo, Yu-Lun; Chen, Chun-houh; Chuang, Tsung-Hsien; Hua, Wei-Kai; Lin, Wey-Jinq; Hsu, Wei-Hsiang; Chang, Peter Mu-Hsin; Hsu, Shih-Lan; Huang, Tse-Hung; Kao, Cheng-Yan; Huang, Chi-Ying F

    2015-01-01

    PG2 is a botanical drug that is mostly composed of Astragalus polysaccharides (APS). Its role in hematopoiesis and relieving cancer-related fatigue has recently been clinically investigated in cancer patients. However, systematic analyses of its functions are still limited. The aim of this study was to use microarray-based expression profiling to evaluate the quality and consistency of PG2 from three different product batches and to study biological mechanisms of PG2. An integrative molecular...

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

    International Nuclear Information System (INIS)

    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

  18. In silico ADME-Toxicity Profiling, Prediction of Bioactivity and CNS Penetrating Properties of some Newer Resveratrol Analogues

    Directory of Open Access Journals (Sweden)

    Supriyo Saha

    2014-03-01

    Full Text Available In silico ADME Toxicity profiling showed an interesting results against the resveratrol and its designed ligands (D1-D16, that these ligands were permeable by intestinal (Human Colonic Carcioma Cell Line CaCo2 cell line and D8, D9, D11, D13, D14, D15, D16 were inhibitor of CYP2C19 microsomal enzyme which were may be active against breast cancer cell line, as the D13, D16 were belong to the p-glycoprotein substrate so there was a chance of efflux in the case of absorption. As well as the toxicity profile checked against the estrogen and androgen receptor,mutagenicity, carcinogenicity, human ether a gogo cell line, LD value clarifies the basic picture of potency. As the detail mechanism of 50 resveratrol was not revealed, so the bioactivity profiling navigate the mechanism behind activity and finally the polar surface area, Log PS and Log BB value justify that molecule D1 was the better molecule which can cross the blood brain barrier. As well as there is a good correlation occurred in between Log P and Log PS with the r2 value 0.7104 which can correlate with the brain penetration capacity of a molecule.

  19. 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.

  20. 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.

  1. 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....

  2. 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

  3. 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

  4. Prediction of Muckpile Profile for Open Bench Blasting with PFC%露天台阶爆破爆堆形态的PFC模拟

    Institute of Scientific and Technical Information of China (English)

    苏都都; 严鹏; 卢文波; 陈明

    2012-01-01

    尝试采用PFC 2D数值方法预测台阶爆破的爆堆形态,并采用该方法对爆堆形态与爆破参数的关系进行了研究.通过与相关观测、模拟结果的比较,论证了该研究方法的可靠性.模拟结果表明:抛距随着单耗q和台阶高度H的增加而增大,随着抵抗线W的增大而减小;爆堆高度与各爆破参数的关系与抛距相反.%The PFC 2D numerical method was used to predict the muckpile profile of bench blasting and to study the relationship between muckpile profile and blasting parameters. By comparison the related observation with the simulation results,this method is reliable. The simulation results show that the throwing distance enlarges with the specific charge q and the bench height H and decreases with the burden W increasing. The height of muckpile profile and the blasting parameters is contrary to the throwing distance.

  5. Glycosaminoglycan Profiling in Patients' Plasma and Urine Predicts the Occurrence of Metastatic Clear Cell Renal Cell Carcinoma.

    Science.gov (United States)

    Gatto, Francesco; Volpi, Nicola; Nilsson, Helén; Nookaew, Intawat; Maruzzo, Marco; Roma, Anna; Johansson, Martin E; Stierner, Ulrika; Lundstam, Sven; Basso, Umberto; Nielsen, Jens

    2016-05-24

    Metabolic reprogramming is a hallmark of clear cell renal cell carcinoma (ccRCC) progression. Here, we used genome-scale metabolic modeling to elucidate metabolic reprogramming in 481 ccRCC samples and discovered strongly coordinated regulation of glycosaminoglycan (GAG) biosynthesis at the transcript and protein levels. Extracellular GAGs are implicated in metastasis, so we speculated that such regulation might translate into a non-invasive biomarker for metastatic ccRCC (mccRCC). We measured 18 GAG properties in 34 mccRCC samples versus 16 healthy plasma and/or urine samples. The GAG profiles were distinctively altered in mccRCC. We derived three GAG scores that distinguished mccRCC patients with 93.1%-100% accuracy. We validated the score accuracies in an independent cohort (up to 18 mccRCC versus nine healthy) and verified that the scores normalized in eight patients with no evidence of disease. In conclusion, coordinated regulation of GAG biosynthesis occurs in ccRCC, and non-invasive GAG profiling is suitable for mccRCC diagnosis. PMID:27184840

  6. Gene Expression Profiling and Pathway Network Analysis Predicts a Novel Antitumor Function for a Botanical-Derived Drug, PG2

    Directory of Open Access Journals (Sweden)

    Yu-Lun Kuo

    2015-01-01

    Full Text Available PG2 is a botanical drug that is mostly composed of Astragalus polysaccharides (APS. Its role in hematopoiesis and relieving cancer-related fatigue has recently been clinically investigated in cancer patients. However, systematic analyses of its functions are still limited. The aim of this study was to use microarray-based expression profiling to evaluate the quality and consistency of PG2 from three different product batches and to study biological mechanisms of PG2. An integrative molecular analysis approach has been designed to examine significant PG2-induced signatures in HL-60 leukemia cells. A quantitative analysis of gene expression signatures was conducted for PG2 by hierarchical clustering of correlation coefficients. The results showed that PG2 product batches were consistent and of high quality. These batches were also functionally equivalent to each other with regard to how they modulated the immune and hematopoietic systems. Within the PG2 signature, there were five genes associated with doxorubicin: IL-8, MDM4, BCL2, PRODH2, and BIRC5. Moreover, the combination of PG2 and doxorubicin had a synergistic effect on induced cell death in HL-60 cells. Together with the bioinformatics-based approach, gene expression profiling provided a quantitative measurement for the quality and consistency of herbal medicines and revealed new roles (e.g., immune modulation for PG2 in cancer treatment.

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

    Science.gov (United States)

    Bellavista, Paolo; Corradi, Antonio; Foschini, Luca; Ianniello, Raffaele

    2015-01-01

    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. PMID:26263985

  8. 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.

  9. Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17,345 persons.

    Directory of Open Access Journals (Sweden)

    Krista Fischer

    2014-02-01

    Full Text Available BACKGROUND: Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts. METHODS AND FINDINGS: 106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18-103 y; 508 deaths during a median of 5.4 y of follow-up. Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up. Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1-standard deviation increment, 95% CI 1.53-1.82, p = 5×10⁻³¹, albumin (HR 0.70, 95% CI 0.65-0.76, p = 2×10⁻¹⁸, very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62-0.77, p = 3×10⁻¹², and citrate (HR 1.33, 95% CI 1.21-1.45, p = 5×10⁻¹⁰. All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001. CONCLUSIONS

  10. Prediction and optimization of residual stresses, weld-bead profile and mechanical properties of laser welded components

    OpenAIRE

    Benyounis, Khaled

    2006-01-01

    Recently, laser welding has become a leading industrial joining process. Mainly because it has become highly automated using sophisticated robotic systems. However, to make effective use of automated laser welding it is essential to have a high degree of confidence in predicting the welding outcome. To achieve a desired weld quality, the weldments are normally examined and related to the weld input parameters. This input-output relationship can be in the form of mathematical models that can b...

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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 benig...... 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...... lymphadenopathy, with samples from patients with no subsequent history of neoplasia. Design: All patients were identified retrospectively from the Danish HIV cohort. Methods: Serum samples (N=21), obtained at time of HIV diagnosis, were subjected to high-resolution two-dimensional gel electrophoresis...

  16. 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.

  17. 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.

  18. A novel chemogenomics analysis of G protein-coupled receptors (GPCRs and their ligands: a potential strategy for receptor de-orphanization

    Directory of Open Access Journals (Sweden)

    Emmerich Michael TM

    2010-06-01

    -based classification uncovers relationships among GPCRs that are not apparent from the sequence-based classification. This will shed light on potential cross-reactivity of GPCR ligands and will aid the design of new ligands with the desired activity profiles. In addition, we linked the ligand-based classification with a ligand-focused sequence-based classification described in literature and proved the potential of this method for de-orphanization of GPCRs.

  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. Interdiffusion in Ni-rich, Ni-Cr-Al alloys at 1100 and 1200 C. I - Diffusion paths and microstructures. II - Diffusion coefficients and predicted concentration profiles

    Science.gov (United States)

    Nesbitt, J. A.; Heckel, R. W.

    1987-01-01

    Interdiffusion in Ni-rich Ni-Cr-Al alloys is investigated experimentally after annealing at 1100 and 1200 C using gamma/gamma, gamma/gamma+beta, gamma/gamma+gamma prime, and gamma/gamma+alpha diffusion couples. The amount and location of Kirkendall porosity suggests that Al diffuses more rapidly than Cr which diffuses more rapidly than Ni in the gamma phase of Ni-Cr-Al alloys. The location and extent of maxima and minima in the concentration profiles of the diffusion couples indicate that both cross-term diffusion coefficients are positive. Measurements are also presented of the ternary interdiffusion coefficients of the gamma phase in the Ni-Cr-Al system. It is shown that the interdiffusion coefficients can be accurately predicted by using a ternary finite-difference interdiffusion model.

  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. 在基因化学的规模上识别G蛋白偶合受体(GPCR)与其配体的相互作用%Identification of G-protein coupled receptors and ligands interactions on a chemo-genomic scale

    Institute of Scientific and Technical Information of China (English)

    王亭; 段勇

    2009-01-01

    G-protein coupled receptors (GPCR) represent a class of important therapeutic targets. Seeking novel ligands as potential drugs targeting GPCRs and identifying natural ligands for orphan GPCRs have been long-standing efforts of academic and pharmaceutical industrial research. To accelerate this effort, there is a critical need for methods capable of predicting GPCR-ligand interactions on a large scale. Such methods also may help to reveal cross-pharmacology of different GPCRs in order to alleviate side effects and toxicity of potential drugs. Here we report a support vector machine (SVM)-based method for predicting GPCR-ligand interactions on a chemo-genomic scale. In this method, GPCRs were characterized by the sequence information of the transmembrane segments and ligands were represented by their chemical structural information. The application of the method to a set of known GPCR-ligand interacting pairs that included GPCRs from 28 subfamilies of the A family led to a model of GPCR-ligand interaction network. The model was able to distinguish interacting pairs from non-interacting pairs with an average 86.9% true-positive rate and 99.97% true-negative rate. Moreover, the model correctly predicted the interactions of a number of new ligands and orphan GPCRs that were chemically and phylogenetically novel to the training data set. This method is expected to be applicable to in silico high-throughput GPCR-targeting drug discovery and ligand identification at the GPCRs with unknown functions.%G蛋白偶合受体(GPCR)不仅是一类重要的生物膜蛋白,而且代表着一类重要的治疗疾病的生物把标.长期以来,学术研究界和制药工业界都在努力寻找能与这些蛋白发生相互作用的配体分子以期成为潜在药物,其中包括对那些生物功能还未知的GPCR的配体的寻找.一个能对GPcR以及可能配体的相互作用关系作出准确预报和筛选的方法显然可以加速这一过程.尤其是这个方

  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. Gene-expression Profiles Predict Survival of Patients with Lung Adenocarcinoma%基因表达谱用于肺腺癌患者的生存预测

    Institute of Scientific and Technical Information of China (English)

    赫捷; 徐崇锐

    2006-01-01

    @@ 1文献类型 诊断. 2证据水平 1b. 3文献来源 Beer DG, Kardia SL, Huang CC,et al. Geneexpression Profiles Predict Survival of Patients with Lung Adenocarcinoma [J]. Nature Medicine, 2002,8(8) :816-824.

  6. BRCA1-like profile predicts benefit of tandem high dose epirubicin-cyclophospamide-thiotepa in high risk breast cancer patients randomized in the WSG-AM01 trial.

    Science.gov (United States)

    Schouten, Philip C; Gluz, Oleg; Harbeck, Nadia; Mohrmann, Svjetlana; Diallo-Danebrock, Raihana; Pelz, Enrico; Kruizinga, Janneke; Velds, Arno; Nieuwland, Marja; Kerkhoven, Ron M; Liedtke, Cornelia; Frick, Markus; Kates, Ronald; Linn, Sabine C; Nitz, Ulrike; Marme, Frederik

    2016-08-15

    BRCA1 is an important protein in the repair of DNA double strand breaks (DSBs), which are induced by alkylating chemotherapy. A BRCA1-like DNA copy number signature derived from tumors with a BRCA1 mutation is indicative for impaired BRCA1 function and associated with good outcome after high dose (HD) and tandem HD DSB inducing chemotherapy. We investigated whether BRCA1-like status was a predictive biomarker in the WSG AM 01 trial. WSG AM 01 randomized high-risk breast cancer patients to induction (2× epirubicin-cyclophosphamide) followed by tandem HD chemotherapy with epirubicin, cyclophosphamide and thiotepa versus dose dense chemotherapy (4× epirubicin-cyclophospamide followed by 3× cyclophosphamide-methotrexate-5-fluorouracil). We generated copy number profiles for 143 tumors and classified them as being BRCA1-like or non-BRCA1-like. Twenty-six out of 143 patients were BRCA1-like. BRCA1-like status was associated with high grade and triple negative tumors. With regard to event-free-survival, the primary endpoint of the trial, patients with a BRCA1-like tumor had a hazard rate of 0.2, 95% confidence interval (CI): 0.07-0.63, p = 0.006. In the interaction analysis, the combination of BRCA1-like status and HD chemotherapy had a hazard rate of 0.19, 95% CI: 0.067-0.54, p = 0.003. Similar results were observed for overall survival. These findings suggest that BRCA1-like status is a predictor for benefit of tandem HD chemotherapy with epirubicin-thiotepa-cyclophosphamide. PMID:26946057

  7. 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.

  8. 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. PMID:24173968

  9. Temperature profiles from XBT casts from the HAMILTON as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 14 April 1975 (NODC Accession 7500661)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the HAMILTON from 14 April 1975. Data were collected by the United States Coast Guard (USCG) as part of the...

  10. Temperature profiles from XBT casts from the AMERICAN RIGEL as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 11 October 1980 (NODC Accession 8000615)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the AMERICAN RIGEL from 11 October 1980. Data were collected by the National Marine Fisheries Service (NMFS)...

  11. Temperature profiles from XBT casts from the LASH ATLANTICO as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 22 March 1978 (NODC Accession 7800644)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the LASH ATLANTICO from 22 March 1978. Data were collected by Grace Prudential Lines as part of the Marine...

  12. A novel programme to evaluate and communicate 10-year risk of CHD reduces predicted risk and improves patients' modifiable risk factor profile

    OpenAIRE

    Benner, J S; Erhardt, L.; Flammer, M; Moller, R A; Rajicic, N; Changela, K; Yunis, C; Cherry, S B; Gaciong, Z; Johnson, E. S.; Sturkenboom, M.C.J.M.; García-Puig, J; Girerd, X

    2008-01-01

    Aims We assessed whether a novel programme to evaluate/communicate predicted coronary heart disease (CHD) risk could lower patients' predicted Framingham CHD risk vs. usual care. Methods The Risk Evaluation and Communication Health Outcomes and Utilization Trial was a prospective, controlled, cluster-randomised trial in nine European countries, among patients at moderate cardiovascular risk. Following baseline assessments, physicians in the intervention group calculated patients' predicted CH...

  13. Prediction of outcome of non-small cell lung cancer patients treated with chemotherapy and bortezomib by time-course MALDI-TOF-MS serum peptide profiling

    NARCIS (Netherlands)

    Voortman, J.; Pham, T.V.; Knol, J.C.; Giaccone, G.; Jimenez, C.R.

    2009-01-01

    Background: Only a minority of patients with advanced non-small cell lung cancer (NSCLC) benefit from chemotherapy. Serum peptide profiling of NSCLC patients was performed to investigate patterns associated with treatment outcome. Using magnetic bead-assisted serum peptide capture coupled to matrix-

  14. 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.

  15. Analysis of Normal-Tumour Tissue Interaction in Tumours: Prediction of Prostate Cancer Features from the Molecular Profile of Adjacent Normal Cells

    OpenAIRE

    Trevino, Victor; Tadesse, Mahlet G.; Vannucci, Marina; Al-Shahrour, Fatima; Antczak, Philipp; Durant, Sarah; Bikfalvi, Andreas; Dopazo, Joaquin; Campbell, Moray J.; Falciani, Francesco

    2011-01-01

    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 t...

  16. Spiking the expectancy profiles:Modelling short- and long-term statistical learning of music as a process of predictive entropy reduction

    OpenAIRE

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

    2014-01-01

    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 statistical learning, causing comparatively sharper key profiles in musicians, we hypothesised that musical learning can be modelled as a process of entropy reduction through experience. Specifically, ...

  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

    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.

  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).

    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

  19. GSVD comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival.

    Directory of Open Access Journals (Sweden)

    Cheng H Lee

    Full Text Available Despite recent large-scale profiling efforts, the best prognostic predictor of glioblastoma multiforme (GBM remains the patient's age at diagnosis. We describe a global pattern of tumor-exclusive co-occurring copy-number alterations (CNAs that is correlated, possibly coordinated with GBM patients' survival and response to chemotherapy. The pattern is revealed by GSVD comparison of patient-matched but probe-independent GBM and normal aCGH datasets from The Cancer Genome Atlas (TCGA. We find that, first, the GSVD, formulated as a framework for comparatively modeling two composite datasets, removes from the pattern copy-number variations (CNVs that occur in the normal human genome (e.g., female-specific X chromosome amplification and experimental variations (e.g., in tissue batch, genomic center, hybridization date and scanner, without a-priori knowledge of these variations. Second, the pattern includes most known GBM-associated changes in chromosome numbers and focal CNAs, as well as several previously unreported CNAs in >3% of the patients. These include the biochemically putative drug target, cell cycle-regulated serine/threonine kinase-encoding TLK2, the cyclin E1-encoding CCNE1, and the Rb-binding histone demethylase-encoding KDM5A. Third, the pattern provides a better prognostic predictor than the chromosome numbers or any one focal CNA that it identifies, suggesting that the GBM survival phenotype is an outcome of its global genotype. The pattern is independent of age, and combined with age, makes a better predictor than age alone. GSVD comparison of matched profiles of a larger set of TCGA patients, inclusive of the initial set, confirms the global pattern. GSVD classification of the GBM profiles of an independent set of patients validates the prognostic contribution of the pattern.

  20. Proteome-wide Anti-HCV and Anti-HIV Antibody Profiling for Predicting and Monitoring Response to HCV Treatment in HIV Co-infected Patients

    Science.gov (United States)

    Burbelo, Peter D.; Kovacs, Joseph A.; Ching, Kathryn H.; Issa, Alexandra T.; Iadarola, Michael J.; Murphy, Alison A; Schlaak, Joerg F.; Masur, Henry; Polis, Michael A.; Kottilil, Shyam

    2010-01-01

    We quantified antibody responses to the HCV proteome that are associated with sustained virologic response (SVR) in HIV/HCV co-infected patients treated with pegylated interferon and ribavirin. Analysis of pre- and post-treatment samples revealed significant decreases in the combined anti-core, anti-E1 and anti-NS4 HCV antibody titers in those with SVR, but not in the relapsers or non-responders. Furthermore, anti-p24 HIV antibody titers inversely correlated with treatment response. These results suggest that profiling anti-HCV antibody is useful for monitoring HCV therapy especially in discriminating between relapsers and SVRs at 48 weeks. PMID:20684729

  1. 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

  2. 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)

  3. Gene Expression Profiles Predict Emergence Of Psychiatric Adverse Events In HIV/HCV Coinfected Patients On Interferon-based HCV Therapy

    Science.gov (United States)

    Rasimas, J.J; Katsounas, A; Raza, H; Murphy, A.A; Yang, J; Lempicki, R.A; Osinusi, A; Masur, H; Polis, M.A; Kottilil, S; Rosenstein, D.L

    2012-01-01

    Background The efficacy of pegylated IFN-α and ribavirin (pegIFN/RBV) in the treatment of Hepatitis C infection is limited by psychiatric adverse effects (IFN-PE). Our study examined the ability of differential gene expression patterns prior to therapy to predict emergent IFN-PE among 28 HIV/HCV co-infected patients treated with pegIFN-α2b/RBV. Methods Patients dually infected with HIV and HCV were evaluated at baseline and during treatment by board-certified psychiatrists who classified patients into 2 groups: those who developed IFN-PE and those who did not (IFN-NPE). Gene expression analysis (Affymetrix HG-U133A) was performed using PBMCs before and after initiation of treatment. ANOVA, post hoc analysis based on pair-wise comparisons and functional annotation analysis identified differentially expressed genes within and between groups. Prediction Analysis for Microarrays was used to test the predictive ability of selected genes. Results Twenty-four genes (16 up- and 8 down-regulated) that were differentially expressed at baseline in patients who subsequently developed IFN-PE compared to the IFN-NPE group showed the ability to predict IFN-PE with an accuracy of 82%. In 16 patients with IFN-PE, 135 genes (117 up-; 18 down-regulated) were significantly modulated following treatment. Of these, 10 genes have already been shown to be associated with neuropsychiatric illnesses and were significantly modulated only in patients who experienced IFN-PE. Conclusions We describe a novel molecular diagnostic biomarker panel to predict emergent IFN-PE in HIV/HCV-co-infected patients undergoing pegIFN/RBV treatment, which may improve the identification of patients at greatest risk for IFN-PE and suggest candidate therapeutic targets for preventing or treating IFN-PE. PMID:22728749

  4. Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?

    Science.gov (United States)

    Fels, Meike; Bauer, Robert; Gharabaghi, Alireza

    2015-08-01

    Objective. Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns. Approach. We assessed the perceived workload with the NASA Task Load Index in twenty-one subjects who were exposed to two different feedback tasks in a cross-over design: (i) brain-robot interface (BRI) with haptic/proprioceptive feedback of sensorimotor oscillations related to motor imagery, and (ii) control of neuromuscular activity with feedback of the electromyography (EMG) of the same hand. We also used electroencephalography to examine the cortical activation patterns beforehand in resting state and during the training session of each task. Main results. The workload profile of BRI feedback differed from EMG feedback and was particularly characterized by the experience of frustration. The frustration level was highly correlated across tasks, suggesting subject-related relevance of this workload component. Those subjects who were specifically challenged by the respective tasks could be detected by an interhemispheric alpha-band network in resting state before the training and by their sensorimotor theta-band activation pattern during the exercise. Significance. Neurophysiological profiles in resting state and during the exercise may provide task-independent workload markers for monitoring and matching participants’ ability and task difficulty of neurofeedback interventions.

  5.  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.

  6. 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.

  7. 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...... 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.......-profiling studies have only focused on the protein-coding part of the genome, however the human genome contains thousands of long non-coding RNAs (lncRNAs) and this unexplored field possesses large potential for identification of novel prognostic markers. METHODS: We evaluated lncRNA microarray data from 164...

  8. A NOVEL APPROACH FOR THE PREDICTION OF SURFACE PROFILE OF OUTGOING WORKPIECE AND THE CALCULATION OF MEAN ROLL RADIUS IN ALLOY BAR ROLLING

    Institute of Scientific and Technical Information of China (English)

    Y.G. Dong; W.Z. Zhang; J.F. Song

    2007-01-01

    In alloy bar rolling process, the component of alloyed steel influenced the spread coefficient greatly, therefore, the component influence coefficient m of different alloyed steel has been determined firstly to calculate the maximum spread. Then the curvature radius of stress free surface and the "critical point on the contact boundary" have been solved, the surface profile of outgoing workpiece has been obtained. Furthermore, the formula of the equivalent contact section area has been proposed and the mean roll radius has been calculated. The bar rolling experiment and the rigid-plastic FEM (finite element method) simulation have been carried out to verify the novel approach. Compared with experimental data and simulation results, the novel approach can be used in setting processing parameter and design of finishing groove.

  9. Thermally driven circulation in a region of complex topography: comparison of wind-profiling radar measurements and MM5 numerical predictions

    Directory of Open Access Journals (Sweden)

    L. Bianco

    2006-07-01

    Full Text Available The diurnal variation of regional wind patterns in the complex terrain of Central Italy was investigated for summer fair-weather conditions and winter time periods using a radar wind profiler. The profiler is located on a site where interaction between the complex topography and land-surface produces a variety of thermally and dynamically driven wind systems. The observational data set, collected for a period of one year, was used first to describe the diurnal evolution of thermal driven winds, second to validate the Mesoscale Model 5 (MM5 that is a three-dimensional numerical model. This type of analysis was focused on the near-surface wind observation, since thermally driven winds occur in the lower atmosphere. According to the valley wind theory expectations, the site – located on the left sidewall of the valley (looking up valley – experiences a clockwise turning with time. Same characteristics in the behavior were established in both the experimental and numerical results.

    Because the thermally driven flows can have some depth and may be influenced mainly by model errors, as a third step the analysis focuses on a subset of cases to explore four different MM5 Planetary Boundary Layer (PBL parameterizations. The reason is to test how the results are sensitive to the selected PBL parameterization, and to identify the better parameterization if it is possible. For this purpose we analysed the MM5 output for the whole PBL levels. The chosen PBL parameterizations are: 1 Gayno-Seaman; 2 Medium-Range Forecast; 3 Mellor-Yamada scheme as used in the ETA model; and 4 Blackadar.

  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. PMID:25194718

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

    Directory of Open Access Journals (Sweden)

    Jesper Grønnegaard Pedersen

    2013-12-01

    Full Text Available 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 observations with simulations that use progressively more realistic forcing relative to observed large-scale pressure gradients.Two case studies are presented. One is based on measurements from the rural site of Høvsøre in Denmark, and the other on measurements from a suburban site in Hamburg, Germany. The applied domain-scale pressure gradient and its height- and time-dependence are estimated from LIDAR measurements of the wind speed above the atmospheric boundary layer in the Høvsøre case, and from radio soundings and a network of ground-based pressure sensors in the Hamburg case.In the two case studies, 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 gradient has a significant influence on simulated wind speeds, and improves agreement with measured wind speeds, especially in the Høvsøre case. In the Hamburg case, an overly simplified specification of the height dependence of the forcing, as well as the influence of phenomena such as large-scale subsidence and advection, tend to reduce agreement with measurements, relative to the Høvsøre case. The Hamburg case illustrates that measurements of the surface

  12. 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

  13. 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.

  14. 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

  15. 石蜡包埋组织的基因表达谱分析预测局部晚期乳腺癌的化疗反应%Gene Expression Profiles in Paraffin-Embedded Core Biopsy Tissue Predict Response to Chemotherapy in Women with Locally Advanced Breast Cancer

    Institute of Scientific and Technical Information of China (English)

    徐兵河; 张绪超

    2007-01-01

    @@ 1文献类型 诊断. 2证据水平 2b. 3文献来源 Gianni L, Zambetti M, Clark K, et al. Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer [J]. J Clin Oncol, 2005,23 ( 29 ): 7265-7277.

  16. Equilibrium Beach profile measurement and sediment analysis : Mustang Island, Texas.

    OpenAIRE

    Knezek, Erick B.

    1997-01-01

    CIVINS This engineering report describes the measurement techniques and results of an equilibrium beach profile survey and sediment analysis. The main objective of the project was to obtain an accurate equilibrium beach profile at a location on Mustang Island, and to compare the actual profile to a predicted profile. The predicted profile is based on the median grain size diameter of sediment samples taken from the dune crest to approximately 4000 ft offshore. The survey was accomplished u...

  17. Profile sampling dependence of the MLAYER program.

    OpenAIRE

    Chang, Ting-Hsun

    1991-01-01

    Approved for public release; distribution is unlimited The dependence of the predictions of the MLAYER program on the set of heights at which the refractive index value are sampled from a fixed reference profile are analyzed. A refractivity profile with a four-meter evaporation duct is adopted as a reference. Two variable piecewise linear profiles of four and five segments, respectively, are used to approximate the reference profile for MLAYER computations. The sensitivities...

  18. 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.

  19. Profile video

    Science.gov (United States)

    Voglewede, Paul E.; Zampieron, Jeffrey

    2009-05-01

    For unattended persistent surveillance there is a need for a system which provides the following information: target classification, target quantity estimate, cargo presence and characterization, direction of travel, and action. Over highly bandwidth restricted links, such as Iridium, SATCOM or HF, the data rates of common techniques are too high, even after aggressive compression, to deliver the required intelligence in a timely, low power manner. We propose the following solution to this data rate problem: Profile Video. Profile video is a new technique which provides all of the required information in a very low data-rate package.

  20. 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

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

    Science.gov (United States)

    Niu, Ai-qin; Xie, Liang-jun; Wang, Hui; Zhu, Bing; Wang, Sheng-qi

    2016-01-01

    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 for the classification of selective ER-β agonists. Chemistry Development Kit extended fingerprints and MACCS fingerprint performed better in structural representation between active and inactive agonists. Conclusion These results demonstrate that combining the fingerprint and ML approaches leads to robust ER-β agonist prediction models, which are potentially applicable to the identification of selective ER-β agonists. PMID:27486309

  2. Spiking the expectancy profiles

    DEFF Research Database (Denmark)

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

    statistical learning, causing comparatively sharper key profiles in musicians, we hypothesised that musical learning can be modelled as a process of entropy reduction through experience. Specifically, implicit learning of statistical regularities allows reduction in the relative entropy (i.e. symmetrised...... 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...

  3. 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...... of a given musical style or of stimuli used in short-term experiments. Five previous probe-tone experiments with musicians and non-musicians are revisited. Exp. 1-2 used jazz, classical and hymn melodies. Exp. 3-5 collected ratings before and after exposure to 5, 15 or 400 novel melodies generated from...... a finite-state grammar using the Bohlen-Pierce scale. We find group differences in entropy corresponding to degree and relevance of musical training and within-participant decreases after short-term exposure. Thus, whereas inexperienced listeners make high-entropy predictions by default, statistical...

  4. 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.

  5. [Safety profile of dolutegravir].

    Science.gov (United States)

    Rivero, Antonio; Domingo, Pere

    2015-03-01

    Integrase inhibitors are the latest drug family to be added to the therapeutic arsenal against human immunodeficiency virus infection. Drugs in this family that do not require pharmacological boosting are characterized by a very good safety profile. The latest integrase inhibitor to be approved for use is dolutegravir. In clinical trials, dolutegravir has shown an excellent tolerability profile, both in antiretroviral-naïve and previously treated patients. Discontinuation rates due to adverse effects were 2% and 3%, respectively. The most frequent adverse effects were nausea, headache, diarrhea and sleep disturbance. A severe hypersensitivity reaction has been reported in only one patient. In patients coinfected with hepatropic viruses, the safety profile is similar to that in patients without coinfection. The lipid profile of dolutegravir is similar to that of raltegravir and superior to those of Atripla® and darunavir/ritonavir. Dolutegravir induces an early, predictable and non-progressive increase in serum creatinine of around 10% of baseline values in treatment-naïve patients and of 14% in treatment-experienced patients. This increase is due to inhibition of tubular creatinine secretion through the OCT2 receptor and does not lead to a real decrease in estimated glomerular filtration rate with algorithms that include serum creatinine. The effect of the combination of dolutegravir plus Kivexa(®) on biomarkers of bone remodeling is lower than that of Atripla(®). Dolutegravir has an excellent tolerability profile with no current evidence of long-term adverse effects. Its use is accompanied by an early and non-progressive increase in serum creatinine due to OCT2 receptor inhibition. In combination with abacavir/lamivudine, dolutegravir has a lower impact than enofovir/emtricitabine/efavirenz on bone remodelling markers. PMID:25858606

  6. 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 01 September 1972 to 05 November 1972 (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...

  7. Temperature profiles from XBT casts from the ENDEAVOR and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 14 January 1979 to 11 July 1979 (NODC Accession 7900211)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the ENDEAVOR and other platforms from 14 January 1979 to 11 July 1979. Data were collected by the National...

  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 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...

  9. 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...

  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 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...

  11. 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...

  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 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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 30 September 1978 to 05 October 1978 (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...

  20. Oceanographic Station Data and temperature profiles from XBT, CTD, and bottle casts from the ALBATROSS IV as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 13 March 1974 to 12 May 1975 (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 the ALBATROSS IV from 13 March 1974 to 12 May 1975. Data...

  1. Temperature profiles from XBT casts from the VALIANT and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 04 March 1979 to 08 April 1979 (NODC Accession 7900186)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the VALIANT and other platforms from 04 March 1979 to 08 April 1979. Data were collected by the National...

  2. Temperature profiles from XBT casts from the VALIANT and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 23 August 1979 to 17 September 1979 (NODC Accession 7900292)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the VALIANT and other platforms from 23 August 1979 to 17 September 1979. Data were collected by the...

  3. Temperature profiles from XBT casts from the VALIANT and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 16 June 1979 to 19 August 1979 (NODC Accession 7900283)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the VALIANT and other platforms from 16 June 1979 to 19 August 1979. Data were collected by the National...

  4. 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...

  5. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 23 September 1980 to 24 September 1980 (NODC Accession 8000493)

    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 23 September 1980 to 24 September 1980. Data were collected by the National Marine...

  6. Temperature profiles from XBT casts from the CARIBOU REEFER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 11 March 1978 to 12 March 1978 (NODC Accession 7800267)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the CARIBOU REEFER from 11 March 1978 to 12 March 1978. Data were collected by the National Marine Fisheries...

  7. Temperature profiles from XBT casts from the LASH ATLANTICO as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 11 March 1976 to 23 April 1976 (NODC Accession 7601067)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the LASH ATLANTICO from 11 March 1976 to 23 April 1976. Data were collected by the National Marine Fisheries...

  8. Temperature profiles from XBT casts from the DECATUR and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 30 August 1969 to 31 March 1983 (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...

  9. 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...

  10. 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...

  11. Temperature profiles from XBT casts from the DELTA ARGENTINA as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 14 November 1972 to 02 January 1973 (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...

  12. Temperature profiles from XBT casts from the DELTA ARGENTINA as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 21 September 1973 to 17 October 1973 (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....

  13. Temperature profiles from XBT casts from the SANTA CRUZ as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 30 March 1974 to 31 March 1974 (NODC Accession 7400276)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the SANTA CRUZ from 30 March 1974 to 31 March 1974. Data were collected by Grace Prudential Lines as part of...

  14. Oceanographic station, temperature profiles, meteorological, and other data from XBT and bottle casts from the OREGON II as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 13 July 1972 to 08 August 1972 (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 the OREGON II from 13 July 1972 to 08...

  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 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...

  16. Temperature profiles from XBT casts from the ALBATROSS IV as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 17 April 1984 to 02 June 1984 (NODC Accession 8400111)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the ALBATROSS IV from 17 April 1984 to 02 June 1984. 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 22 May 1978 to 23 May 1978 (NODC 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 PORT JEFFERSON as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 28 March 1978 to 29 March 1978 (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...

  19. Temperature profiles from XBT casts from the MARINE CRUISER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 27 March 1977 to 28 March 1977 (NODC Accession 7700294)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the MARINE CRUISER from 27 March 1977 to 28 March 1977. Data were collected by the National Marine Fisheries...

  20. Temperature profiles from XBT casts from the CARIBOU REEFER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 02 June 1978 to 03 June 1978 (NODC 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...

  1. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 27 September 1979 to 28 September 1979 (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...

  2. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 06 March 1981 to 07 March 1981 (NODC Accession 8100490)

    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 06 March 1981 to 07 March 1981. Data were collected by the National Marine...

  3. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 14 February 1981 to 15 February 1981 (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...

  4. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 1980-02-06 to 1980-02-07 (NODC Accession 8000031)

    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 06 February 1980 to 07 February 1980. Data were collected by the National Marine...

  5. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 18 July 1981 to 20 July 1981 (NODC Accession 8100622)

    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 18 July 1981 to 20 July 1981. Data were collected by the National Marine Fisheries...

  6. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 14 October 1980 to 15 October 1980 (NODC Accession 8000590)

    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 October 1980 to 15 October 1980. Data were collected by the National Marine...

  7. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 25 January 1980 to 26 January 1980 (NODC Accession 8100484)

    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 25 January 1980 to 26 January 1980. Data were collected by the National Marine...

  8. Temperature profiles from XBT casts from the AMERICAN RIGEL as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 31 October 1976 to 12 December 1976 (NODC Accession 7700035)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the AMERICAN RIGEL from 31 October 1976 to 12 December 1976. Data were collected by the National Marine...

  9. Temperature profiles from XBT casts from the EDGAR M. QUEENY as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 20 November 1980 to 21 November 1980 (NODC Accession 8000621)

    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 20 November 1980 to 21 November 1980. Data were collected by the National Marine...

  10. Temperature profiles from XBT casts from the AMERICAN TRADE as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 27 January 1972 to 10 February 1972 (NODC Accession 7300788)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the AMERICAN TRADE from 27 January 1972 to 10 Februay 1972. Data were collected by Moore McCormack Lines...

  11. Temperature profiles from XBT casts from the MARINE CRUISER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 16 March 1978 to 17 March 1978 (NODC Accession 7800292)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the MARINE CRUISER from 16 March 1978 to 17 March 1978. Data were collected by the National Marine Fisheries...

  12. Temperature profiles from XBT casts from the CARIBOU REEFER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 20 April 1977 to 21 April 1977 (NODC Accession 7700322)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the CARIBOU REEFER from 20 April 1977 to 21 April 1977. Data were collected by the National Marine Fisheries...

  13. Temperature profiles from XBT casts from the ALBATROSS IV and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) and WARM CORE RINGS projects from 23 September 1981 to 29 November 1982 (NODC Accession 8200241)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the ALBATROSS IV and other platforms from 23 September 1981 to 29 November 1982. Data were collected by the...

  14. Temperature profiles from XBT casts from the GULF TRADER as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 01 August 1973 to 13 September 1973 (NODC Accession 7301164)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from the GULF TRADER from 01 August 1973 to 13 September 1973. Data were collected by Lyke Brothers Lines as part...

  15. 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.

  16. VAPID: Voigt Absorption-Profile [Interstellar] Dabbler

    Science.gov (United States)

    Howarth, Ian D.

    2015-06-01

    VAPID (Voigt Absorption Profile [Interstellar] Dabbler) models interstellar absorption lines. It predicts profiles and optimizes model parameters by least-squares fitting to observed spectra. VAPID allows cloud parameters to be optimized with respect to several different data set simultaneously; those data sets may include observations of different transitions of a given species, and may have different S/N ratios and resolutions.

  17. 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.

  18. 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 episode of >30

  19. 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)

  20. Profile sampling dependence of the MLAYER program

    Science.gov (United States)

    Chang, Ting-Hsun

    1991-03-01

    The dependence of the predictions of the MLAYER program on the set of heights at which the refractive index value are sampled from a fixed reference profile are analyzed. A refractivity profile with a four-meter evaporation duct is adopted as a reference. Two variable piecewise linear profiles of four and five segments, respectively, are used to approximate the reference profile for MLAYER computations. The sensitivities of the waveguide mode location, the range attenuation rate, and the height-gain function to the changes of the piece-wise linear profiles are investigated at the frequencies 3, 6, 10, and 15 GHz. The frequency dependence of the dominant mode for one profile is also studied to investigate the fact that the sensitivity to changes in sampling point location is lower at GHz than at other frequencies. A general rule-of-thumb for the change in range attenuation rate due to a slight change in refractivity is suggested.

  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...

  2. A study of high-temperature heat pipes with multiple heat sources and sinks. I - Experimental methodology and frozen startup profiles. II - Analysis of continuum transient and steady-state experimental data with numerical predictions

    Science.gov (United States)

    Faghri, A.; Cao, Y.; Buchko, M.

    1991-01-01

    Experimental profiles for heat pipe startup from the frozen state were obtained, using a high-temperature sodium/stainless steel pipe with multiple heat sources and sinks to investigate the startup behavior of the heat pipe for various heat loads and input locations, with both low and high heat rejection rates at the condensor. The experimental results of the performance characteristics for the continuum transient and steady-state operation of the heat pipe were analyzed, and the performance limits for operation with varying heat fluxes and location are determined.

  3. 基于磨耗数据驱动模型的轮对镟修策略优化和剩余寿命预报%Optimization of the re-profiling strategy and remaining useful life prediction of wheels based on a data-driven wear model

    Institute of Scientific and Technical Information of China (English)

    王凌; 员华; 那文波; 陈锡爱; 李运堂

    2011-01-01

    Based on the wheel wear data of Guangzhou Metro, a new data-driven model of wheel wear is given in terms of the variationa of wheel diameter, flange thickness, and the re-profiling gain. A control limit policy for the wheel re-profiling decision is also proposed. According to the wheel wear model, the Monte Carlo simulation procedure of the re-profiling strategy is described in detail. Utilizing the Monte Carlo simulation, this wheel re-profiling strategy is optimized in order to minimize the expected long-run cost of wheel maintenance, and the prediction of remaining useful life of wheels is realized. The results indicate that wheels should be brought to 29-30mm when the flange is worn down to 27-27.5mm, which could reduce the expenditure associated with wheel re-profiling and extend the expected lifetime of wheels.The proposed prediction method of remaining useful life can derive the probability distribution of the remaining life of a wheel at a gven time.%基于广州地铁车辆轮对的磨耗实测数据,首先针对踏面直径和轮缘厚度两个型面参数以及镟修比例系数,给出了一种轮对磨耗的数据驱动模型.根据轮对应用要求,提出一种轮对镟修的控制限策略.在前述轮对磨耗模型的基础上,给出了该镟修策略的蒙特卡罗仿真步骤.然后应用蒙特卡罗仿真方法,实现以期望费用率最小为目标的轮对镟修策略优化,并给出轮对剩余寿命仿真预报.研究结果表明:当轮缘厚度减少到27 mm至27.5 mm时,通过镟修将轮缘厚度恢复到29mm至30mm,这样的镟修策略能降低轮对镟修期望费用率,并延长轮对期望使用寿命;提出的轮对剩余寿命仿真预报法能够给出某时刻轮对剩余寿命的概率密度分布.

  4. Support Vector Machine Based on microRNA Expression Profiles to Predict Histological Origin of Ampullary Carcinoma: Case Report of a Patient Affected From Adenocarcinoma of the Papilla of Vater With Lynch Syndrome.

    Science.gov (United States)

    Tavano, Francesca; Copetti, Massimiliano; Piepoli, Ada; Carella, Massimo; Gentile, Annamaria; Burbaci, Francesca Paola; Fontana, Andrea; De Bonis, Antonio; di Mola, Fabio Francesco; di Sebastiano, Pierluigi; Andriulli, Angelo

    2016-04-01

    Adenocarcinomas of Vater's papilla (PVAC) may originate from either the pancreatic duct or the intestinal epithelium. Conflicting data have been reported about the frequency of the 2 anatomical entities and their influence on patients' prognosis. To ascertain the anatomical origin of PVAC in a family member of a Lynch syndrome kindred, we searched for microRNA (miRNA) expression profiles on resected tumor specimens. The support vector machine was trained on our previous miRNAs expression data sets of pancreatic and colorectal tissue samples and used to classify the site of origin of the tumor in our patient. The support vector machine worked by contrasting the profiles of miRNAs in patients with pancreatic ductal and colorectal cancers to that of our patient, which was finally classified as pancreatic ductal adenocarcinoma accordingly to alterations of 55 miRNAs. The PVAC might be originated from ductal epithelium rather than from the intestinal mucosa of the papilla in the case at issue. Alteration of miR-548b-3p, miR-551a, miR-21, miR-92a, miR-let-7i, and miR-181a* emerged as potentially associated with cancer genetic susceptibility in PVAC. PMID:26954494

  5. System for diagnosis of rolling profiles of the railway vehicles

    Science.gov (United States)

    Medianu, Silviu Octavian; Rimbu, Gimi Aurelian; Lipcinski, Daniel; Popovici, Iuliu; Strambeanu, Dumitru

    2014-10-01

    A computerized system for monitoring and diagnosis (Profilograph), which is capable to predict the wheel profile evolution, was developed. The S78 and UIC-ORE types of profiles were tested, for which the wear parameters are monitored. The main parameters that characterize the wear profiles were measured and analyzed: Sh-flange height, Sd-flange thickness and qR-flange slope quota. The tests were executed on the basis of UIC norms and regulations. The diagnosis, gives technical information about the wheel profile, based on which, the following corrective mechanical actions should be taken: re-profiling, invalidation or parts replacement (in case of bandage wheel profile).

  6. 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 ...... profile and a method for the construction thereof. The profile is intended for, but not limited to, useas a wind turbine blade, an aerofoil device or as a wing profile used in the aeronautical industry....

  7. 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

  8. Pharmacology profiling of chemicals and proteins

    DEFF Research Database (Denmark)

    Kringelum, Jens Vindahl

    of pharmaceuticals, a process referred to as pharmacology profiling. Pharmacology profiling of chemical and protein based pharmaceuticals has been proven valuable in a number studies [2], however missing values in the drug-protein interaction matrix limits the profile for novel or less studied compounds....... This limitation complicates adverse effect assessment in the early drug-development phase, thus contributing to drugattrition. Prediction models offer the possibility to close these gaps and provide more complete pharmacology profiles, however improvements in performances are required for these tools to serve...... as an alternative to experimentally obtained measurements. Here I present several different tools that aid pharmacology profiling of the two main classes of pharmaceuticals; chemicals (small molecules) and proteins (biopharmaceuticals). Biopharmaceuticals have the inherent risks of eliciting an immune response due...

  9. 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.

  10. Breast Molecular Profiling and Radiotherapy Considerations.

    Science.gov (United States)

    Mahmoud, Omar; Haffty, Bruce G

    2016-01-01

    The last decade has seen major changes in the management of breast cancer. Heterogeneity regarding histology, therapeutic response, dissemination patterns, and patient outcome is evident. Molecular profiling provides an accurate tool to predict treatment outcome compared with classical clinicopathologic features. The genomic profiling unveiled the heterogeneity of breast cancer and identified distinct biologic subtypes. These advanced techniques were integrated into the clinical management; predicting systemic therapy benefit and overall survival. Utilizing genotyping to guide locoregional management decisions needs further characterization. In this chapter we will review available data on molecular classification of breast cancer, their association with locoregional outcome, their radiobiological properties and radiotherapy considerations. PMID:26987532

  11. 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.

  12. 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...

  13. 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. PMID:25391915

  14. 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

  15. Tensor GSVD of patient- and platform-matched tumor and normal DNA copy-number profiles uncovers chromosome arm-wide patterns of tumor-exclusive platform-consistent alterations encoding for cell transformation and predicting ovarian cancer survival.

    Science.gov (United States)

    Sankaranarayanan, Preethi; Schomay, Theodore E; Aiello, Katherine A; Alter, Orly

    2015-01-01

    The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD), which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV) tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs). We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient's prognosis, is independent of the tumor's stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell's immortality, and a patient's shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival. In Xq, PABPC5

  16. Tensor GSVD of patient- and platform-matched tumor and normal DNA copy-number profiles uncovers chromosome arm-wide patterns of tumor-exclusive platform-consistent alterations encoding for cell transformation and predicting ovarian cancer survival.

    Directory of Open Access Journals (Sweden)

    Preethi Sankaranarayanan

    Full Text Available The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD, which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs. We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient's prognosis, is independent of the tumor's stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell's immortality, and a patient's shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival

  17. Tensor GSVD of Patient- and Platform-Matched Tumor and Normal DNA Copy-Number Profiles Uncovers Chromosome Arm-Wide Patterns of Tumor-Exclusive Platform-Consistent Alterations Encoding for Cell Transformation and Predicting Ovarian Cancer Survival

    Science.gov (United States)

    Sankaranarayanan, Preethi; Schomay, Theodore E.; Aiello, Katherine A.; Alter, Orly

    2015-01-01

    The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD), which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV) tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs). We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient’s prognosis, is independent of the tumor’s stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell’s immortality, and a patient’s shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival. In Xq

  18. 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.

  19. Evoked emotions predict food choice.

    Science.gov (United States)

    Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry

    2014-01-01

    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. PMID:25521352

  20. 血清多肽谱预测乳腺癌新辅助化疗疗效的应用%Serum proteomic profiling predicts the susceptibility of breast cancer to neoadjuvant chemotherapy

    Institute of Scientific and Technical Information of China (English)

    汪亮; 郑智国; 祝磊; 丁小文; 孟旭莉

    2011-01-01

    Objective To analyze the serum proteomic patterns in the breast cancer patients using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) before neoadjuvant chemotherapy, build predictive model and evaluate its clinic significance. Methods Fifty patients with clinical stage Ⅱ -Ⅲ of invasive ductal carcinoma were included in this study. Serum samples were prospectively collected before 2-4 cycles of neoadjuvant chemotherapy, and were analyzed using MAL-DI-TOF-MS. According to the response evaluation criteria in solid tumors ( RECIST), patients were divided into 2 groups: drug susceptible group (31 cases, CR + PR) and drug resistant group ( 19 cases, SD +PD). Biomarker Wizard software was used to detect protein peaks significantly different between these two groups. The rule was built using two different supervised classification algorithms: K-Nearest Neighbor Clustering (KNN) and Support Vector Machines (SVM). The method with the highest accuracy was selected as the optimal predicting algorithm. Results 145 major protein peaks were detected at the molecular range of 1000 to 15 000, and 3 major protein peaks were detected significantly different between drug susceptible group and drug resistant group ( P < 0. 01 ), with Mass/Charge (m/z) values being 2651,3452, 2176 respectively. In the validation set, the supervised classification with the KNN model correctly classified most tumor responses with an accuracy rate of 84%, and sensitivity of 100%, specificity of 56%. The predictive model consisted of 9 protein peaks at Mass/Charge(m/z) 2651,3452, 2176, 1585,1682, 1908, 10 700, 3014, 8426 respectively. Conclusion MALDI-TOF-MS technique could screen related proteomic fingerprints in estimating the therapeutic effect of neoadjuvant chemotherapy.%目的 用纳米磁珠结合基质辅助激光解析离子化飞行时间质谱(MALDI-TOF-MS)技术检测乳腺癌新辅助化疗患者治疗前血清蛋白指纹图谱,筛选有疗

  1. 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 a...

  2. Successful Predictions

    Science.gov (United States)

    Pierrehumbert, R.

    2012-12-01

    In an observational science, it is not possible to test hypotheses through controlled laboratory experiments. One can test parts of the system in the lab (as is done routinely with infrared spectroscopy of greenhouse gases), but the collective behavior cannot be tested experimentally because a star or planet cannot be brought into the lab; it must, instead, itself be the lab. In the case of anthropogenic global warming, this is all too literally true, and the experiment would be quite exciting if it weren't for the unsettling fact that we and all our descendents for the forseeable future will have to continue making our home in the lab. There are nonetheless many routes though which the validity of a theory of the collective behavior can be determined. A convincing explanation must not be a"just-so" story, but must make additional predictions that can be verified against observations that were not originally used in formulating the theory. The field of Earth and planetary climate has racked up an impressive number of such predictions. I will also admit as "predictions" statements about things that happened in the past, provided that observations or proxies pinning down the past climate state were not available at the time the prediction was made. The basic prediction that burning of fossil fuels would lead to an increase of atmospheric CO2, and that this would in turn alter the Earth's energy balance so as to cause tropospheric warming, is one of the great successes of climate science. It began in the lineage of Fourier, Tyndall and Arrhenius, and was largely complete with the the radiative-convective modeling work of Manabe in the 1960's -- all well before the expected warming had progressed far enough to be observable. Similarly, long before the increase in atmospheric CO2 could be detected, Bolin formulated a carbon cycle model and used it to predict atmospheric CO2 out to the year 2000; the actual values come in at the high end of his predicted range, for

  3. Generalised empirical method for predicting surface subsidence

    International Nuclear Information System (INIS)

    Based on a simplified strata parameter, i.e. the ratio of total thickness of the strong rock beds in an overburden to the overall thickness of the overburden, a Generalised Empirical Method (GEM) is described for predicting the maximum subsidence and the shape of a complete transverse subsidence profile due to a single completely extracted longwall panel. In the method, a nomogram for predicting the maximum surface subsidence is first developed from the data collected from subsidence measurements worldwide. Then, a method is developed for predicting the shapes of complete transfer subsidence profiles for a horizontal seam and ground surface and is verified by case studies. 13 refs., 9 figs., 2 tabs

  4. 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...

  5. Energy confinement and profile consistency in TFTR

    International Nuclear Information System (INIS)

    A new regime of enhanced energy confinement has been observed on TFTR with neutral beam injection at low plasma current. It is characterized by extremely peaked electron density profiles and broad electron temperature profiles. The electron temperature profile shapes violate the concept of profile consistency in which T/sub e/(O)//sub v/ is assumed to be a tightly constrained function of q/sub a/, but they are in good agreement with a form of profile consistency based on examining the temperature profile shape outside the plasma core. The enhanced confinement regime is only obtained with a highly degassed limiter; in discharges with gas-filled limiters convective losses are calculated to dominate the edge electron power balance. Consistent with the constraint of profile consistency, global confinement is degraded in these cases. The best heating results in the enhanced confinement regime are obtained with nearly balanced co- and counter-injection. Much of the difference between balanced and co-only injection can be explained on the basis of classically predicted effects associated with plasma rotation

  6. 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.

  7. Reliability Assessment of Transformerless PV Inverters Considering Mission Profiles

    DEFF Research Database (Denmark)

    Yang, Yongheng; Wang, Huai; Blaabjerg, Frede

    2015-01-01

    reliability of three transformerless inverters under a yearly mission profile (i.e., solar irradiance and ambient temperature). The mission profile is translated to device thermal loading, which is used for lifetime prediction. Compar¬ison results reveal the lifetime mismatches among the power switching...

  8. 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

  9. 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...

  10. Community Profiles Tool

    OpenAIRE

    Institute of Public Health in Ireland (IPH)

    2014-01-01

    The Community Profiles Tool can be used to develop local health and wellbeing profiles from over 200 health-related indicators compiled from a range of data sources. Users can create tables, maps and charts of health-related indicators, and integrate this with key public health documents from the Health Well website such as relevant interventions, policies, and evidence related to each indicator.

  11. Chemical profiling of explosives

    NARCIS (Netherlands)

    G.M.H. Brust

    2014-01-01

    The primary goal of this thesis is to develop analytical methods for the chemical profiling of explosives. Current methodologies for the forensic analysis of explosives focus on identification of the explosive material. However, chemical profiling of explosives becomes increasingly important, as thi

  12. Evoked Emotions Predict Food Choice

    OpenAIRE

    Dalenberg, Jelle R.; Swetlana Gutjar; ter Horst, Gert J.; Kees de Graaf; Renken, Remco J.; Gerry Jager

    2014-01-01

    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 ...

  13. Toxicogenomics: transcription profiling for toxicology assessment.

    Science.gov (United States)

    Zhou, Tong; Chou, Jeff; Watkins, Paul B; Kaufmann, William K

    2009-01-01

    Toxicogenomics, the application of transcription profiling to toxicology, has been widely used for elucidating the molecular and cellular actions of chemicals and other environmental stressors on biological systems, predicting toxicity before any functional damages, and classification of known or new toxicants based on signatures of gene expression. The success of a toxicogenomics study depends upon close collaboration among experts in different fields, including a toxicologist or biologist, a bioinformatician, statistician, physician and, sometimes, mathematician. This review is focused on toxicogenomics studies, including transcription profiling technology, experimental design, significant gene extraction, toxicological results interpretation, potential pathway identification, database input and the applications of toxicogenomics in various fields of toxicological study. PMID:19157067

  14. 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. PMID:25635533

  15. [Research on theory and application of the interferogram of Voigt profile].

    Science.gov (United States)

    He, Jian; Zhang, Chun-min; Zhang, Qing-guo

    2007-03-01

    At normal pressure, Voigt profile (the convolution of Gaussian profile and Lorentzian profile) is the closest to actual profile, but it has no accurate expression, so in actual application many approximations are used to express Voigt profile. In the present paper, without any approximation, the authors calculate the interferogram of Voigt profile, showing that Voigt profile has no expression, but its interferogram can be calculated strictly. The transform has only one term, which is very similar to the expressions of Gaussian profile and Lorentzian profile, so any calculations of the widened profile can be finished, which doesn't have two terms as some papers predict, and difficulties will be brought. The calculation results are consistent with the experimental results. As an example in actual application, its application in atmospheric wind measurement is pointed out. This calculation has important significance in Fourier transform spectrometer of gas widened profile. PMID:17554889

  16. 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

  17. 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

  18. Predicting Post-Editor Profiles from the Translation Process

    DEFF Research Database (Denmark)

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

    2014-01-01

    Translation Process Research Database (TPR-DB). The analysis has two main research goals: We create n-gram models based on user activity and part-of-speech sequences to automatically cluster post-editors, and we use discriminative classifier models to characterize post-editors based on a diverse range...

  19. Perceived Partner Responsiveness Predicts Diurnal Cortisol Profiles 10 Years Later

    OpenAIRE

    Slatcher, Richard B.; Selcuk, Emre; Ong, Anthony D.

    2015-01-01

    Several decades of research have demonstrated that marital relationships have a powerful influence on physical health. However, surprisingly little is known about how marriage affects health—both in terms of psychological processes and biological ones. We investigated the associations between perceived partner responsiveness—the extent to which people feel understood, cared for and appreciated by their romantic partner—and diurnal cortisol over a 10-year period in a large sample of married an...

  20. Early pharmaceutical profiling to predict oral drug absorption

    DEFF Research Database (Denmark)

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

    2014-01-01

    Preformulation measurements are used to estimate the fraction absorbed in vivo for orally administered compounds and thereby allow an early evaluation of the need for enabling formulations. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary of the pharmac......Preformulation measurements are used to estimate the fraction absorbed in vivo for orally administered compounds and thereby allow an early evaluation of the need for enabling formulations. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary...

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

    DEFF Research Database (Denmark)

    Jensen, Jacob Skibsted

    2008-01-01

    de phenoliske forbindelser, som i overvejende grad stammer fra druerne. Sammenhængen mellem det phenoliske indhold i druer og det phenoliske indhold og farve egenskaberne af rødvin er dog kompleks. Frembringelsen af hurtige metoder til objektivt at analysere det phenoliske indhold af røde druer kan...... sammensætning med en multivariate fremgangsmåde. Det viste sig dog, at det var tilstrækkeligt at anvende druernes anthocyanin indhold til at prædiktere vin farve parametrene. Ydermere var det muligt at prædiktere flere vinfarve parametre fra FT-MIR spektroskopiske målinger af drueekstrakterne. Resultaterne af...

  2. Research on Designing Profiled Rod Warhead

    Institute of Scientific and Technical Information of China (English)

    Huijun Ning; Hao Wang; Cheng Zhang; Dongyang Chen; Wenjun Ruan

    2015-01-01

    A new Kinetic Energy Rod ( KER) warhead named profiled rod warhead is proposed in this paper. Based on the design of profiled rod warhead, a model of profiled rod driven by detonation is established. The detonation process is simulated by ANSYS/LS⁃DYNA, and the deployment velocity and initial flight attitude of rod are achieved. In addition, static rod deployment testing are performed to investigate the damage effect, the spatial flight attitude and deployment velocity. A satisfactory agreement is obtained by the comparison between numerical results and testing results. Meanwhile, the profiled rod studies are conducted to determine a higher penetrability compared with traditional cylindrical rods. Rigid body dynamics equations of profiled rod, which accounts for the influence of air resistance, are set up to predict the flight trajectory of long⁃distance. The results show that the profiled rod may provide a better penetration angle which still maintains a significant penetrability against projectiles when the rods move off long⁃distance range.

  3. Profiling the Mobile Customer

    DEFF Research Database (Denmark)

    Jessen, Pernille Wegener; King, Nancy J.

    2010-01-01

    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...... and legislative reform. 1 It discusses how well privacy and personal data concerns related to consumer profiling are addressed by two leading industry self-regulatory codes from the UK and the U.S. that aim to establish fair information practices for behavioural advertising by their member companies. It also...

  4. 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...

  5. 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...

  6. 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...

  7. 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.

  8. 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...

  9. 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...

  10. Country nuclear power profiles

    International Nuclear Information System (INIS)

    The preparation of Country Nuclear Power Profiles was initiated within the framework of the IAEA's programme for nuclear power plant performance assessment and feedback. It responded to a need for a database and a technical document containing a description of the energy and economic situation and the primary organizations involved in nuclear power in IAEA Member States. The task was included in the IAEA's programmes for 1993/1994 and 1995/1996. In March 1993, the IAEA organized a Technical Committee meeting to discuss the establishment of country data ''profiles'', to define the information to be included in the profiles and to review the information already available in the IAEA. Two expert meetings were convened in November 1994 to provide guidance to the IAEA on the establishment of the country nuclear profiles, on the structure and content of the profiles, and on the preparation of the publication and the electronic database. In June 1995, an Advisory Group meeting provided the IAEA with comprehensive guidance on the establishment and dissemination of an information package on industrial and organizational aspects of nuclear power to be included in the profiles. The group of experts recommended that the profiles focus on the overall economic, energy and electricity situation in the country and on its nuclear power industrial structure and organizational framework. In its first release, the compilation would cover all countries with operating power plants by the end of 1995. It was also recommended to further promote information exchange on the lessons learned from the countries engaged in nuclear programmes. For the preparation of this publication, the IAEA received contributions from the 29 countries operating nuclear power plants and Italy. A database has been implemented and the profiles are supporting programmatic needs within the IAEA; it is expected that the database will be publicly accessible in the future

  11. Histone profiles in cancer.

    Science.gov (United States)

    Riedel, Simone S; Neff, Tobias; Bernt, Kathrin M

    2015-10-01

    While DNA abnormalities have long been recognized as the cause of cancer, the contribution of chromatin is a relatively recent discovery. Excitement in the field of cancer epigenetics is driven by 3 key elements: 1. Chromatin may play an active and often critical role in controlling gene expression, DNA stability and cell identity. 2. Chromatin modifiers are frequent targets of DNA aberrations, in some cancers reaching near 100%. Particularly in cancers with low rates of DNA mutations, the key "driver" of malignancy is often a chromatin modifier. 3. Cancer-associated aberrant chromatin is amenable to pharmacologic modulation. This has sparked the rapidly expanding development of small molecules targeting chromatin modifiers or reader domains, several of which have shown promise in clinical trials. In parallel, technical advances have greatly enhanced our ability to perform comprehensive chromatin/histone profiling. Despite the discovery that distinct histone profiles are associated with prognostic subgroups, and in some instances may point towards an underlying aberration that can be targeted, histone profiling has not entered clinical diagnostics. Even eligibility for clinical trials targeting chromatin hinges on traditional histologic or DNA-based molecular criteria rather than chromatin profiles. This review will give an overview of the philosophical debate around the role of histones in controlling or modulating gene expression and discuss the most common techniques for histone profiling. In addition, we will provide prominent examples of aberrantly expressed or mutated chromatin modifiers that result in either globally or locally aberrant histone profiles, and that may be promising therapeutic targets.

  12. 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.

  13. Relaxation of Surface Profiles by Evaporation Dynamics

    OpenAIRE

    Hager, Johannes

    1997-01-01

    We present simulations of the relaxation towards equilibrium of one dimensional steps and sinusoidal grooves imprinted on a surface below its roughening transition. We use a generalization of the hypercube stacking model of Forrest and Tang, that allows for temperature dependent next-nearest-neighbor interactions. For the step geometry the results at T=0 agree well with the t^(1/4) prediction of continuum theory for the spreading of the step. In the case of periodic profiles we modify the mob...

  14. Environmental profile analysis

    International Nuclear Information System (INIS)

    The Institute for Ecological Chemistry of the GSF in Munich, West Germany, developed a test system to evaluate the potential environmental hazard of chemicals. This so-called Environmental Profile Analysis is a test system for the screening of chemicals for their environmental behavior. The test system consists of the following five tests: (1) bio-accumulation in algae; (2) bio-accumulation in fish; (3) retention, dispersion, and excretion in rats (warm-blooded animals); (4) degradation, transformation and accumulation in activated sludge (microbial process); (5) photomineralization (abiotic process). The test system involves the use of radio-labeled test materials. This allows the use of scintillation counting as the universal analytical method and avoids the significant analytical limitations other methods are faced with. Also, the very sensitive method of scintillation counting allows the detection of traces of test materials and/or transformation products. Difficulties and risks of the use of radioactive materials can be eliminated by following strictly the procedures of the guidelines. A series of more than one hundred compounds belonging to widely different classes of compounds and displaying widely different application patterns and physicochemical properties has been tested so far. The test data for all the parameters of the five tests can be graphically presented creating a profile of parameters. The profile of the unknown materials is compared with the profile of compounds which are known to impose a burden on the environment. Potentially hazardous material is identified by similarities of the profiles and additional investigation should be performed. Through this comparison of profiles, the ecotoxicological profile analysis allows a quick recognition of potentially hazardous chemicals

  15. 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 ...

  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. Profile Based Information Retrieval

    Directory of Open Access Journals (Sweden)

    Athar shaikh,

    2011-04-01

    Full Text Available This paper present Profile Based information retrieval system(PBIR. This system provide the user to register with it and based on the users registered areas of interest the system searches the related and efficient information form the world wide web using the technique of web text mining and arranges the unstructured data into structured format and present it to the user. This system also stores the previously searched data and based on users areas of interest and rating awarded to the interest by the user his profile will be updated at particular scheduled time.

  20. Venture profile analysis.

    Science.gov (United States)

    Murphy, R F

    1985-01-01

    Imposed restrictions on inpatient revenue have encouraged hospitals to seek alternative sources of revenue through diversification. The venture profile analysis is a low-cost, orderly process to help hospitals plan for service diversification. Potential business ventures are assigned a weighted score based on nine evaluation criteria. Potential business ventures with high relative scores should be those opportunities with the greater prospects of success and those deserving of serious consideration by the hospital. The format of the profile facilitates active involvement of board members in the decision making process and prudent management of risk in market-based strategic planning. PMID:10300483

  1. Culinary Arts Profile.

    Science.gov (United States)

    Missouri Univ., Columbia. Instructional Materials Lab.

    This chart is intended for use in documenting the fact that a student participating in a culinary arts program has achieved the performance standards specified in the Missouri Competency Profile for culinary arts. The chart includes space for recording basic student and instructor information and the student's on-the-job training and work…

  2. Low profile thermite igniter

    Science.gov (United States)

    Halcomb, Danny L.; Mohler, Jonathan H.

    1991-03-05

    A thermite igniter/heat source comprising a housing, high-density thermite, and low-density thermite. The housing has a relatively low profile and can focus energy by means of a torch-like ejection of hot reaction products and is externally ignitable.

  3. Origins of metabolic profiling.

    Science.gov (United States)

    Robinson, Arthur B; Robinson, Noah E

    2011-01-01

    Quantitative metabolic profiling originated as a 10-year project carried out between 1968 and 1978 in California. It was hypothesized and then demonstrated that quantitative analysis of a large number of metabolites - selected by analytical convenience and evaluated by computerized pattern recognition - could serve as a useful method for the quantitative measurement of human health. Using chromatographic and mass spectrometric methods to measure between 50 and 200 metabolites in more than 15,000 human specimens, statistically significant and diagnostically useful profiles for several human diseases and for other systematic variables including age, diet, fasting, sex, and other variables were demonstrated. It was also shown that genetically distinct metabolic profiles for each individual are present in both newborn infants and adults. In the course of this work, the many practical and conceptual problems involved in sampling, analysis, evaluation of results, and medical use of quantitative metabolic profiling were considered and, for the most part, solved. This article is an account of that research project. PMID:21207281

  4. 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…

  5. 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,…

  6. Prediction of burnout. Chapter 14

    International Nuclear Information System (INIS)

    A broad survey is made of the effect on burnout heat flux of various system parameters to give the reader a better initial idea of the significance of changes in individual parameters. A detailed survey is then made of various correlation equations for predicting burnout for steam -water in uniformly heated tubes, annuli, rectangular channels and rod clusters, giving details of recommended equations. Finally comments are made on the influence of heat-flux profile and swirl flow on burnout, and on the definition of dryout margin. (author)

  7. 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.

  8. Simultaneous measurement of liquid velocity and interface profiles of horizontal duct wavy flow by ultrasonic velocity profile meter

    International Nuclear Information System (INIS)

    A simultaneous measurement of the liquid velocity and interface profiles was performed for stratified-smooth and wavy flows in a horizontal duct using a ultrasonic velocity profile (UVP) meter. The influences of the reflections of ultrasonic pulses at the gas-liquid interface and channel bottom were reduced by using an absorbent for the ultrasonic pulses on the duct bottom wall and optimization of the liquid level and time interval between pulses. For a smooth-stratified flow, good comparison was obtained with a velocity profile obtained by particle tracking velocimetry (PTV) for video pictures taken simultaneously at the UVP measurement. Polystyrene beads were used as the reflector and tracers respectively, for the UVP and PTV measurements. The velocity profiles measured for a wavy flow with periodically-generated interfacial waves agreed well with the theoretical prediction for solitary waves. Turbulence component appeared in the velocity profiles of both the smooth-stratified and wavy flows. (orig.)

  9. Temperature profiles of impacts

    Energy Technology Data Exchange (ETDEWEB)

    Canavan, G.H.

    1997-05-01

    Similarity solutions determine the profiles of density and temperature from impacts, which determine the scaling of the temperature and optical depth on material parameters, time, screening, and impactor size. This note uses scaling results derived earlier for the growth, size, and temperature produced by impacts to discuss the radial temperature profiles they produce. While the plasmas cool in milliseconds, they offer unique information about the thermodynamic state and material properties of the target material. The brightness temperature can be estimated from known two-dimensional similarity solutions. Regions close to unit optical thickness contribute effectively to the radiation, hence, they determine the plasma brightness temperature. The estimates of temperature as a function of time can be combined with the estimates of the exit hole size to estimate the total observable signal, which should be readily observable from distances of hundreds of kilometers.

  10. Cinnarizine: Comprehensive Profile.

    Science.gov (United States)

    Haress, Nadia G

    2015-01-01

    Cinnarizine is a piperazine derivative with antihistaminic, antiserotonergic, antidopaminergic, and calcium channel-blocking activities. A comprehensive profile was performed on cinnarizine including its description and the different methods of analysis. The 1H NMR and 13C one- and two-dimensional NMR methods were used. In addition, infrared and mass spectral analyses were performed which all confirmed the structure of cinnarizine. PMID:26051684

  11. In search of the entrepreneurial profile(s) in Luxembourg

    OpenAIRE

    Dimaria, Charles-Henri; Ries, Jean

    2006-01-01

    This article tries to characterize the profiles of entrepreneurs in Luxembourg. First, theoretical benchmark definitions of entrepreneur and entrepreneurship are surveyed and descriptive statistics are computed to define an average profile of the entrepreneur using a new and original dataset for Luxembourg. Then, using the Factors of Business Success survey (FoBS), clustering techniques are used to determine potential entrepreneurial profiles in Luxembourg.

  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. A profile of profiles: A meta-analysis of the nomological net of commitment profiles.

    Science.gov (United States)

    Kabins, Adam H; Xu, Xiaohong; Bergman, Mindy E; Berry, Christopher M; Willson, Victor L

    2016-06-01

    Although the majority of empirical commitment research has adopted a variable-centered approach, the person-centered or profiles approach is gaining traction. One challenge in the commitment profiles literature is that names are attached to profiles based on the within-study comparison among profiles and their relative levels and shapes. Thus, it is possible that different studies name the same profiles differently or different profiles similarly because of the context of the other profiles in the study. A meta-analytic approach, combined with multilevel latent profile analysis (LPA) that accounts for both within- and between-sample variability, is used in this study to examine the antecedents and outcomes of commitment profiles. This helps solve the naming problem by examining multiple data sets (K = 40) with a large sample (N = 16,052), obtained by contacting commitment researchers who voluntarily supplied primary data to bring further consensus about the phenomenology of profiles. LPA results revealed 5 profiles (Low, Moderate, AC-dominant, AC/NC-dominant, and High). Meta-analytic results revealed that high levels of bases of commitment were associated with value-based profiles whereas low levels were associated with weak commitment profiles. Additionally, value-based profiles were associated with older, married, and less educated participants than the weak commitment profiles. Regarding outcomes of commitment, profiles were found to significantly relate to focal behaviors (e.g., performance, tenure, and turnover) and discretionary behaviors (e.g., organizational citizenship behaviors). Value-based profiles were found to have higher levels of both focal and discretionary behaviors for all analyses. Implications for the commitment and profile literature are discussed. (PsycINFO Database Record PMID:26949821

  14. 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......-to-structure prediction methods....

  15. 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...

  16. 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...

  17. 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...

  18. Oceanographic Station Data and temperature profiles from CTD, XBT, and bottle casts from the ALBATROSS IV and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) from 01 January 1973 to 29 March 1973 (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 the ALBATROSS IV and other platforms from 01 January 1973 to...

  19. Temperature profile data from XBT casts from the ATLANTIS II and other platforms from the North Atlantic Ocean as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP), WARM CORE RINGS, and other projects from 22 April 1978 to 15 October 1982 (NODC Accession 8200237)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles and other data were collected from XBT casts from ATLANTIS II and other platforms in the Atlantic Ocean from 22 April 1978 to 15 October 1982....

  20. 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...

  1. Physical, temperature profile, and other data from CTD and XBT casts from the L. MCCORMICK and other platforms as part of the Marine Resources Monitoring, Assessment and Prediction (MARMAP) project from 14 September 1981 to 05 March 1983 (NODC Accession 8300038)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical, temperature profile, and other data were collected from CTD and XBT casts from the L. MCCORMICK and other platforms from 14 September 1981 to 05 March...

  2. 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 and offe......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...... developed metastasis and 82 primary breast tumors from patients who remained metastasis-free, by microarray gene expression profiling. We employed a nested case-control design, where samples were matched, in this study one-to-one, to exclude differences in gene expression based on tumor type, tumor size...

  3. 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.

  4. On the potential use of radar-derived information in operational numerical weather prediction

    Science.gov (United States)

    Mcpherson, R. D.

    1986-01-01

    Estimates of requirements likely to be levied on a new observing system for mesoscale meteonology are given. Potential observing systems for mesoscale numerical weather prediction are discussed. Thermodynamic profiler radiometers, infrared radiometer atmospheric sounders, Doppler radar wind profilers and surveillance radar, and moisture profilers are among the instruments described.

  5. 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.

  6. [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.

  7. [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. PMID:22512162

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

    Directory of Open Access Journals (Sweden)

    Karacali Bilge

    2007-10-01

    Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

  14. The architectural network for protein secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Anindya Sundar Panja

    2016-07-01

    Full Text Available Over the past 25 years, the accuracy of proteins secondary structure prediction has improved substantially. Recently evolutionary information taken from the deviation of proteins in some structural family have again enhance prediction accuracy for all these residues predicted correctly is in one of the three sates helix, strands and others . The new methods developed over the past few years may be interesting in context of improvements which is achieved through combination of the existing methods. Evolutionary divergences profile posses’ adequate information to improve protein secondary structure prediction accuracy. These profiles can also able to correctly predict long stretches of identical residues in other secondary structure. This sequence structure relationship may help to help to developed tool which can efficiently predict the protein secondary structure from its amino acid sequence

  15. 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.

  16. Analysis of superfamily specific profile-profile recognition accuracy

    Directory of Open Access Journals (Sweden)

    Saqi Mansoor AS

    2004-12-01

    Full Text Available Abstract Background Annotation of sequences that share little similarity to sequences of known function remains a major obstacle in genome annotation. Some of the best methods of detecting remote relationships between protein sequences are based on matching sequence profiles. We analyse the superfamily specific performance of sequence profile-profile matching. Our benchmark consists of a set of 16 protein superfamilies that are highly diverse at the sequence level. We relate the performance to the number of sequences in the profiles, the profile diversity and the extent of structural conservation in the superfamily. Results The performance varies greatly between superfamilies with the truncated receiver operating characteristic, ROC10, varying from 0.95 down to 0.01. These large differences persist even when the profiles are trimmed to approximately the same level of diversity. Conclusions Although the number of sequences in the profile (profile width and degree of sequence variation within positions in the profile (profile diversity contribute to accurate detection there are other superfamily specific factors.

  17. Elucidating polypharmacological mechanisms of polyphenols by gene module profile analysis.

    Science.gov (United States)

    Li, Bin; Xiong, Min; Zhang, Hong-Yu

    2014-01-01

    Due to the diverse medicinal effects, polyphenols are among the most intensively studied natural products. However, it is a great challenge to elucidate the polypharmacological mechanisms of polyphenols. To address this challenge, we establish a method for identifying multiple targets of chemical agents through analyzing the module profiles of gene expression upon chemical treatments. By using FABIA algorithm, we have performed a biclustering analysis of gene expression profiles derived from Connectivity Map (cMap), and clustered the profiles into 49 gene modules. This allowed us to define a 49 dimensional binary vector to characterize the gene module profiles, by which we can compare the expression profiles for each pair of chemical agents with Tanimoto coefficient. For the agent pairs with similar gene expression profiles, we can predict the target of one agent from the other. Drug target enrichment analysis indicated that this method is efficient to predict the multiple targets of chemical agents. By using this method, we identify 148 targets for 20 polyphenols derived from cMap. A large part of the targets are validated by experimental observations. The results show that the medicinal effects of polyphenols are far beyond their well-known antioxidant activities. This method is also applicable to dissect the polypharmacology of other natural products. PMID:24968267

  18. Elucidating Polypharmacological Mechanisms of Polyphenols by Gene Module Profile Analysis

    Directory of Open Access Journals (Sweden)

    Bin Li

    2014-06-01

    Full Text Available Due to the diverse medicinal effects, polyphenols are among the most intensively studied natural products. However, it is a great challenge to elucidate the polypharmacological mechanisms of polyphenols. To address this challenge, we establish a method for identifying multiple targets of chemical agents through analyzing the module profiles of gene expression upon chemical treatments. By using FABIA algorithm, we have performed a biclustering analysis of gene expression profiles derived from Connectivity Map (cMap, and clustered the profiles into 49 gene modules. This allowed us to define a 49 dimensional binary vector to characterize the gene module profiles, by which we can compare the expression profiles for each pair of chemical agents with Tanimoto coefficient. For the agent pairs with similar gene expression profiles, we can predict the target of one agent from the other. Drug target enrichment analysis indicated that this method is efficient to predict the multiple targets of chemical agents. By using this method, we identify 148 targets for 20 polyphenols derived from cMap. A large part of the targets are validated by experimental observations. The results show that the medicinal effects of polyphenols are far beyond their well-known antioxidant activities. This method is also applicable to dissect the polypharmacology of other natural products.

  19. 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.

  20. PREDICTING TURBINE STAGE PERFORMANCE

    Science.gov (United States)

    Boyle, R. J.

    1994-01-01

    This program was developed to predict turbine stage performance taking into account the effects of complex passage geometries. The method uses a quasi-3D inviscid-flow analysis iteratively coupled to calculated losses so that changes in losses result in changes in the flow distribution. In this manner the effects of both the geometry on the flow distribution and the flow distribution on losses are accounted for. The flow may be subsonic or shock-free transonic. The blade row may be fixed or rotating, and the blades may be twisted and leaned. This program has been applied to axial and radial turbines, and is helpful in the analysis of mixed flow machines. This program is a combination of the flow analysis programs MERIDL and TSONIC coupled to the boundary layer program BLAYER. The subsonic flow solution is obtained by a finite difference, stream function analysis. Transonic blade-to-blade solutions are obtained using information from the finite difference, stream function solution with a reduced flow factor. Upstream and downstream flow variables may vary from hub to shroud and provision is made to correct for loss of stagnation pressure. Boundary layer analyses are made to determine profile and end-wall friction losses. Empirical loss models are used to account for incidence, secondary flow, disc windage, and clearance losses. The total losses are then used to calculate stator, rotor, and stage efficiency. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370/3033 under TSS with a central memory requirement of approximately 4.5 Megs of 8 bit bytes. This program was developed in 1985.

  1. Infant Motor Profile and cerebral palsy : promising associations

    NARCIS (Netherlands)

    Heineman, Kirsten R.; Bos, Arend F.; Hadders-Algra, Mijna

    2011-01-01

    AIM The Infant Motor Profile (IMP) is a novel qualitative assessment of motor behaviour in infancy. The aim of this study was to determine whether IMP scores throughout infancy differ between children with and without cerebral palsy (CP) at 18 months. Furthermore, we evaluated the predictive ability

  2. Nonmonotone Saturation Profiles for Hydrostatic Equilibrium in Homogeneous Porous Media

    NARCIS (Netherlands)

    Hilfer, R.; Doster, F.; Zegeling, P.A.

    2012-01-01

    Nonmonotonic saturation profiles (saturation overshoot) occur as travelling waves in gravity driven fingering. They seem important for preferential flow mechanisms and have found much attention recently. Here, we predict them even for hydrostatic equilibrium when all velocities vanish. We suggest th

  3. Short-term prediction of local wind conditions

    DEFF Research Database (Denmark)

    Landberg, L.; Watson, S.J.

    1994-01-01

    Using Numerical Weather Prediction (NWP) models it has been shown that they, combined with models (either physical or statistical) taking local effects into account, can be used to predict the wind locally better than the models commonly used today (as eg persistence). By ''local'' is meant at one...... law, and the logarithmic wind profile. The predictions are made up to 36 hours ahead. The model is tested on data from 50 meteorological stations scattered all over Europe....

  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. Modelling of Temperature Profiles and Transport Scaling in Auxiliary Heated Tokamaks

    DEFF Research Database (Denmark)

    Callen, J.D.; Christiansen, J.P.; Cordey, J.G.;

    1987-01-01

    in detail: (i) a heat pinch or excess temperature gradient model with constant coefficients; and (ii) a non-linear heat diffusion coefficient (χ) model. Both models predict weak (lesssim20%) temperature profile responses to physically relevant changes in the heat deposition profile – primarily because...... the temperature profile is a double integral of the heating profile. The model predictions are shown to agree with JET data for a variety of heating profiles ranging from peaked on-axis through approximately flat (NBI at high density) to localized off-axis (ICRH). The modest temperature profile responses......-mode) scaling with input power, . The constant heat pinch or excess temperature gradient model leads to the offset linear law for the total stored energy W with Pin, W = τinc Pin + W(0), which describes JET auxiliary heating data quite well. It also provides definitions for the incremental energy confinement...

  6. The Ly and Ly profiles in solar prominences and prominence fine structure

    CERN Document Server

    Vial, J -C; Ajabshirizadeh, A

    2007-01-01

    We present the first combined Ly and Ly profiles in solar prominences obtained by the SOHO/SUMER instrument and discuss their important spatial variability with respect to predictions from 1D and multithread models.

  7. Nonparametric bootstrap prediction

    OpenAIRE

    Fushiki, Tadayoshi; Komaki, Fumiyasu; Aihara, Kazuyuki

    2005-01-01

    Ensemble learning has recently been intensively studied in the field of machine learning. `Bagging' is a method of ensemble learning and uses bootstrap data to construct various predictors. The required prediction is then obtained by averaging the predictors. Harris proposed using this technique with the parametric bootstrap predictive distribution to construct predictive distributions, and showed that the parametric bootstrap predictive distribution gives asymptotically better prediction tha...

  8. 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.

  9. 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

  10. 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...

  11. Dielectric responses of graded composites having generalized gradation profiles

    Institute of Scientific and Technical Information of China (English)

    Wei En-Bo; Gu Guo-Qing; Yu Kin-Wah

    2006-01-01

    Under an external uniform electric field, the dielectric response of graded cylindrical composites having generalized dielectric profile inclusions is investigated. The generalized dielectric profile of graded cylindrical inclusion is expressed in the form,εi(γ) = c(b +γ)κeβγ where γ is the radial variable of the cylindrical inclusions and c,b,κand β are parameters. The local potential solution of generalized dielectric profile graded composites is derived by means of the power series method and the effective dielectric response is predicted in the dilute limit.Moreover,from the result of generalized profile, the analytical solutions of local potentials and the effective responses of graded composites having three cases of dielectric profiles,I.e.,the exponential profile εi(γ) = ceβγ, the general power law protile εi(γ) = c (b +γ)κ and the profileεi (γ) = cγκeβγ, are sorted out,respectively.In the dilute limit,our exact results are used to test the validity of differential effective dipole approximation (DEDA) for estimating the effective response of graded cylindrical composites,and it is shown that the DEDA is in excellent agreement with the exact result.

  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. Optical measurement of slurry concentration profile in a concurrent-flow gas-slurry column

    International Nuclear Information System (INIS)

    An optical technique is described which allows the measurement of steady-state slurry concentration profile in a slender concurrent-flow gas-slurry bubble column. The optically measured profile is compared with that predicted by a previously reported semiempirical dispersion model. Qualitative agreement is observed between them, and the reliability of the technique is supported by additional experimental data

  14. Swarm Terrain Profiler Robotics System

    OpenAIRE

    Vivek Kumar; Dr. Praveen Kant Pandey; Dr. Sandeep Sharma

    2016-01-01

    An autonomous terrain profiling multi-robotic system is developed which uses ultrasonic technology to determine terrain profile including environmental pollution level detection. The system is deployed for both airy and aquatic medium. In addition to only terrain profiling under airy medium, the system exploits temperature and turbidity analysis for aquatic environment too. The multi-robot system is further extended to swarm intelligence system and correspondingly simulated results have been ...

  15. 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.

  16. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions. PMID:27286683

  17. 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

  18. USGIN ISO metadata profile

    Science.gov (United States)

    Richard, S. M.

    2011-12-01

    The USGIN project has drafted and is using a specification for use of ISO 19115/19/39 metadata, recommendations for simple metadata content, and a proposal for a URI scheme to identify resources using resolvable http URI's(see http://lab.usgin.org/usgin-profiles). The principal target use case is a catalog in which resources can be registered and described by data providers for discovery by users. We are currently using the ESRI Geoportal (Open Source), with configuration files for the USGIN profile. The metadata offered by the catalog must provide sufficient content to guide search engines to locate requested resources, to describe the resource content, provenance, and quality so users can determine if the resource will serve for intended usage, and finally to enable human users and sofware clients to obtain or access the resource. In order to achieve an operational federated catalog system, provisions in the ISO specification must be restricted and usage clarified to reduce the heterogeneity of 'standard' metadata and service implementations such that a single client can search against different catalogs, and the metadata returned by catalogs can be parsed reliably to locate required information. Usage of the complex ISO 19139 XML schema allows for a great deal of structured metadata content, but the heterogenity in approaches to content encoding has hampered development of sophisticated client software that can take advantage of the rich metadata; the lack of such clients in turn reduces motivation for metadata producers to produce content-rich metadata. If the only significant use of the detailed, structured metadata is to format into text for people to read, then the detailed information could be put in free text elements and be just as useful. In order for complex metadata encoding and content to be useful, there must be clear and unambiguous conventions on the encoding that are utilized by the community that wishes to take advantage of advanced metadata

  19. Profiles of sibling bullying.

    Science.gov (United States)

    Skinner, Jessica A; Kowalski, Robin M

    2013-05-01

    Considerable research has been done on childhood bullying, including its antecedents and consequences. Yet, with all of the attention on bullying, particularly school bullying, sibling bullying has been vastly overlooked. Sibling bullying is a type of violence prevalent in the lives of most children, but little is known about the phenomenon. The purpose of this study was to profile sibling bullying by examining prevalence rates, the extent to which siblings perceive sibling bullying to be normative, and victim-perpetrator differences in perceptions of sibling bullying. Twenty-seven sibling pairs who wrote stories about personal experiences of sibling bullying and victimization completed questionnaires about these experiences and responded to their sibling partners' stories. Of the siblings surveyed, 78% reported being bullied by their sibling and 85% reported bullying their sibling during their childhood. This is far greater than published statistics on peer bullying. Not surprisingly, victims viewed sibling bullying more negatively than perpetrators. Sadly, there was a norm of acceptance of sibling bullying among most of the sibling pairs. Practical implications are discussed. PMID:23348680

  20. Molecular profiling of chordoma

    Science.gov (United States)

    SCHEIL-BERTRAM, STEFANIE; KAPPLER, ROLAND; VON BAER, ALEXANDRA; HARTWIG, ERICH; SARKAR, MICHAEL; SERRA, MASSIMO; BRÜDERLEIN, SILKE; WESTHOFF, BETTINA; MELZNER, INGO; BASSALY, BIRGIT; HERMS, JOCHEN; HUGO, HEINZ-HERMANN; SCHULTE, MICHAEL; MÖLLER, PETER

    2014-01-01

    The molecular basis of chordoma is still poorly understood, particularly with respect to differentially expressed genes involved in the primary origin of chordoma. In this study, therefore, we compared the transcriptional expression profile of one sacral chordoma recurrence, two chordoma cell lines (U-CH1 and U-CH2) and one chondrosarcoma cell line (U-CS2) with vertebral disc using a high-density oligonucleotide array. The expression of 65 genes whose mRNA levels differed significantly (p<0.001; ≥6-fold change) between chordoma and control (vertebral disc) was identified. Genes with increased expression in chordoma compared to control and chondrosarcoma were most frequently located on chromosomes 2 (11%), 5 (8%), 1 and 7 (each 6%), whereas interphase cytogenetics of 33 chordomas demonstrated gains of chromosomal material most prevalent on 7q (42%), 12q (21%), 17q (21%), 20q (27%) and 22q (21%). The microarray data were confirmed for selected genes by quantitative polymerase chain reaction analysis. As in other studies, we showed the expression of brachyury. We demonstrate the expression of new potential candidates for chordoma tumorigenesis, such as CD24, ECRG4, RARRES2, IGFBP2, RAP1, HAI2, RAB38, osteopontin, GalNAc-T3, VAMP8 and others. Thus, we identified and validated a set of interesting candidate genes whose differential expression likely plays a role in chordoma. PMID:24452533

  1. 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.

  2. 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.

  3. 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

  4. 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 Italy. 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...

  5. 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 Turkey. 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. Ec...

  6. 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 Equatorial Guinea. 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 const...

  7. 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 Sri Lanka. 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....

  8. 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.

  9. 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 Gabon. 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...

  10. 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 Lithuania. 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....

  11. 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 Thailand. 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. ...

  12. 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 Malaysia. 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. ...

  13. Commitment Profiles and Employee Turnover

    Science.gov (United States)

    Stanley, Laura; Vandenberghe, Christian; Vandenberg, Robert; Bentein, Kathleen

    2013-01-01

    We examined how affective (AC), normative (NC), perceived sacrifice (PS), and few alternatives (FA) commitments combine to form profiles and determine turnover intention and turnover. We theorized that three mechanisms account for how profiles operate, i.e., the degree to which membership is internally regulated, the perceived desirability and…

  14. Sensitivity of the urban airshed model to mixing height profiles

    Energy Technology Data Exchange (ETDEWEB)

    Rao, S.T.; Sistla, G.; Ku, J.Y.; Zhou, N.; Hao, W. [New York State Dept. of Environmental Conservation, Albany, NY (United States)

    1994-12-31

    The United States Environmental Protection Agency (USEPA) has recommended the use of the Urban Airshed Model (UAM), a grid-based photochemical model, for regulatory applications. One of the important parameters in applications of the UAM is the height of the mixed layer or the diffusion break. In this study, we examine the sensitivity of the UAM-predicted ozone concentrations to (a) a spatially invariant diurnal mixing height profile, and (b) a spatially varying diurnal mixing height profile for a high ozone episode of July 1988 for the New York Airshed. The 1985/88 emissions inventory used in the EPA`s Regional Oxidant Modeling simulations has been regridded for this study. Preliminary results suggest that the spatially varying case yields a higher peak ozone concentrations compared to the spatially invariant mixing height simulation, with differences in the peak ozone ranging from a few ppb to about 40 ppb for the days simulated. These differences are attributed to the differences in the shape of the mixing height profiles and its rate of growth during the morning hours when peak emissions are injected into the atmosphere. Examination of the impact of emissions reductions associated with these two mixing height profiles indicates that NO{sub x}-focussed controls provide a greater change in the predicted ozone peak under spatially invariant mixing heights than under the spatially varying mixing height profile. On the other hand, VOC-focussed controls provide a greater change in the predicted peak ozone levels under spatially varying mixing heights than under the spatially invariant mixing height profile.

  15. 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.

  16. Plasma long-chain free fatty acids predict mammalian longevity

    OpenAIRE

    Mariona Jové; Alba Naudí; Juan Carlos Aledo; Rosanna Cabré; Victoria Ayala; Manuel Portero-Otin; Gustavo Barja; Reinald Pamplona

    2013-01-01

    Membrane lipid composition is an important correlate of the rate of aging of animals and, therefore, the determination of their longevity. In the present work, the use of high-throughput technologies allowed us to determine the plasma lipidomic profile of 11 mammalian species ranging in maximum longevity from 3.5 to 120 years. The non-targeted approach revealed a specie-specific lipidomic profile that accurately predicts the animal longevity. The regression analysis between lipid species and ...

  17. Nonlinear Combustion Instability Prediction

    Science.gov (United States)

    Flandro, Gary

    2010-01-01

    The liquid rocket engine stability prediction software (LCI) predicts combustion stability of systems using LOX-LH2 propellants. Both longitudinal and transverse mode stability characteristics are calculated. This software has the unique feature of being able to predict system limit amplitude.

  18. 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…

  19. Preclinical profile of cabazitaxel.

    Science.gov (United States)

    Vrignaud, Patricia; Semiond, Dorothée; Benning, Veronique; Beys, Eric; Bouchard, Hervé; Gupta, Sunil

    2014-01-01

    First-generation taxanes have changed the treatment paradigm for a wide variety of cancers, but innate or acquired resistance frequently limits their use. Cabazitaxel is a novel second-generation taxane developed to overcome such resistance. In vitro, cabazitaxel showed similar antiproliferative activity to docetaxel in taxane-sensitive cell lines and markedly greater activity in cell lines resistant to taxanes. In vivo, cabazitaxel demonstrated excellent antitumor activity in a broad spectrum of docetaxel-sensitive tumor xenografts, including a castration-resistant prostate tumor xenograft, HID28, where cabazitaxel exhibited greater efficacy than docetaxel. Importantly, cabazitaxel was also active against tumors with innate or acquired resistance to docetaxel, suggesting therapeutic potential for patients progressing following taxane treatment and those with docetaxel-refractory tumors. In patients with tumors of the central nervous system (CNS), and in patients with pediatric tumors, therapeutic success with first-generation taxanes has been limited. Cabazitaxel demonstrated greater antitumor activity than docetaxel in xenograft models of CNS disease and pediatric tumors, suggesting potential clinical utility in these special patient populations. Based on therapeutic synergism observed in an in vivo tumor model, cabazitaxel is also being investigated clinically in combination with cisplatin. Nonclinical evaluation of the safety of cabazitaxel in a range of animal species showed largely reversible changes in the bone marrow, lymphoid system, gastrointestinal tract, and male reproductive system. Preclinical safety signals of cabazitaxel were consistent with the previously reported safety profiles of paclitaxel and docetaxel. Clinical observations with cabazitaxel were consistent with preclinical results, and cabazitaxel is indicated, in combination with prednisone, for the treatment of patients with hormone-refractory metastatic prostate cancer previously treated

  20. 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.

  1. Testing earthquake predictions

    Science.gov (United States)

    Luen, Brad; Stark, Philip B.

    2008-01-01

    Statistical tests of earthquake predictions require a null hypothesis to model occasional chance successes. To define and quantify 'chance success' is knotty. Some null hypotheses ascribe chance to the Earth: Seismicity is modeled as random. The null distribution of the number of successful predictions - or any other test statistic - is taken to be its distribution when the fixed set of predictions is applied to random seismicity. Such tests tacitly assume that the predictions do not depend on the observed seismicity. Conditioning on the predictions in this way sets a low hurdle for statistical significance. Consider this scheme: When an earthquake of magnitude 5.5 or greater occurs anywhere in the world, predict that an earthquake at least as large will occur within 21 days and within an epicentral distance of 50 km. We apply this rule to the Harvard centroid-moment-tensor (CMT) catalog for 2000-2004 to generate a set of predictions. The null hypothesis is that earthquake times are exchangeable conditional on their magnitudes and locations and on the predictions - a common "nonparametric" assumption in the literature. We generate random seismicity by permuting the times of events in the CMT catalog. We consider an event successfully predicted only if (i) it is predicted and (ii) there is no larger event within 50 km in the previous 21 days. The P-value for the observed success rate is <0.001: The method successfully predicts about 5% of earthquakes, far better than 'chance' because the predictor exploits the clustering of earthquakes - occasional foreshocks - which the null hypothesis lacks. Rather than condition on the predictions and use a stochastic model for seismicity, it is preferable to treat the observed seismicity as fixed, and to compare the success rate of the predictions to the success rate of simple-minded predictions like those just described. If the proffered predictions do no better than a simple scheme, they have little value.

  2. 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

  3. 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.

  4. 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 of the w......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...

  5. 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...

  6. 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....

  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. Preclinical profile of cabazitaxel

    Directory of Open Access Journals (Sweden)

    Vrignaud P

    2014-10-01

    safety profiles of paclitaxel and docetaxel. Clinical observations with cabazitaxel were consistent with preclinical results, and cabazitaxel is indicated, in combination with prednisone, for the treatment of patients with hormone-refractory metastatic prostate cancer previously treated with docetaxel. In conclusion, the demonstrated activity of cabazitaxel in tumors with innate or acquired resistance to docetaxel, CNS tumors, and pediatric tumors made this agent a candidate for further clinical evaluation in a broader range of patient populations compared with first-generation taxanes. Keywords: XRP6258, CNS tumors, mCRPC, pediatric tumor, taxane resistance, xenograft

  9. VPFIT: Voigt profile fitting program

    Science.gov (United States)

    Carswell, R. F.; Webb, J. K.

    2014-08-01

    The VPFIT program fits multiple Voigt profiles (convolved with the instrument profiles) to spectroscopic data that is in FITS or an ASCII file. It requires CFITSIO (ascl:1010.001) and PGPLOT (ascl:1103.002); the tarball includes RDGEN (ascl:1408.017), which can be used with VPFIT to set up the fits, fit the profiles, and examine the result in interactive mode for setting up initial guesses; vpguess (ascl:1408.016) can also be used to set up an initial file.

  10. Profiler/satellite interference analysis

    Science.gov (United States)

    Chadwick, R. B.

    1987-02-01

    An engineering analysis of potential radio interference between the Wind Profiler Demonstration Network and three NOAA satellite-based systems is presented. These three systems are: Geostationary Operational Environmental Satellite (GOES) system, the Search and Rescue Satellite (SARSAT) system, and the TIROS series Data Collection System (TDCS). The Profiler considered in this analysis is the UHF Wind Profiler to be supplied by Sperry Corporation under a contract awarded June 1986. The analysis is based on the interference-to-noise ratio at the satellite receiver. Several engineering changes have been made to the original contract to reduce potential interference. The effects of these changes are presented.

  11. 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.)

  12. Professor DS Kothari: A Profile

    Directory of Open Access Journals (Sweden)

    A. Nagaratnam

    1994-07-01

    Full Text Available This paper describes the profile of Prof. D.S. Kothari including his brief biodata his academic career etc. Prof. Kothari's contributions in the field of Astro-physics, education are also discussed.

  13. 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...

  14. 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.

  15. 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.

  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.M.Q.

    the data management. It is expected that there would be multiple profilers operating at various locations, such as coastal seas, dams and other water bodies. Data would be relayed for archival, processing and be made available to the communities who...

  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. 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...

  19. A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

    International Nuclear Information System (INIS)

    Highlights: • An energy prediction (EP) method is introduced for battery ERDE determination. • EP determines ERDE through coupled prediction of future states, parameters, and output. • The PAEP combines parameter adaptation and prediction to update model parameters. • The PAEP provides improved ERDE accuracy compared with DC and other EP methods. - Abstract: In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (ERDE) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available ERDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the ERDE directly to the current state of charge (SOC). To enhance the ERDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the ERDE prediction horizon, and the ERDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different ERDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the ERDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online ERDE prediction. The correlation of SOC estimation and ERDE calculation is then discussed to illustrate the importance of an

  20. 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.

  1. Gene expression profiles in irradiated cancer cells

    International Nuclear Information System (INIS)

    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

  2. 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

  3. 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.

  4. 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...

  5. Secondary maxima in ozone profiles

    OpenAIRE

    R. Lemoine

    2004-01-01

    International audience Ozone profiles from balloon soundings as well as SAGE II ozone profiles were used to detect anomalous large ozone concentrations of ozone in the lower stratosphere. These secondary ozone maxima are found to be the result of differential advection of ozone-poor and ozone-rich air associated with Rossby wave breaking events. The frequency and intensity of secondary ozone maxima and their geographical distribution is presented. The occurrence and amplitude of ozone seco...

  6. COGNITIVE PROFILE OF TURNER SYNDROME

    OpenAIRE

    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 report, we review previous and current research related to the cognitive profile of TS. We also discuss how cognitive impairments in this syndrome may...

  7. Integrated theater assessment profiling system

    OpenAIRE

    Wiest, James A.; Hadley, Michael P.

    2002-01-01

    Approved for public release, distribution is unlimited The Integrated Theater Assessment Profiling System (iTAPS) takes the original stove-piped Theater Assessment Profiling System (TAPS) software solution and turns it into a robust, data-centric, web-based decision support system for Commander, Second Fleet. ITAPS uses the .Net Framework and ASP.NET/ADO.NET, along with SQL Server to provide a web-enabled application that gives an overarching, abstracted view of the battle space for the Op...

  8. Lipid profile in cerebrovascular accidents

    OpenAIRE

    Soodeh Razeghi; Patricia Khashaiar; Babak Ahmadi; Mohamad Reza Gheini; Mansoureh Togha

    2011-01-01

    Background: Changes in the lipid profile have been suggested as a risk factor for developing ischemic stroke. Their role in intra-cerebral hemorrhage, however, is not clear. The present study was designed to evaluate the lipid profile levels of patients who had experienced an acute stroke during the first 24-hour and to compare these levels in different patients suffering from the stroke, either hemorrhagic or ischemic, and healthy individuals.Methods: In this cross-sectional study, 258 conse...

  9. Profiles of Everyday Thought Suppression

    OpenAIRE

    Ie, Amanda Yen Lin

    2014-01-01

    The present research assessed whether levels of depression, anxiety and worry, obsessive-compulsive distress, and psychopathy were differentially related to distinct thought suppression profiles. As a means to achieving this goal, the Profiles of Everyday Thought Suppression (PETS) scale was constructed to measure the frequencies with which various target thoughts are suppressed. The PETS scale demonstrated good internal consistency and test-retest reliability, and scores were positively co...

  10. Psychological profile of laryngectomized patients

    OpenAIRE

    Bogdan Popescu; Oana Păun; Răzvan V. Scăunașu; Cristian Bălălău; Șerban V. Berteșteanu

    2016-01-01

    Larynx cancer is one of the most susceptible form of cancer susceptible to induce alteration of the patient’s psychological profile due to the social role that the larynx has in communication. Oral communication is severely impaired even after voice rehabilitation of the laryngectomized patients, so that the social rehabilitation is somewhat not only a medical but also a social problem. The psychological profile of these patients is altered in a way that dealing with the disease is sometimes ...

  11. Profile: American Indian/Alaska Native

    Science.gov (United States)

    ... Minority Population Profiles > American Indian/Alaska Native Profile: American Indian/Alaska Native Spotlight ACA Infographic for American Indians/ ... Program Circle of Life multimedia youth education program American Indian/Alaska Native Profile Great Plains Area Alaska Area ...

  12. Molecular profiling of breast cancer: transcriptomic studies and beyond.

    Science.gov (United States)

    Culhane, A C; Howlin, J

    2007-12-01

    Utilisation of 'omics' technologies, in particular gene expression profiling, has increased dramatically in recent years. In basic research, high-throughput profiling applications are increasingly used and may now even be considered standard research tools. In the clinic, there is a need for better and more accurate diagnosis, prognosis and treatment response indicators. As such, clinicians have looked to omics technologies for potential biomarkers. These prediction profiling studies have in turn attracted the attention of basic researchers eager to uncover biological mechanisms underlying clinically useful signatures. Here we highlight some of the seminal work establishing the arrival of the omics, in particular transcriptomics, in breast cancer research and discuss a sample of the most current applications. We also discuss the challenges of data analysis and integrated data analysis with emphasis on utilising the current publicly available gene expression datasets. (Part of a Multi-author Review). PMID:17957338

  13. The generation of subsurface temperature profiles for Kuwait

    Energy Technology Data Exchange (ETDEWEB)

    Al-Temeemi, A.A.; Harris, D.J. [Department of Building Engineering and Surveying, Heriot-Watt University, Edinburgh (United Kingdom)

    2001-07-01

    A predicted profile of the periodic variation of subsurface temperature with depth is presented for the soil conditions of the State of Kuwait. The generation of the profile is based on Labs' equation for subterranean temperatures, which takes into account the thermal and physical properties of the soil. These subsurface temperatures are then compared with the ambient dry-bulb temperature. The profiles are then used to analyse the seasonal variations in subsurface temperatures at different depths and the time lags produced when compared with air temperatures. The resulting charts and graphs should be a useful tool for those interested in the energy conservation potential of earth-sheltered and earth-bermed structures in Kuwait. (author)

  14. Motivational profile of astronauts at the International Space Station

    Science.gov (United States)

    Brcic, Jelena

    2010-11-01

    Research has demonstrated that the motive triad of needs for achievement, power, and affiliation can predict variables such as occupational success and satisfaction, innovation, aggressiveness, susceptibility to illness, cooperation, conformity, and many others. The present study documents the motivational profiles of astronauts at three stages of their expedition. Thematic content analysis was employed for references to Winter's well-established motive markers in narratives (media interviews, journals, and oral histories) of 46 astronauts participating in International Space Station (ISS) expeditions. Significant pre-flight differences were found in relation to home agency and job status. NASA astronauts, compared with those from the Russian Space Agency, are motivated by higher need for power, as are commanders in comparison to flight engineers. The need for affiliation motive showed a significant change from pre-flight to in-flight stages. The implications of the relationship between the motivational profile of astronauts and the established behavioural correlates of such profiles are discussed.

  15. 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.

  16. Visualizing Risk Prediction Models

    OpenAIRE

    Vanya Van Belle; Ben Van Calster

    2015-01-01

    Objective Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. Methods The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fib...

  17. Pyroshock prediction procedures

    Science.gov (United States)

    Piersol, Allan G.

    2002-05-01

    Given sufficient effort, pyroshock loads can be predicted by direct analytical procedures using Hydrocodes that analytically model the details of the pyrotechnic explosion and its interaction with adjacent structures, including nonlinear effects. However, it is more common to predict pyroshock environments using empirical procedures based upon extensive studies of past pyroshock data. Various empirical pyroshock prediction procedures are discussed, including those developed by the Jet Propulsion Laboratory, Lockheed-Martin, and Boeing.

  18. 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.

  19. Longitudinal variability of black carbon vertical profiles

    Science.gov (United States)

    Schwarz, J. P.; Weinzierl, B.; Samset, B. H.; Perring, A. E.; Dollner, M.; Heimerl, K.; Markovic, M. Z.; Ziemba, L. D.

    2015-12-01

    Black carbon (BC) aerosol contributes substantially to both climate forcing and climate forcing uncertainty. An important source of this uncertainty derives from the difficulty in predicting BC's global abundance and vertical distribution. Here we present a multi-year record of black carbon (BC) vertical concentration profiles from both sides of the Atlantic, obtained from airborne Single Particle Soot Photometers (SP2s) flown on the NASA DC-8, and the DLR Falcon research aircraft from the CONCERT, ACCESS, DC3, SEAC4RS, and SALTRACE campaigns. The measurements constrain the relative rates of BC transport/removal from, and zonal mixing in, the upper troposphere, as well as the range of BC loadings in these regions. They also constrain the time-rates of change of BC loads in altitudes at which it is a highly efficient (although sparse) climate forcer, and a relatively long-lived aerosol tracer. We find that concentration of BC in the upper troposphere can vary by a factor 10. Over the Northern mid-latitudes concentrations are however consistent to a fraction of this range over wide longitudinal ranges, over month-long timescales. The data show that BC becomes zonally mixed here starting at 500 hPa and extending to near the tropopause. These results imply broader value than previously associated with measured vertical profiles in constraining global scale BC loadings aloft.

  20. 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.

  1. A Universal Temperature Profile for Galaxy Clusters

    CERN Document Server

    Loken, C; Nelson, E; Burns, J; Bryan, G L; Motl, P M

    2002-01-01

    We investigate the predicted present-day temperature profiles of the hot, X-ray emitting gas in galaxy clusters for two cosmological models - a current best-guess LCDM model and standard cold dark matter (SCDM). Our numerically-simulated "catalogs" of clusters are derived from high-resolution (15/h kpc) simulations which make use of a sophisticated, Eulerian-based, Adaptive Mesh-Refinement (AMR) code that faithfully captures the shocks which are essential for correctly modelling cluster temperatures. We show that the temperature structure on Mpc-scales is highly complex and non-isothermal. However, the temperature profiles of the simulated LCDM and SCDM clusters are remarkably similar and drop-off as $T +AFw-propto (1+-r/a_x)^{-+AFw-delta}$ where $a_x +AFw-sim r_{vir}/1.5$ and $+AFw-delta +AFw-sim 1.6$. This decrease is in good agreement with the observational results of Markevitch et al.(1998) but diverges, primarily in the innermost regions, from their fit which assumes a polytropic equation of state. Our r...

  2. Uplift histories from river profiles

    Science.gov (United States)

    Pritchard, D.; Roberts, G. G.; White, N. J.; Richardson, C. N.

    2009-12-01

    Longitudinal river profiles, where elevation of a river bed is plotted as a function of distance along the river bed, contain information about uplift rate. When a region adjacent to a reference level (e.g., sea level) is uplifted, a rapid change in gradient occurs near the river mouth. The erosional process causes this change in gradient to migrate upstream. Thus a river profile is effectively a ‘tape recording’ of the uplift rate history, provided that the erosional process can be adequately parameterized. Here, we use a non-linear equation to relate the shape of a river profile, z(x), to uplift rate history, U(t). If erosion is assumed to be dominated by knickpoint retreat, an inverse model can be formulated and used to calculate uplift rate histories. Our model builds upon standard stream profile analysis, which focuses on the relationship between profile slope and drainage area. We have applied this analytical approach to river profiles from the Bié Dome, Angola. Calculated uplift rate histories agree with independent geologic estimates.

  3. 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.

  4. Spinal patterns as predictors of personality profiles: a pilot study.

    Science.gov (United States)

    Koren, T; Rosenwinkel, E

    1992-01-01

    The present pilot study is part of an ongoing effort to further the investigation of the relationship between spinal patterns and personality. The present pilot study seeks to identify likely spinal patterns of certain personality profiles and asks whether changing posture can affect personality, and/or can emotional states alter posture? Forty patients of a private chiropractic practice participated in the study. Four radiographs (x-rays) of each subject were taken and each subject completed the Minnesota Multiphasic Personality Inventory (MMPI). Measurements obtained from the radiographs and the MMPI data were used to derive general linear models of the predictability of the MMPI in terms of the spinal/postural measures. Several models were highly significant and preliminary support for the authors' hypothesis that spinal patterns are likely to be predictive of personality profiles is suggested. Support for previous research is offered and directions for future research are discussed. PMID:1428613

  5. 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....

  6. Analysis and Prediction of Electricity Consumption Using Smart Meter Data

    OpenAIRE

    Sauhats, A; Varfolomejeva, R; Linkevičs, O; Petričenko, R; Kuņickis, M; Balodis, M.

    2015-01-01

    This paper is considering application of smart meter data to predict electricity consumption of household consumers. The availability and amount of data is suitable for in- depth statistical analysis of electricity consumption profiles and the study of consumer’s behavior. Prediction of electricity consumption is very important for electricity traders to balance their electricity purchase and sales portfolio, as well as to prepare optimal price products (offers) for their clients. Electricity...

  7. 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)...

  8. A Spanish text corpus for the author profiling task

    OpenAIRE

    Villegas, María Paula; Garciarena Ucelay, María José; ERRECALDE, MARCELO LUIS; Cagnina, Leticia

    2014-01-01

    Author Profiling is the task of predicting characteristics of the author of a text, such as age, gender, personality, native language, etc. This is a task of growing importance due to its potential applications in security, crime and marketing, among others. One of the main difficulties in this field is the lack of reliable text collections (corpora) to train and test automatically derived classifiers, in particular in specific languages such as Spanish. Although some recent data sets were ge...

  9. An experimental study for the Cross Domain Author Profiling classification

    OpenAIRE

    Garciarena Ucelay, María José; Villegas, María Paula; Cagnina, Leticia; ERRECALDE, MARCELO LUIS

    2015-01-01

    Author Profiling is the task of predicting characteristics of the author of a text, such as age, gender, personality, native language, etc. This is a task of growing importance due to the potential applications in security, crime detection and marketing, among others. An interesting point is to study the robustness of a classifier when it is trained with a dataset and tested with others containing different characteristics. Commonly this is called cross domain experimentation. Although differ...

  10. 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.

  11. Surface Brightness Profiles of Dwarf Galaxies: I. Profiles and Statistics

    CERN Document Server

    Herrmann, Kimberly A; Elmegreen, Bruce G

    2013-01-01

    Radial surface brightness profiles of spiral galaxies are classified into three types: (I) single exponential, or the light falls off with one exponential to a break before falling off (II) more steeply, or (III) less steeply. Profile breaks are also found in dwarf disks, but some dwarf Type IIs are flat or increasing out to a break before falling off. Here we re-examine the stellar disk profiles of 141 dwarfs: 96 dwarf irregulars (dIms), 26 Blue Compact Dwarfs (BCDs), and 19 Magellanic-type spirals (Sms). We fit single, double, or even triple exponential profiles in up to 11 passbands: GALEX FUV and NUV, ground-based UBV JHK and H{\\alpha}, and Spitzer 3.6 and 4.5 {\\mu}m. We find that more luminous galaxies have brighter centers, larger inner and outer scale lengths, and break at larger radii; dwarf trends with M_B extend to spirals. However, the V-band break surface brightness is independent of break type, M_B, and Hubble type. Dwarf Type II and III profiles fall off similarly beyond the breaks but have diff...

  12. 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.

  13. 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...

  14. Prediction of Antibody Epitopes

    DEFF Research Database (Denmark)

    Nielsen, Morten; Marcatili, Paolo

    2015-01-01

    self-proteins. Given the sequence or the structure of a protein of interest, several methods exploit such features to predict the residues that are more likely to be recognized by an immunoglobulin.Here, we present two methods (BepiPred and DiscoTope) to predict linear and discontinuous antibody...

  15. Modelling profile and shape evolution during hot rolling of steel strip

    International Nuclear Information System (INIS)

    Profile and shape control are required to assure the dimensional quality of rolled strip. Occurrence of waves either at the edges or centre of strips is attributed to inconsistency between the entry and exit cross-section profiles of the stock within a given rolling pass. The exit profile of the strip can be computed by considering that the such profile is the complement of that of the roll-gap, which is affected by wear, thermal expansion and distortion of the work rolls. A computer model was developed to predict the profile of the roll-gap taking into account the thermal gradient within the work roll and the distortion caused by the acting forces. It was possible to establish a good correlation between the profiles of strips obtained from trials carried out on site, and the predictions of the model. The model allows for the prediction of the onset of shape defects from changes in the profile of rolled strips. (Author) 17 refs

  16. Evaluating prediction uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    McKay, M.D. [Los Alamos National Lab., NM (United States)

    1995-03-01

    The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented.

  17. Predictable return distributions

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard

    This paper provides detailed insights into predictability of the entire stock and bond return distribution through the use of quantile regression. This allows us to examine speci…c parts of the return distribution such as the tails or the center, and for a suf…ciently …ne grid of quantiles we can...... predictable as a function of economic state variables. The results are, however, very different for stocks and bonds. The state variables primarily predict only location shifts in the stock return distribution, while they also predict changes in higher-order moments in the bond return distribution. Out......-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing an...

  18. The SUMER Lyman-alpha line profile in quiescent prominences

    CERN Document Server

    Curdt, W; Teriaca, L; Schühle, U

    2010-01-01

    Aims: Out of a novel observing technique, we publish for the first time, SoHO-SUMER observations of the true spectral line profile of hydrogen Lyman-alpha in quiescent prominences. With SoHO not being in Earth orbit, our high-quality data set is free from geocoronal absorption. We study the line profile and compare it with earlier observations of the higher Lyman lines and recent model predictions. Methods: We applied the reduced-aperture observing mode to two prominence targets and started a statistical analysis of the line profiles in both data sets. In particular, we investigated the shape of the profile, the radiance distribution and the line shape-to-radiance interrelation. We also compare Ly-a data to co-temporal 1206 Si III data. Results: We find that the average profile of Ly-a has a blue-peak dominance and is more reversed, if the line-of-sight is perpendicular to the field lines. The contrast of Ly-a prominence emission rasters is very low and the radiance distribution differs from the log-normal di...

  19. Morphological filters for functional assessment of roundness profiles

    International Nuclear Information System (INIS)

    Filtration techniques are useful tools for analysing roundness profiles. The 2RC filter and Gaussian filter are commonly used to assess peripheral undulations of the roundness data. However they cannot do every aspect of functional prediction. Morphological filters are employed to characterize roundness profiles for functional assessment. Traditional computation methods for morphological filters are limited to planar surfaces and unable to be extended to roundness measurement. A novel method based on alpha shape theory is developed to break up the confinement. The morphological closing and opening envelopes are obtained by rolling a disk upon the roundness profile from the air and material side of the component respectively. They can be used to identify significant peaks and valleys on the profile respectively, which is vital to the functional performance of components, especially contact phenomenon. A case study is presented where various options of morphological filters and reference circles are applied to a roundness profile, delivering different functional meanings. An in-depth comparison of morphological filters and the Gaussian filter is followed to derive their pros and cons. (paper)

  20. Multi channel beam profile digitizer

    International Nuclear Information System (INIS)

    Beam of ions in an accelerator are focussed with the help of focussing magnets to achieve very narrow circular beam. To verify the beam profile along its length, Beam Profile Monitors (BPM) are installed at number of points. The signal generated from these units convey information about the shape and axial error of the beam. Presently BPM signals are monitored on oscilloscope. One oscilloscope is required per BPM channel to be monitored and normally 2 oscilloscopes are kept for viewing beam at two successive points along with one channel selector to select the channel to be monitored. The 8 channel beam profile digitizer being developed is a low cost intelligent PC-add on card, built around Intel's 8751 microcontroller, which can be easily integrated with PC based data acquisition and control system for accelerators. Microcontroller digitizes the signal and stores information on FIFO for PC to read and graphically display the profile. User can select up to 8 profiles to view simultaneously on the screen. (author). 1 ref., 2 figs