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Sample records for ranked treatments predicted

  1. Evaluation of treatment effects by ranking

    DEFF Research Database (Denmark)

    Halekoh, U; Kristensen, K

    2008-01-01

    In crop experiments measurements are often made by a judge evaluating the crops' conditions after treatment. In the present paper an analysis is proposed for experiments where plots of crops treated differently are mutually ranked. In the experimental layout the crops are treated on consecutive...... plots usually placed side by side in one or more rows. In the proposed method a judge ranks several neighbouring plots, say three, by ranking them from best to worst. For the next observation the judge moves on by no more than two plots, such that up to two plots will be re-evaluated again...

  2. Ranking of hair dye substances according to predicted sensitization potency

    DEFF Research Database (Denmark)

    Søsted, H; Basketter, D A; Estrada, E

    2004-01-01

    substances registered in Europe and to provide their tonnage data. The sensitization potential of each substance was then estimated by using a quantitative structure-activity relationship (QSAR) model and the substances were ranked according to their predicted potency. A cluster analysis was performed...

  3. AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

    Science.gov (United States)

    Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

    2017-06-15

    Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online.

  4. Google and the mind: predicting fluency with PageRank.

    Science.gov (United States)

    Griffiths, Thomas L; Steyvers, Mark; Firl, Alana

    2007-12-01

    Human memory and Internet search engines face a shared computational problem, needing to retrieve stored pieces of information in response to a query. We explored whether they employ similar solutions, testing whether we could predict human performance on a fluency task using PageRank, a component of the Google search engine. In this task, people were shown a letter of the alphabet and asked to name the first word beginning with that letter that came to mind. We show that PageRank, computed on a semantic network constructed from word-association data, outperformed word frequency and the number of words for which a word is named as an associate as a predictor of the words that people produced in this task. We identify two simple process models that could support this apparent correspondence between human memory and Internet search, and relate our results to previous rational models of memory.

  5. Ranking beta sheet topologies with applications to protein structure prediction

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2011-01-01

    One reason why ab initio protein structure predictors do not perform very well is their inability to reliably identify long-range interactions between amino acids. To achieve reliable long-range interactions, all potential pairings of ß-strands (ß-topologies) of a given protein are enumerated...... of this paper is a method to deal with the inaccuracies of secondary structure predictors when enumerating potential ß-topologies. The results reported in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. They indicate that decoy generation can......, consistently top-ranks native ß-topologies. Since the number of potential ß-topologies grows exponentially with the number of ß-strands, it is unrealistic to expect that all potential ß-topologies can be enumerated for large proteins. The second result of this paper is an enumeration scheme of a subset of ß...

  6. Aggregate Interview Method of ranking orthopedic applicants predicts future performance.

    Science.gov (United States)

    Geissler, Jacqueline; VanHeest, Ann; Tatman, Penny; Gioe, Terence

    2013-07-01

    This article evaluates and describes a process of ranking orthopedic applicants using what the authors term the Aggregate Interview Method. The authors hypothesized that higher-ranking applicants using this method at their institution would perform better than those ranked lower using multiple measures of resident performance. A retrospective review of 115 orthopedic residents was performed at the authors' institution. Residents were grouped into 3 categories by matching rank numbers: 1-5, 6-14, and 15 or higher. Each rank group was compared with resident performance as measured by faculty evaluations, the Orthopaedic In-Training Examination (OITE), and American Board of Orthopaedic Surgery (ABOS) test results. Residents ranked 1-5 scored significantly better on patient care, behavior, and overall competence by faculty evaluation (Porthopedic resident candidates who scored highly on the Accreditation Council for Graduate Medical Education resident core competencies as measured by faculty evaluations, performed above the national average on the OITE, and passed the ABOS part 1 examination at rates exceeding the national average. Copyright 2013, SLACK Incorporated.

  7. RRCRank: a fusion method using rank strategy for residue-residue contact prediction.

    Science.gov (United States)

    Jing, Xiaoyang; Dong, Qiwen; Lu, Ruqian

    2017-09-02

    In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years. In this work, a novel fusion method based on rank strategy has been proposed to predict contacts. Unlike the traditional regression or classification strategies, the contact prediction task is regarded as a ranking task. First, two kinds of features are extracted from correlated mutations methods and ensemble machine-learning classifiers, and then the proposed method uses the learning-to-rank algorithm to predict contact probability of each residue pair. First, we perform two benchmark tests for the proposed fusion method (RRCRank) on CASP11 dataset and CASP12 dataset respectively. The test results show that the RRCRank method outperforms other well-developed methods, especially for medium and short range contacts. Second, in order to verify the superiority of ranking strategy, we predict contacts by using the traditional regression and classification strategies based on the same features as ranking strategy. Compared with these two traditional strategies, the proposed ranking strategy shows better performance for three contact types, in particular for long range contacts. Third, the proposed RRCRank has been compared with several state-of-the-art methods in CASP11 and CASP12. The results show that the RRCRank could achieve comparable prediction precisions and is better than three methods in most assessment metrics. The learning-to-rank algorithm is introduced to develop a novel rank-based method for the residue-residue contact prediction of proteins, which

  8. Ranking of microRNA target prediction scores by Pareto front analysis.

    Science.gov (United States)

    Sahoo, Sudhakar; Albrecht, Andreas A

    2010-12-01

    Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. Juvenile rank can predict male-typical adult mating behavior in female sheep treated prenatally with testosterone.

    Science.gov (United States)

    Roberts, Eila K; Flak, Jonathan N; Ye, Wen; Padmanabhan, Vasantha; Lee, Theresa M

    2009-04-01

    Previous research with female sheep indicates that exposure to excess testosterone for 60 days (from Gestational Days 30-90 of the 147-day gestation) leads to virilized genitalia, severe neuroendocrine deficits, as well as masculinization and defeminization of sexual behavior (T60 females). In contrast, 30 days of testosterone exposure (Gestational Days 60-90) produce animals with female-typical genitalia, less severe neuroendocrine alterations, and variable gender patterns of sexual behavior (T30 females). Variation in adult sexual behavior of male ungulates is influenced by early social experience, but this has never been tested in females. Here we investigate the influence of rank in the dominance hierarchy on the expression of adult sexual behavior in females. Specifically, we hypothesized that juvenile rank would predict the amount of male- and female-typical mating behavior exhibited by adult female sheep. This hypothesis was tested in two treatment groups and their controls (group 1: T60 females; group 2: T30 females). Dominance hierarchies were determined by observing competition over resources. Both groups of prenatal testosterone-treated females were higher ranking than controls (T60: P = 0.05; T30: P mating behavior than did controls; however, the T30 animals also exhibited female-typical behavior. For the T60 group, prenatal treatment, not juvenile rank, best predicted male-typical sex behavior (P = 0.007), while juvenile rank better predicted male mating behavior for the T30 group (P = 0.006). Rank did not predict female mating behavior in the hormone-treated or control ewes. We conclude that the effect of prenatal testosterone exposure on adult male-specific but not female-specific mating behavior is modulated by juvenile social experiences.

  10. Juvenile Rank Can Predict Male-Typical Adult Mating Behavior in Female Sheep Treated Prenatally with Testosterone1

    Science.gov (United States)

    Roberts, Eila K.; Flak, Jonathan N.; Ye, Wen; Padmanabhan, Vasantha; Lee, Theresa M.

    2009-01-01

    Previous research with female sheep indicates that exposure to excess testosterone for 60 days (from Gestational Days 30–90 of the 147-day gestation) leads to virilized genitalia, severe neuroendocrine deficits, as well as masculinization and defeminization of sexual behavior (T60 females). In contrast, 30 days of testosterone exposure (Gestational Days 60–90) produce animals with female-typical genitalia, less severe neuroendocrine alterations, and variable gender patterns of sexual behavior (T30 females). Variation in adult sexual behavior of male ungulates is influenced by early social experience, but this has never been tested in females. Here we investigate the influence of rank in the dominance hierarchy on the expression of adult sexual behavior in females. Specifically, we hypothesized that juvenile rank would predict the amount of male- and female-typical mating behavior exhibited by adult female sheep. This hypothesis was tested in two treatment groups and their controls (group 1: T60 females; group 2: T30 females). Dominance hierarchies were determined by observing competition over resources. Both groups of prenatal testosterone-treated females were higher ranking than controls (T60: P = 0.05; T30: P < 0.01). During the breeding season, both T60 and T30 females exhibited more male-typical mating behavior than did controls; however, the T30 animals also exhibited female-typical behavior. For the T60 group, prenatal treatment, not juvenile rank, best predicted male-typical sex behavior (P = 0.007), while juvenile rank better predicted male mating behavior for the T30 group (P = 0.006). Rank did not predict female mating behavior in the hormone-treated or control ewes. We conclude that the effect of prenatal testosterone exposure on adult male-specific but not female-specific mating behavior is modulated by juvenile social experiences. PMID:19122184

  11. Time-Aware Service Ranking Prediction in the Internet of Things Environment

    Directory of Open Access Journals (Sweden)

    Yuze Huang

    2017-04-01

    Full Text Available With the rapid development of the Internet of things (IoT, building IoT systems with high quality of service (QoS has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

  12. Time-Aware Service Ranking Prediction in the Internet of Things Environment

    Science.gov (United States)

    Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

    2017-01-01

    With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets. PMID:28448451

  13. Time-Aware Service Ranking Prediction in the Internet of Things Environment.

    Science.gov (United States)

    Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

    2017-04-27

    With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

  14. A rank-based Prediction Algorithm of Learning User's Intention

    Science.gov (United States)

    Shen, Jie; Gao, Ying; Chen, Cang; Gong, HaiPing

    Internet search has become an important part in people's daily life. People can find many types of information to meet different needs through search engines on the Internet. There are two issues for the current search engines: first, the users should predetermine the types of information they want and then change to the appropriate types of search engine interfaces. Second, most search engines can support multiple kinds of search functions, each function has its own separate search interface. While users need different types of information, they must switch between different interfaces. In practice, most queries are corresponding to various types of information results. These queries can search the relevant results in various search engines, such as query "Palace" contains the websites about the introduction of the National Palace Museum, blog, Wikipedia, some pictures and video information. This paper presents a new aggregative algorithm for all kinds of search results. It can filter and sort the search results by learning three aspects about the query words, search results and search history logs to achieve the purpose of detecting user's intention. Experiments demonstrate that this rank-based method for multi-types of search results is effective. It can meet the user's search needs well, enhance user's satisfaction, provide an effective and rational model for optimizing search engines and improve user's search experience.

  15. Discovering urban mobility patterns with PageRank based traffic modeling and prediction

    Science.gov (United States)

    Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

    2017-11-01

    Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

  16. Facial morphology predicts male fitness and rank but not survival in Second World War Finnish soldiers.

    Science.gov (United States)

    Loehr, John; O'Hara, Robert B

    2013-08-23

    We investigated fitness, military rank and survival of facial phenotypes in large-scale warfare using 795 Finnish soldiers who fought in the Winter War (1939-1940). We measured facial width-to-height ratio-a trait known to predict aggressive behaviour in males-and assessed whether facial morphology could predict survival, lifetime reproductive success (LRS) and social status. We found no difference in survival along the phenotypic gradient, however, wider-faced individuals had greater LRS, but achieved a lower military rank.

  17. How different from random are docking predictions when ranked by scoring functions?

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Oliva, Baldomero

    2010-01-01

    Docking algorithms predict the structure of protein-protein interactions. They sample the orientation of two unbound proteins to produce various predictions about their interactions, followed by a scoring step to rank the predictions. We present a statistical assessment of scoring functions used...... to rank near-native orientations, applying our statistical analysis to a benchmark dataset of decoys of protein-protein complexes and assessing the statistical significance of the outcome in the Critical Assessment of PRedicted Interactions (CAPRI) scoring experiment. A P value was assigned that depended...... functions results merely from random choice. This analysis reveals that changes should be made in the design of the CAPRI scoring experiment. We propose including the statistical assessment in this experiment either at the preprocessing or the evaluation step....

  18. Netter: re-ranking gene network inference predictions using structural network properties.

    Science.gov (United States)

    Ruyssinck, Joeri; Demeester, Piet; Dhaene, Tom; Saeys, Yvan

    2016-02-09

    Many algorithms have been developed to infer the topology of gene regulatory networks from gene expression data. These methods typically produce a ranking of links between genes with associated confidence scores, after which a certain threshold is chosen to produce the inferred topology. However, the structural properties of the predicted network do not resemble those typical for a gene regulatory network, as most algorithms only take into account connections found in the data and do not include known graph properties in their inference process. This lowers the prediction accuracy of these methods, limiting their usability in practice. We propose a post-processing algorithm which is applicable to any confidence ranking of regulatory interactions obtained from a network inference method which can use, inter alia, graphlets and several graph-invariant properties to re-rank the links into a more accurate prediction. To demonstrate the potential of our approach, we re-rank predictions of six different state-of-the-art algorithms using three simple network properties as optimization criteria and show that Netter can improve the predictions made on both artificially generated data as well as the DREAM4 and DREAM5 benchmarks. Additionally, the DREAM5 E.coli. community prediction inferred from real expression data is further improved. Furthermore, Netter compares favorably to other post-processing algorithms and is not restricted to correlation-like predictions. Lastly, we demonstrate that the performance increase is robust for a wide range of parameter settings. Netter is available at http://bioinformatics.intec.ugent.be. Network inference from high-throughput data is a long-standing challenge. In this work, we present Netter, which can further refine network predictions based on a set of user-defined graph properties. Netter is a flexible system which can be applied in unison with any method producing a ranking from omics data. It can be tailored to specific prior

  19. Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  20. Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  1. DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank.

    Science.gov (United States)

    Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2016-06-15

    Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. http://datamining-iip.fudan.edu.cn/service/DrugE-Rank zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  2. Effect of Water Invasion on Outburst Predictive Index of Low Rank Coals in Dalong Mine.

    Directory of Open Access Journals (Sweden)

    Jingyu Jiang

    Full Text Available To improve the coal permeability and outburst prevention, coal seam water injection and a series of outburst prevention measures were tested in outburst coal mines. These methods have become important technologies used for coal and gas outburst prevention and control by increasing the external moisture of coal or decreasing the stress of coal seam and changing the coal pore structure and gas desorption speed. In addition, techniques have had a significant impact on the gas extraction and outburst prevention indicators of coal seams. Globally, low rank coals reservoirs account for nearly half of hidden coal reserves and the most obvious feature of low rank coal is the high natural moisture content. Moisture will restrain the gas desorption and will affect the gas extraction and accuracy of the outburst prediction of coals. To study the influence of injected water on methane desorption dynamic characteristics and the outburst predictive index of coal, coal samples were collected from the Dalong Mine. The methane adsorption/desorption test was conducted on coal samples under conditions of different injected water contents. Selective analysis assessed the variations of the gas desorption quantities and the outburst prediction index (coal cutting desorption index. Adsorption tests indicated that the Langmuir volume of the Dalong coal sample is ~40.26 m3/t, indicating a strong gas adsorption ability. With the increase of injected water content, the gas desorption amount of the coal samples decreased under the same pressure and temperature. Higher moisture content lowered the accumulation desorption quantity after 120 minutes. The gas desorption volumes and moisture content conformed to a logarithmic relationship. After moisture correction, we obtained the long-flame coal outburst prediction (cutting desorption index critical value. This value can provide a theoretical basis for outburst prediction and prevention of low rank coal mines and similar

  3. Effect of Water Invasion on Outburst Predictive Index of Low Rank Coals in Dalong Mine

    Science.gov (United States)

    Jiang, Jingyu; Cheng, Yuanping; Mou, Junhui; Jin, Kan; Cui, Jie

    2015-01-01

    To improve the coal permeability and outburst prevention, coal seam water injection and a series of outburst prevention measures were tested in outburst coal mines. These methods have become important technologies used for coal and gas outburst prevention and control by increasing the external moisture of coal or decreasing the stress of coal seam and changing the coal pore structure and gas desorption speed. In addition, techniques have had a significant impact on the gas extraction and outburst prevention indicators of coal seams. Globally, low rank coals reservoirs account for nearly half of hidden coal reserves and the most obvious feature of low rank coal is the high natural moisture content. Moisture will restrain the gas desorption and will affect the gas extraction and accuracy of the outburst prediction of coals. To study the influence of injected water on methane desorption dynamic characteristics and the outburst predictive index of coal, coal samples were collected from the Dalong Mine. The methane adsorption/desorption test was conducted on coal samples under conditions of different injected water contents. Selective analysis assessed the variations of the gas desorption quantities and the outburst prediction index (coal cutting desorption index). Adsorption tests indicated that the Langmuir volume of the Dalong coal sample is ~40.26 m3/t, indicating a strong gas adsorption ability. With the increase of injected water content, the gas desorption amount of the coal samples decreased under the same pressure and temperature. Higher moisture content lowered the accumulation desorption quantity after 120 minutes. The gas desorption volumes and moisture content conformed to a logarithmic relationship. After moisture correction, we obtained the long-flame coal outburst prediction (cutting desorption) index critical value. This value can provide a theoretical basis for outburst prediction and prevention of low rank coal mines and similar occurrence conditions

  4. MicroRNA prediction with a novel ranking algorithm based on random walks.

    Science.gov (United States)

    Xu, Yunpen; Zhou, Xuefeng; Zhang, Weixiong

    2008-07-01

    MicroRNA (miRNAs) play essential roles in post-transcriptional gene regulation in animals and plants. Several existing computational approaches have been developed to complement experimental methods in discovery of miRNAs that express restrictively in specific environmental conditions or cell types. These computational methods require a sufficient number of characterized miRNAs as training samples, and rely on genome annotation to reduce the number of predicted putative miRNAs. However, most sequenced genomes have not been well annotated and many of them have a very few experimentally characterized miRNAs. As a result, the existing methods are not effective or even feasible for identifying miRNAs in these genomes. Aiming at identifying miRNAs from genomes with a few known miRNA and/or little annotation, we propose and develop a novel miRNA prediction method, miRank, based on our new random walks- based ranking algorithm. We first tested our method on Homo sapiens genome; using a very few known human miRNAs as samples, our method achieved a prediction accuracy greater than 95%. We then applied our method to predict 200 miRNAs in Anopheles gambiae, which is the most important vector of malaria in Africa. Our further study showed that 78 out of the 200 putative miRNA precursors encode mature miRNAs that are conserved in at least one other animal species. These conserved putative miRNAs are good candidates for further experimental study to understand malaria infection. MiRank is programmed in Matlab on Windows platform. The source code is available upon request.

  5. Ranking dental aesthetics and thresholds of treatment need: a comparison between patients, parents, and dentists.

    Science.gov (United States)

    Hamdan, Ahmad M; Al-Omari, Iyad K; Al-Bitar, Zaid B

    2007-08-01

    The aims of the present study were to compare rankings of dental aesthetics and the threshold at which orthodontic treatment would be sought among patients, parents, and dentists. A prospective cross-sectional study was designed to address these aims. The study sample comprised 100 patients and parents and 23 dental specialists. The patients were equally divided between males and females and their mean age was 14.7 years (standard deviation 2.3 years). The aesthetic component (AC) of the Index of Orthodontic Treatment Need (IOTN) represented impairment of dental aesthetics. The 10 numbered photographs of the AC were cut into equal-sized rectangles and subjects were asked to arrange them from 'the one that looks best' to 'the one that looks worst'. The subjects were then presented with the 10 photographs of AC in sequence and asked to identify the cut-off point between 'teeth that need orthodontic treatment' and 'no treatment'. Statistical analysis was undertaken with a Mann-Whitney test. The results showed that median rankings of dental aesthetics were similar among the three groups (P > 0.05). The median ranking of photographs 1, 2, 3, 4, and 10 were identical to the AC of IOTN. The photographs representing IOTN AC 7 and 8 were allocated the same median rank of 7 and AC 5 and 9 were allocated corresponding median ranks of 6 and 8, respectively. There were no significant differences in median cut-off points for treatment need among the three groups of subjects (P > 0.05), indicating that the mean threshold at which treatment would be sought was AC 4.

  6. Spectrum Hole Prediction And White Space Ranking For Cognitive Radio Network Using An Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Sunday Iliya

    2015-08-01

    Full Text Available Abstract With spectrum becoming an ever scarcer resource it is critical that new communication systems utilize all the available frequency bands as efficiently as possible in time frequency and spatial domain. rHowever spectrum allocation policies most of the licensed spectrums grossly underutilized while the unlicensed spectrums are overcrowded. Hence all future wireless communication devices beequipped with cognitive capability to maximize quality of service QoS require a lot of time and energartificial intelligence and machine learning in cognitive radio deliver optimum performance. In this paper we proposed a novel way of spectrum holes prediction using artificial neural network ANN. The ANN was trained to adapt to the radio spectrum traffic of 20 channels and the trained network was used for prediction of future spectrum holes. The input of the neural network consist of a time domain vector of length six i.e. minute hour date day week and month. The output is a vector of length 20 each representing the probability of the channel being idle. The channels are ranked in order of decreasing probability of being idleminimizing We assumed that all the channels have the same noise and quality of service and only one vacant channel is needed for communication. The result of the spectrum holes search using ANN was compared with that of blind linear and blind stochastic search and was found to be superior. The performance of the ANN that was trained to predict the probability of the channels being idle outperformed the ANN that will predict the exact channel states busy or idle. In the ANN that was trained to predict the exact channels states all channels predicted to be idle are randomly searched until the first spectrum hole was found no information about search direction regarding which channel should be sensed first.

  7. Weighted log-rank statistic to compare shared-path adaptive treatment strategies.

    Science.gov (United States)

    Kidwell, Kelley M; Wahed, Abdus S

    2013-04-01

    Adaptive treatment strategies (ATSs) more closely mimic the reality of a physician's prescription process where the physician prescribes a medication to his/her patient, and based on that patient's response to the medication, modifies the treatment. Two-stage randomization designs, more generally, sequential multiple assignment randomization trial designs, are useful to assess ATSs where the interest is in comparing the entire sequence of treatments, including the patient's intermediate response. In this paper, we introduce the notion of shared-path and separate-path ATSs and propose a weighted log-rank statistic to compare overall survival distributions of multiple two-stage ATSs, some of which may be shared-path. Large sample properties of the statistic are derived and the type I error rate and power of the test are compared with the standard log-rank test through simulation.

  8. Improving predicted protein loop structure ranking using a Pareto-optimality consensus method.

    Science.gov (United States)

    Li, Yaohang; Rata, Ionel; Chiu, See-wing; Jakobsson, Eric

    2010-07-20

    Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction. We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of approximately 20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD functions based on Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set.

  9. Usability Prediction & Ranking of SDLC Models Using Fuzzy Hierarchical Usability Model

    Science.gov (United States)

    Gupta, Deepak; Ahlawat, Anil K.; Sagar, Kalpna

    2017-06-01

    Evaluation of software quality is an important aspect for controlling and managing the software. By such evaluation, improvements in software process can be made. The software quality is significantly dependent on software usability. Many researchers have proposed numbers of usability models. Each model considers a set of usability factors but do not cover all the usability aspects. Practical implementation of these models is still missing, as there is a lack of precise definition of usability. Also, it is very difficult to integrate these models into current software engineering practices. In order to overcome these challenges, this paper aims to define the term `usability' using the proposed hierarchical usability model with its detailed taxonomy. The taxonomy considers generic evaluation criteria for identifying the quality components, which brings together factors, attributes and characteristics defined in various HCI and software models. For the first time, the usability model is also implemented to predict more accurate usability values. The proposed system is named as fuzzy hierarchical usability model that can be easily integrated into the current software engineering practices. In order to validate the work, a dataset of six software development life cycle models is created and employed. These models are ranked according to their predicted usability values. This research also focuses on the detailed comparison of proposed model with the existing usability models.

  10. A dose-volume-based tool for evaluating and ranking IMRT treatment plans.

    Science.gov (United States)

    Miften, Moyed M; Das, Shiva K; Su, Min; Marks, Lawrence B

    2004-01-01

    External beam radiotherapy is commonly used for patients with cancer. While tumor shrinkage and palliation are frequently achieved, local control and cure remain elusive for many cancers. With regard to local control, the fundamental problem is that radiotherapy-induced normal tissue injury limits the dose that can be delivered to the tumor. While intensity-modulated radiation therapy (IMRT) allows for the delivery of higher tumor doses and the sparing of proximal critical structures, multiple competing plans can be generated based on dosimetric and/or biological constraints that need to be considered/compared. In this work, an IMRT treatment plan evaluation and ranking tool, based on dosimetric criteria, is presented. The treatment plan with the highest uncomplicated target conformity index (TCI+) is ranked at the top. The TCI+ is a dose-volume-based index that considers both a target conformity index (TCI) and a normal tissue-sparing index (NTSI). TCI+ is designed to assist in the process of judging the merit of a clinical treatment plan. To demonstrate the utility of this tool, several competing lung and prostate IMRT treatment plans are compared. Results show that the plan with the highest TCI+ values accomplished the competing goals of tumor coverage and critical structures sparing best, among rival treatment plans for both treatment sites. The study demonstrates, first, that dose-volume-based indices, which summarize complex dose distributions through a single index, can be used to automatically select the optimal plan among competing plans, and second, that this dose-volume-based index may be appropriate for ranking IMRT dose distributions.

  11. A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

    Directory of Open Access Journals (Sweden)

    Vassal Aurélien

    2008-01-01

    Full Text Available Abstract Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM. Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with

  12. Subtype prediction in pediatric acute myeloid leukemia: classification using differential network rank conservation revisited.

    Science.gov (United States)

    Obulkasim, Askar; Fornerod, Maarten; Zwaan, Michel C; Reinhardt, Dirk; van den Heuvel-Eibrink, Marry M

    2015-09-23

    One of the most important application spectrums of transcriptomic data is cancer phenotype classification. Many characteristics of transcriptomic data, such as redundant features and technical artifacts, make over-fitting commonplace. Promising classification results often fail to generalize across datasets with different sources, platforms, or preprocessing. Recently a novel differential network rank conservation (DIRAC) algorithm to characterize cancer phenotypes using transcriptomic data. DIRAC is a member of a family of algorithms that have shown useful for disease classification based on the relative expression of genes. Combining the robustness of this family's simple decision rules with known biological relationships, this systems approach identifies interpretable, yet highly discriminate networks. While DIRAC has been briefly employed for several classification problems in the original paper, the potentials of DIRAC in cancer phenotype classification, and especially robustness against artifacts in transcriptomic data have not been fully characterized yet. In this study we thoroughly investigate the potentials of DIRAC by applying it to multiple datasets, and examine the variations in classification performances when datasets are (i) treated and untreated for batch effect; (ii) preprocessed with different techniques. We also propose the first DIRAC-based classifier to integrate multiple networks. We show that the DIRAC-based classifier is very robust in the examined scenarios. To our surprise, the trained DIRAC-based classifier even translated well to a dataset with different biological characteristics in the presence of substantial batch effects that, as shown here, plagued the standard expression value based classifier. In addition, the DIRAC-based classifier, because of the integrated biological information, also suggests pathways to target in specific subtypes, which may enhance the establishment of personalized therapy in diseases such as pediatric AML

  13. Predicting Rank Attainment in Political Science: What Else besides Publications Affects Promotion?

    Science.gov (United States)

    Hesli, Vicki L.; Lee, Jae Mook; Mitchell, Sara McLaughlin

    2012-01-01

    We report the results of hypotheses tests about the effects of several measures of research, teaching, and service on the likelihood of achieving the ranks of associate and full professor. In conducting these tests, we control for institutional and individual background characteristics. We focus our tests on the link between productivity and…

  14. Iteratively reweighted generalized rank annihilation method 1. Improved handling of prediction bias

    NARCIS (Netherlands)

    Faber, N.M.; Ferre, J.; Boque, R.

    2001-01-01

    The generalized rank annihilation method (GRAM) is a method for curve resolution and calibration that uses two bilinear matrices simultaneously, i.e., one for the unknown and one for the calibration sample. A GRAM calculation amounts to solving an eigenvalue problem for which the eigenvalues are

  15. D3R Grand Challenge 2: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

    Science.gov (United States)

    Gaieb, Zied; Liu, Shuai; Gathiaka, Symon; Chiu, Michael; Yang, Huanwang; Shao, Chenghua; Feher, Victoria A.; Walters, W. Patrick; Kuhn, Bernd; Rudolph, Markus G.; Burley, Stephen K.; Gilson, Michael K.; Amaro, Rommie E.

    2018-01-01

    The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank (http://www.pdb.org), and in affinity ranking and scoring of bound ligands.

  16. Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

    Science.gov (United States)

    Hu, Peizhen; Chung, Leland W K; Berel, Dror; Frierson, Henry F; Yang, Hua; Liu, Chunyan; Wang, Ruoxiang; Li, Qinlong; Rogatko, Andre; Zhau, Haiyen E

    2013-01-01

    We reported (PLoS One 6 (12):e28670, 2011) that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC) tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE) tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1) expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

  17. Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

    Directory of Open Access Journals (Sweden)

    Peizhen Hu

    Full Text Available We reported (PLoS One 6 (12:e28670, 2011 that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1 expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

  18. Effects of sample size on differential gene expression, rank order and prediction accuracy of a gene signature.

    Directory of Open Access Journals (Sweden)

    Cynthia Stretch

    Full Text Available Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65 ♀ in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n = 10 (5 ♂, 5 ♀ to n = 120 (60 ♂, 60 ♀ thereof were used to assess the effect of sample size on the differential expression of single genes, gene rank order and prediction accuracy. Using our full dataset (n = 134, we identified 717 differentially expressed transcripts (p<0.0001 and we were able predict sex with ~90% accuracy, both within our dataset and on external datasets. Both p-values and rank order of top differentially expressed genes became more variable using smaller subsamples. For example, at n = 10 (5 ♂, 5 ♀, no gene was considered differentially expressed at p<0.0001 and prediction accuracy was ~50% (no better than chance. We found that sample size clearly affects microarray analysis results; small sample sizes result in unstable gene lists and poor prediction accuracy. We anticipate this will apply to other phenotypes, in addition to sex.

  19. The role of rank-ligand inhibition in the treatment of postmenopausal osteoporosis

    Directory of Open Access Journals (Sweden)

    M. Varenna

    2011-06-01

    Full Text Available Osteoporosis is a skeletal disease affecting millions of people worldwide in which a decreased bone mass and a microarchitectural deterioration compromise bone strength leading to bone fragility and increased susceptibility to fracture. Bone turnover increases at menopause, with osteoclast-mediated bone resorption exceeding bone formation. Recent discoveries in bone biology have demonstrated that RANKL, a cytokine member of the tumor necrosis factor superfamily, is an essential mediator of osteoclast formation, function and survival. Denosumab is a fully human monoclonal antibody with a high affinity and specificity for human RANKL. By binding to its target, denosumab prevents the interaction of RANKL with its receptor RANK on osteoclasts and their precursors and inhibits osteoclast-mediated bone resorption. Administered as a subcutaneous injection every six months, denosumab has been shown to decrease bone turnover and to increase bone mineral density in postmenopausal women with low bone mass and osteoporosis. In these patients denosumab significantly reduced the risk of vertebral fractures, hip fractures and nonvertebral fractures. In all clinical trials published to date, denosumab was well tolerated with an incidence of adverse events, including infections and malignancy, generally similar to subjects receiving placebo or alendronate. The denosumab therapeutic regimen consisting in a subcutaneous injection every 6 months may increase patient compliance and persistence with a further benefit from treatment. By providing a new molecular target for osteoporosis treatment, denosumab is a promising drug for the treatment of postmenopausal osteoporosis and the prevention of fragility fractures.

  20. Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients.

    Science.gov (United States)

    Liu, Tianchi; Lin, Zhiping; Ong, Marcus Eng Hock; Koh, Zhi Xiong; Pek, Pin Pin; Yeo, Yong Kiang; Oh, Beom-Seok; Ho, Andrew Fu Wah; Liu, Nan

    2015-12-01

    The recently developed geometric distance scoring system has shown the effectiveness of scoring systems in predicting cardiac arrest within 72h and the potential to predict other clinical outcomes. However, the geometric distance scoring system predicts scores based on only local structure embedded by the data, thus leaving much room for improvement in terms of prediction accuracy. We developed a novel scoring system for predicting cardiac arrest within 72h. The scoring system was developed based on a semi-supervised learning algorithm, manifold ranking, which explores both the local and global consistency of the data. System evaluation was conducted on emergency department patients׳ data, including both vital signs and heart rate variability (HRV) parameters. Comparison of the proposed scoring system with previous work was given in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). Out of 1025 patients, 52 (5.1%) met the primary outcome. Experimental results show that the proposed scoring system was able to achieve higher area under the curve (AUC) on both the balanced dataset (0.907 vs. 0.824) and the imbalanced dataset (0.774 vs. 0.734) compared to the geometric distance scoring system. The proposed scoring system improved the prediction accuracy by utilizing the global consistency of the training data. We foresee the potential of extending this scoring system, as well as manifold ranking algorithm, to other medical decision making problems. Furthermore, we will investigate the parameter selection process and other techniques to improve performance on the imbalanced dataset. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR

    Science.gov (United States)

    Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A.; Ducrot, Pierre; Barril, Xavier

    2017-08-01

    The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

  2. Predicted binding site information improves model ranking in protein docking using experimental and computer-generated target structures.

    Science.gov (United States)

    Maheshwari, Surabhi; Brylinski, Michal

    2015-11-23

    Protein-protein interactions (PPIs) mediate the vast majority of biological processes, therefore, significant efforts have been directed to investigate PPIs to fully comprehend cellular functions. Predicting complex structures is critical to reveal molecular mechanisms by which proteins operate. Despite recent advances in the development of new methods to model macromolecular assemblies, most current methodologies are designed to work with experimentally determined protein structures. However, because only computer-generated models are available for a large number of proteins in a given genome, computational tools should tolerate structural inaccuracies in order to perform the genome-wide modeling of PPIs. To address this problem, we developed eRank(PPI), an algorithm for the identification of near-native conformations generated by protein docking using experimental structures as well as protein models. The scoring function implemented in eRank(PPI) employs multiple features including interface probability estimates calculated by eFindSite(PPI) and a novel contact-based symmetry score. In comparative benchmarks using representative datasets of homo- and hetero-complexes, we show that eRank(PPI) consistently outperforms state-of-the-art algorithms improving the success rate by ~10 %. eRank(PPI) was designed to bridge the gap between the volume of sequence data, the evidence of binary interactions, and the atomic details of pharmacologically relevant protein complexes. Tolerating structure imperfections in computer-generated models opens up a possibility to conduct the exhaustive structure-based reconstruction of PPI networks across proteomes. The methods and datasets used in this study are available at www.brylinski.org/erankppi.

  3. On predicting student performance using low-rank matrix factorization techniques

    DEFF Research Database (Denmark)

    Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

    2017-01-01

    Predicting the score of a student is one of the important problems in educational data mining. The scores given by an individual student reflect how a student understands and applies the knowledge conveyed in class. A reliable performance prediction enables teachers to identify weak students...... that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools...

  4. Analysis of the predictive qualities of betting odds and FIFA World Ranking: evidence from the 2006, 2010 and 2014 Football World Cups.

    Science.gov (United States)

    Wunderlich, Fabian; Memmert, Daniel

    2016-12-01

    The present study aims to investigate the ability of a new framework enabling to derive more detailed model-based predictions from ranking systems. These were compared to predictions from the bet market including data from the World Cups 2006, 2010, and 2014. The results revealed that the FIFA World Ranking has essentially improved its predictive qualities compared to the bet market since the mode of calculation was changed in 2006. While both predictors were useful to obtain accurate predictions in general, the world ranking was able to outperform the bet market significantly for the World Cup 2014 and when the data from the World Cups 2010 and 2014 were pooled. Our new framework can be extended in future research to more detailed prediction tasks (i.e., predicting the final scores of a match or the tournament progress of a team).

  5. Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

    Directory of Open Access Journals (Sweden)

    Christof Winter

    Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

  6. What Predicts Performance? A Multicenter Study Examining the Association Between Resident Performance, Rank List Position, and United States Medical Licensing Examination Step 1 Scores.

    Science.gov (United States)

    Wagner, Jonathan G; Schneberk, Todd; Zobrist, Marissa; Hern, H Gene; Jordan, Jamie; Boysen-Osborn, Megan; Menchine, Michael

    2017-03-01

    Each application cycle, emergency medicine (EM) residency programs attempt to predict which applicants will be most successful in residency and rank them accordingly on their program's Rank Order List (ROL). Determine if ROL position, participation in a medical student rotation at their respective program, or United States Medical Licensing Examination (USMLE) Step 1 rank within a class is predictive of residency performance. All full-time EM faculty at Los Angeles County + University of Southern California (LAC + USC), Harbor-UCLA (Harbor), Alameda Health System-Highland (Highland), and the University of California-Irvine (UCI) ranked each resident in the classes of 2013 and 2014 at time of graduation. From these anonymous surveys, a graduation ROL was created, and using Spearman's rho, was compared with the program's adjusted ROL, USMLE Step 1 rank, and whether the resident participated in a medical student rotation. A total of 93 residents were evaluated. Graduation ROL position did not correlate with adjusted ROL position (Rho = 0.14, p = 0.19) or USMLE Step 1 rank (Rho = 0.15, p = 0.14). Interestingly, among the subgroup of residents who rotated as medical students, adjusted ROL position demonstrated significant correlation with final ranking on graduation ROL (Rho = 0.31, p = 0.03). USMLE Step 1 score rank and adjusted ROL position did not predict resident performance at time of graduation. However, adjusted ROL position was predictive of future residency success in the subgroup of residents who had completed a sub-internship at their respective programs. These findings should guide the future selection of EM residents. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

    Science.gov (United States)

    Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

    2018-01-01

    The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

  8. Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

    Science.gov (United States)

    Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

    2017-10-01

    The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

  9. Tensor Rank

    OpenAIRE

    Erdtman, Elias; Jönsson, Carl

    2012-01-01

    This master's thesis addresses numerical methods of computing the typical ranks of tensors over the real numbers and explores some properties of tensors over finite fields. We present three numerical methods to compute typical tensor rank. Two of these have already been published and can be used to calculate the lowest typical ranks of tensors and an approximate percentage of how many tensors have the lowest typical ranks (for some tensor formats), respectively. The third method was developed...

  10. Rank Dynamics

    Science.gov (United States)

    Gershenson, Carlos

    Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

  11. Prediction of antiepileptic drug treatment outcomes using machine learning.

    Science.gov (United States)

    Colic, Sinisa; Wither, Robert G; Lang, Min; Zhang, Liang; Eubanks, James H; Bardakjian, Berj L

    2017-02-01

    Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs. Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I CFC) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes. (a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably. Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.

  12. Frequency and predictive values of first rank symptoms at baseline among 362 young adult patients with first-episode schizophrenia Results from the Danish OPUS study

    DEFF Research Database (Denmark)

    Thorup, Anne; Petersen, Lone; Jeppesen, Pia

    2007-01-01

    To investigate the frequency of the Schneiderian First Rank Symptoms (FRSs) in a representative group of patients with first-episode schizophrenia and to analyse the predictive value of these symptoms in relation to psychopathology, work situation, depression, dependency and admission after 2 years...

  13. Prediction of treatment response to adalimumab

    DEFF Research Database (Denmark)

    Krintel, S. B.; Dehlendorff, C.; Hetland, M. L.

    2016-01-01

    At least 30% of patients with rheumatoid arthritis (RA) do not respond to biologic agents, which emphasizes the need of predictive biomarkers. We aimed to identify microRNAs (miRNAs) predictive of response to adalimumab in 180 treatment-naïve RA patients enrolled in the OPtimized treatment algori...... of low expression of miR-22 and high expression of miR-886.3p was associated with EULAR good response. Future studies to assess the utility of these miRNAs as predictive biomarkers are needed.The Pharmacogenomics Journal advance online publication, 5 May 2015; doi:10.1038/tpj.2015.30....

  14. Sequential rank agreement methods for comparison of ranked lists

    DEFF Research Database (Denmark)

    Ekstrøm, Claus Thorn; Gerds, Thomas Alexander; Jensen, Andreas Kryger

    2015-01-01

    The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies...... are illustrated using gene rankings, and using data from two Danish ovarian cancer studies where we assess the within and between agreement of different statistical classification methods.......The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies...

  15. Influence of Ascaridia galli infections and anthelmintic treatments on the behaviour and social ranks of laying hens (Gallus gallus domesticus).

    Science.gov (United States)

    Gauly, M; Duss, C; Erhardt, G

    2007-05-31

    In the present study, the effects of an experimental Ascaridia galli infection and anthelmintic treatment on the behaviour and social status of laying hens of two different lines were studied. Sixty white (Lohmann LSL; LSL) and 60 brown (Lohmann Brown; LB) hens were reared under helminth-free conditions. The hens of each line were divided into four groups. The birds in two of the groups were artificially infected with 250 embryonated A. galli eggs at an age of 27 weeks. The other two groups were kept as uninfected controls. One infection and control group was dewormed at 38 weeks of age and slaughtered 4 weeks later, contemporary with the other animals. Individual faecal Ascaridia egg counts (FEC) were performed 11 weeks post-infection (p.i.). Body weights, laying performance and egg weights were recorded regularly. Blood was taken to measure testosterone levels. The worm burdens established in the intestines were counted in the infected not treated group after slaughtering. In addition, 15 behavioural parameters were recorded by focal animal observation (n=10 per group) of one infection (plus anthelmintic treatment) and one control group, according to the time-sampling method throughout the experiment. All agonistic interactions within the groups were recorded simultaneously on an ongoing basis, thereby allowing the calculation of an individual social rank index. The following results were obtained: Mean FEC and worm burden were higher (p hens than in the LB hens, but their performances were not different (p > 0.05) from the controls. Infections with A. galli resulted in significant behavioural changes in both lines as the infected birds showed a higher food intake and lower locomotion activity during the prepatent and patent periods. After anthelmintic treatment, food intake decreased and locomotion increased. Behavioural changes were more pervasive in the infected LSL hens, as these hens also showed changes in ground pecking and nesting activity not only during

  16. Ranking antireabsorptive agents to prevent vertebral fractures in postmenopausal osteoporosis by mixed treatment comparison meta-analysis.

    Science.gov (United States)

    Migliore, A; Broccoli, S; Massafra, U; Cassol, M; Frediani, B

    2013-03-01

    Bisphosphonates are considered as a first-line therapy for the prevention and treatment of osteoporosis, showing in double-blind, randomized, controlled trials a significant reduction of incidence of new vertebral fractures compared to placebo. Recently also, Denosumab has been shown to reduce the appearance of new vertebral fractures by blocking RANK. There are not head to head comparative studies between the above mentioned drugs. Mixed treatment comparison, an extension of traditional meta-analysis, is able to compare simultaneously several drugs across a range producing a synthetic evidence of efficacy and a range of probability as to the best treatment. The aim of this study is to simultaneously compare alendronate, risedronate, ibandronate, zolendronate and denosumab in the prevention of OP vertebral fractures in a Bayesian meta-analysis for assessing indirect comparisons. A search for randomized controlled trials involving alendronate, risedronate, ibandronate, zolendronate and denosumab was conducted using several databases. Randomized controlled trials (RCTs) with a double blind treatment period of at least 3 years were included. Men and Glucorticoid Induced osteoporosis, RCTs having as primary or secondary endpoints continuous values as body mineral density (BMD) and studies comparing different dosing regimens of the same agent, which are not used in clinical practice, were excluded. Only fully published reports were considered. A total of 9 RCTs were identified providing data on 31,393 participants. Zolendronate had the highest probability (52%) of being the most effective treatment towards placebo, followed by denosumab (46% probability), ibandronate and then alendronate and risedronate against placebo. Although the mixed treatment comparisons among alendronate, risedronate, ibandronate, zolendronate and denosumab did not show a statistically significant difference, this analysis suggests that zolendronate, compared to placebo, is expected to provide

  17. Collision prediction software for radiotherapy treatments

    Energy Technology Data Exchange (ETDEWEB)

    Padilla, Laura [Virginia Commonwealth University Medical Center, Richmond, Virginia 23298 (United States); Pearson, Erik A. [Techna Institute and the Princess Margaret Cancer Center, University Health Network, Toronto, Ontario M5G 2M9 (Canada); Pelizzari, Charles A., E-mail: c-pelizzari@uchicago.edu [Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, Illinois 60637 (United States)

    2015-11-15

    Purpose: This work presents a method of collision predictions for external beam radiotherapy using surface imaging. The present methodology focuses on collision prediction during treatment simulation to evaluate the clearance of a patient’s treatment position and allow for its modification if necessary. Methods: A Kinect camera (Microsoft, Redmond, WA) is used to scan the patient and immobilization devices in the treatment position at the simulator. The surface is reconstructed using the SKANECT software (Occipital, Inc., San Francisco, CA). The treatment isocenter is marked using simulated orthogonal lasers projected on the surface scan. The point cloud of this surface is then shifted to isocenter and converted from Cartesian to cylindrical coordinates. A slab models the treatment couch. A cylinder with a radius equal to the normal distance from isocenter to the collimator plate, and a height defined by the collimator diameter is used to estimate collisions. Points within the cylinder clear through a full gantry rotation with the treatment couch at 0° , while points outside of it collide. The angles of collision are reported. This methodology was experimentally verified using a mannequin positioned in an alpha cradle with both arms up. A planning CT scan of the mannequin was performed, two isocenters were marked in PINNACLE, and this information was exported to AlignRT (VisionRT, London, UK)—a surface imaging system for patient positioning. This was used to ensure accurate positioning of the mannequin in the treatment room, when available. Collision calculations were performed for the two treatment isocenters and the results compared to the collisions detected the room. The accuracy of the Kinect-Skanect surface was evaluated by comparing it to the external surface of the planning CT scan. Results: Experimental verification results showed that the predicted angles of collision matched those recorded in the room within 0.5°, in most cases (largest deviation

  18. Attentional bias predicts heroin relapse following treatment

    NARCIS (Netherlands)

    Marissen, Marlies A. E.; Franken, Ingmar H. A.; Waters, Andrew J.; Blanken, Peter; van den Brink, Wim; Hendriks, Vincent M.

    2006-01-01

    AIMS: Previous studies have shown that abstinent heroin addicts exhibit an attentional bias to heroin-related stimuli. It has been suggested that attentional bias may represent a vulnerability to relapse into drug use. In the present study, the predictive value of pre-treatment attentional bias on

  19. Predicting treatment outcome in nocturnal enuresis.

    Science.gov (United States)

    Devlin, J B; O'Cathain, C

    1990-01-01

    A presenting sample of 127 consecutive referrals to a community based enuresis clinic were evaluated after treatment with baseline behavioural recording and the enuresis alarm. Almost one in five became dry after baseline recording only while 81 of 96 (84%) enuretics who used the alarm achieved the initial dryness criterion. Successful outcome was associated with the absence of adverse environmental factors and psychiatric disorders in the child. A logistic regression procedure enabled a risk score to be created so that successful outcome could be predicted. Psychiatric disorder in the child, family stress, and the degree of concern shown by the child emerged as the most important prognostic factors in the treatment of enuresis. The favourable success rates with baseline recording and the enuresis alarm confirm the role of conditioning treatment at the forefront of management of enuresis and the risk score allows outcome to be predicted for the first time. PMID:2248510

  20. Predictive Bayesian inference and dynamic treatment regimes.

    Science.gov (United States)

    Saarela, Olli; Arjas, Elja; Stephens, David A; Moodie, Erica E M

    2015-11-01

    While optimal dynamic treatment regimes (DTRs) can be estimated without specification of a predictive model, a model-based approach, combined with dynamic programming and Monte Carlo integration, enables direct probabilistic comparisons between the outcomes under the optimal DTR and alternative (dynamic or static) treatment regimes. The Bayesian predictive approach also circumvents problems related to frequentist estimators under the nonregular estimation problem. However, the model-based approach is susceptible to misspecification, in particular of the "null-paradox" type, which is due to the model parameters not having a direct causal interpretation in the presence of latent individual-level characteristics. Because it is reasonable to insist on correct inferences under the null of no difference between the alternative treatment regimes, we discuss how to achieve this through a "null-robust" reparametrization of the problem in a longitudinal setting. Since we argue that causal inference can be entirely understood as posterior predictive inference in a hypothetical population without covariate imbalances, we also discuss how controlling for confounding through inverse probability of treatment weighting can be justified and incorporated in the Bayesian setting. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Personalization of cancer treatment using predictive simulation.

    Science.gov (United States)

    Doudican, Nicole A; Kumar, Ansu; Singh, Neeraj Kumar; Nair, Prashant R; Lala, Deepak A; Basu, Kabya; Talawdekar, Anay A; Sultana, Zeba; Tiwari, Krishna Kumar; Tyagi, Anuj; Abbasi, Taher; Vali, Shireen; Vij, Ravi; Fiala, Mark; King, Justin; Perle, MaryAnn; Mazumder, Amitabha

    2015-02-01

    The personalization of cancer treatments implies the reconsideration of a one-size-fits-all paradigm. This move has spawned increased use of next generation sequencing to understand mutations and copy number aberrations in cancer cells. Initial personalization successes have been primarily driven by drugs targeting one patient-specific oncogene (e.g., Gleevec, Xalkori, Herceptin). Unfortunately, most cancers include a multitude of aberrations, and the overall impact on cancer signaling and metabolic networks cannot be easily nullified by a single drug. We used a novel predictive simulation approach to create an avatar of patient cancer cells using point mutations and copy number aberration data. Simulation avatars of myeloma patients were functionally screened using various molecularly targeted drugs both individually and in combination to identify drugs that are efficacious and synergistic. Repurposing of drugs that are FDA-approved or under clinical study with validated clinical safety and pharmacokinetic data can provide a rapid translational path to the clinic. High-risk multiple myeloma patients were modeled, and the simulation predictions were assessed ex vivo using patient cells. Here, we present an approach to address the key challenge of interpreting patient profiling genomic signatures into actionable clinical insights to make the personalization of cancer therapy a practical reality. Through the rational design of personalized treatments, our approach also targets multiple patient-relevant pathways to address the emergence of single therapy resistance. Our predictive platform identified drug regimens for four high-risk multiple myeloma patients. The predicted regimes were found to be effective in ex vivo analyses using patient cells. These multiple validations confirm this approach and methodology for the use of big data to create personalized therapeutics using predictive simulation approaches.

  2. Computational Ranking of Yerba Mate Small Molecules Based on Their Predicted Contribution to Antibacterial Activity against Methicillin-Resistant Staphylococcus aureus.

    Directory of Open Access Journals (Sweden)

    Caroline S Rempe

    Full Text Available The aqueous extract of yerba mate, a South American tea beverage made from Ilex paraguariensis leaves, has demonstrated bactericidal and inhibitory activity against bacterial pathogens, including methicillin-resistant Staphylococcus aureus (MRSA. The gas chromatography-mass spectrometry (GC-MS analysis of two unique fractions of yerba mate aqueous extract revealed 8 identifiable small molecules in those fractions with antimicrobial activity. For a more comprehensive analysis, a data analysis pipeline was assembled to prioritize compounds for antimicrobial testing against both MRSA and methicillin-sensitive S. aureus using forty-two unique fractions of the tea extract that were generated in duplicate, assayed for activity, and analyzed with GC-MS. As validation of our automated analysis, we checked our predicted active compounds for activity in literature references and used authentic standards to test for antimicrobial activity. 3,4-dihydroxybenzaldehyde showed the most antibacterial activity against MRSA at low concentrations in our bioassays. In addition, quinic acid and quercetin were identified using random forests analysis and 5-hydroxy pipecolic acid was identified using linear discriminant analysis. We also generated a ranked list of unidentified compounds that may contribute to the antimicrobial activity of yerba mate against MRSA. Here we utilized GC-MS data to implement an automated analysis that resulted in a ranked list of compounds that likely contribute to the antimicrobial activity of aqueous yerba mate extract against MRSA.

  3. Low-rank coal research

    Energy Technology Data Exchange (ETDEWEB)

    Weber, G. F.; Laudal, D. L.

    1989-01-01

    This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

  4. Assessment of OPG/RANK/RANKL gene expression levels in peripheral blood mononuclear cells (PBMC) after treatment with strontium ranelate and ibandronate in patients with postmenopausal osteoporosis.

    Science.gov (United States)

    Stuss, Michal; Rieske, Piotr; Cegłowska, Agnieszka; Stêpień-Kłos, Wioletta; Liberski, Paweł P; Brzeziańska, Ewa; Sewerynek, Ewa

    2013-05-01

    Recent research results have confirmed the high significance of the OPG/RANK/RANKL system in the development of bone diseases. The aim of the reported study was to assess gene expression levels of the OPG/RANK/RANKL system in peripheral blood mononuclear cells (PBMCs) after strontium ranelate (SR) and ibandronate administered to patients with postmenopausal osteoporosis. A total of 89 postmenopausal women, aged 51 to 85 years, patients of the Outpatient Clinic of Osteoporosis of the Military Teaching Hospital in Lodz, were enrolled into the study. The patients were randomly assigned to different medical therapies: ibandronate and SR. Patients of the control group received only calcium and vitamin D₃ supplements. Patient visits were repeated after 3 and 6 months. Measurements of serum alkaline phosphatase concentrations and of RNA expression in PBMCs as well as of total serum calcium and phosphate levels and of their 24-hour urine excretion rates were carried out in material, collected at baseline and after 3 and 6 months of the therapy. Densitometry of the left hip and of the lumbar spine was done at the baseline visit and after 6 months. The differences in gene expressions of RANKL and RANK were not significant during the study period and did not differ between the groups in a statistically significant manner. No OPG gene expression was observed in PBMCs of patients in any of the studied groups and at any time point. The tendency of correlation (P = .07) was observed between decreasing RANK gene expression and increasing bone mineral density in the patients treated with SR. Both ibandronate and SR do not seem to cause any significant changes in gene expression levels of OPG/RANK/RANKL in PBMCs during the first 6 months of treatment.

  5. Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature ranking and a genetic algorithm.

    Science.gov (United States)

    Beheshti, Iman; Demirel, Hasan; Matsuda, Hiroshi

    2017-04-01

    We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking and a genetic algorithm to analyze structural magnetic resonance imaging data; using this system, we can predict conversion of mild cognitive impairment (MCI)-to-Alzheimer's disease (AD) at between one and three years before clinical diagnosis. The CAD system was developed in four stages. First, we used a voxel-based morphometry technique to investigate global and local gray matter (GM) atrophy in an AD group compared with healthy controls (HCs). Regions with significant GM volume reduction were segmented as volumes of interest (VOIs). Second, these VOIs were used to extract voxel values from the respective atrophy regions in AD, HC, stable MCI (sMCI) and progressive MCI (pMCI) patient groups. The voxel values were then extracted into a feature vector. Third, at the feature-selection stage, all features were ranked according to their respective t-test scores and a genetic algorithm designed to find the optimal feature subset. The Fisher criterion was used as part of the objective function in the genetic algorithm. Finally, the classification was carried out using a support vector machine (SVM) with 10-fold cross validation. We evaluated the proposed automatic CAD system by applying it to baseline values from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (160 AD, 162 HC, 65 sMCI and 71 pMCI subjects). The experimental results indicated that the proposed system is capable of distinguishing between sMCI and pMCI patients, and would be appropriate for practical use in a clinical setting. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Ranking library materials

    OpenAIRE

    Lewandowski, Dirk

    2015-01-01

    Purpose: This paper discusses ranking factors suitable for library materials and shows that ranking in general is a complex process and that ranking for library materials requires a variety of techniques. Design/methodology/approach: The relevant literature is reviewed to provide a systematic overview of suitable ranking factors. The discussion is based on an overview of ranking factors used in Web search engines. Findings: While there are a wide variety of ranking factors appl...

  7. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  8. Models Predicting Success of Infertility Treatment: A Systematic Review

    Science.gov (United States)

    Zarinara, Alireza; Zeraati, Hojjat; Kamali, Koorosh; Mohammad, Kazem; Shahnazari, Parisa; Akhondi, Mohammad Mehdi

    2016-01-01

    Background: Infertile couples are faced with problems that affect their marital life. Infertility treatment is expensive and time consuming and occasionally isn’t simply possible. Prediction models for infertility treatment have been proposed and prediction of treatment success is a new field in infertility treatment. Because prediction of treatment success is a new need for infertile couples, this paper reviewed previous studies for catching a general concept in applicability of the models. Methods: This study was conducted as a systematic review at Avicenna Research Institute in 2015. Six data bases were searched based on WHO definitions and MESH key words. Papers about prediction models in infertility were evaluated. Results: Eighty one papers were eligible for the study. Papers covered years after 1986 and studies were designed retrospectively and prospectively. IVF prediction models have more shares in papers. Most common predictors were age, duration of infertility, ovarian and tubal problems. Conclusion: Prediction model can be clinically applied if the model can be statistically evaluated and has a good validation for treatment success. To achieve better results, the physician and the couples’ needs estimation for treatment success rate were based on history, the examination and clinical tests. Models must be checked for theoretical approach and appropriate validation. The privileges for applying the prediction models are the decrease in the cost and time, avoiding painful treatment of patients, assessment of treatment approach for physicians and decision making for health managers. The selection of the approach for designing and using these models is inevitable. PMID:27141461

  9. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating e...... eigenvalues and eigenvectors. We give a number of different applications to regression and time series analysis, and show how the reduced rank regression estimator can be derived as a Gaussian maximum likelihood estimator. We briefly mention asymptotic results......The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  10. Dynamics of Ranking Processes in Complex Systems

    Science.gov (United States)

    Blumm, Nicholas; Ghoshal, Gourab; Forró, Zalán; Schich, Maximilian; Bianconi, Ginestra; Bouchaud, Jean-Philippe; Barabási, Albert-László

    2012-09-01

    The world is addicted to ranking: everything, from the reputation of scientists, journals, and universities to purchasing decisions is driven by measured or perceived differences between them. Here, we analyze empirical data capturing real time ranking in a number of systems, helping to identify the universal characteristics of ranking dynamics. We develop a continuum theory that not only predicts the stability of the ranking process, but shows that a noise-induced phase transition is at the heart of the observed differences in ranking regimes. The key parameters of the continuum theory can be explicitly measured from data, allowing us to predict and experimentally document the existence of three phases that govern ranking stability.

  11. Ranking Operations Management conferences

    NARCIS (Netherlands)

    Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

    2007-01-01

    Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

  12. Predicting treatment outcome by DNA and organoids

    NARCIS (Netherlands)

    Weeber, Fleur

    2017-01-01

    Tailoring treatment to the unique cancer of each individual patient is important to improve patient outcomes, facilitate drug development and increase cost-effectiveness in health care. This thesis describes several research projects focused on personalized medicine in cancer. The first part of this

  13. Pre-treatment amygdala volume predicts electroconvulsive therapy response

    NARCIS (Netherlands)

    ten Doesschate, Freek; van Eijndhoven, Philip; Tendolkar, Indira; van Wingen, Guido A.; van Waarde, Jeroen A.

    2014-01-01

    Electroconvulsive therapy (ECT) is an effective treatment for patients with severe depression. Knowledge on factors predicting therapeutic response may help to identify patients who will benefit most from the intervention. Based on the neuroplasticity hypothesis, volumes of the amygdala and

  14. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-04-17

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

  15. Predicting the effect of psychoeducational group treatment for hypochondriasis.

    NARCIS (Netherlands)

    Buwalda, F.M.; Bouman, T.K.

    2008-01-01

    Both individual cognitive-behavioural therapy and short-term psychoeducational courses have shown to be effective in reducing hypochondriacal complaints. However, it is unknown which patients benefit from treatment. The aim of the present study is to explore which variables predict treatment outcome

  16. A cognitive model for aggregating people's rankings

    National Research Council Canada - National Science Library

    Lee, Michael D; Steyvers, Mark; Miller, Brent

    2014-01-01

    .... Applications of the model to 23 data sets, dealing with general knowledge and prediction tasks, show that the model performs well in producing an aggregate ranking that is often close to the ground...

  17. Maximum Waring ranks of monomials

    OpenAIRE

    Holmes, Erik; Plummer, Paul; Siegert, Jeremy; Teitler, Zach

    2013-01-01

    We show that monomials and sums of pairwise coprime monomials in four or more variables have Waring rank less than the generic rank, with a short list of exceptions. We asymptotically compare their ranks with the generic rank.

  18. Enuresis - children's predictions of their treatment's progress and outcomes.

    Science.gov (United States)

    Ronen, Tammie; Hamama, Liat; Rosenbaum, Michael

    2013-01-01

    To investigate how nurses can use children's ability to predict treatment outcomes as a possible feature contributing to successful therapeutic processes targeting enuresis. Prediction of outcomes was viewed both as a self-efficacy component or belief (based on self-efficacy theory), and also as a skill for actually influencing change. The study was conducted in a mental health community center, located in a large city in central Israel, which was well known for treatment of children with enuresis. For the purpose of the study, the children and their parents completed three questionnaires and underwent training to maintain bedwetting records. The study compared three groups of children aged 8-14 years who: made predictions only at baseline (n = 32), predicted progress every week during treatment (n = 38), or did not use prediction at all (n = 31). Findings pinpointed the role of practice in improving predictions. Children who predicted weekly showed the highest congruence with outcomes. Based on self-efficacy, skills acquisition, and learning and training in the change process, nurses may help children overcome enuresis. © 2012 Blackwell Publishing Ltd.

  19. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    Science.gov (United States)

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. How to Rank Journals.

    Science.gov (United States)

    Bradshaw, Corey J A; Brook, Barry W

    2016-01-01

    There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

  1. Do Dimensions of TC Treatment Predict Retention and Outcomes?

    OpenAIRE

    Mandell, Wallace; Edelen, Maria O.; Wenzel, Suzanne L.; Dahl, James; Ebener, Patricia

    2008-01-01

    First week Dimensions of Change Instrument (DCI) assessments from a cohort of 519 adults entering six TCs were used to predict treatment retention and outcomes. More positive first week response to TC social processes, Community Responsibility; Resident Sharing Support and Enthusiasm; Group Process; and Clarity and Safety, and to one TC personal development process, Positive Self-Attitude and Commitment to Abstinence, predicted retention for the first month. Improvement at 30 days in Clarity ...

  2. 3P: Personalized Pregnancy Prediction in IVF Treatment Process

    Science.gov (United States)

    Uyar, Asli; Ciray, H. Nadir; Bener, Ayse; Bahceci, Mustafa

    We present an intelligent learning system for improving pregnancy success rate of IVF treatment. Our proposed model uses an SVM based classification system for training a model from past data and making predictions on implantation outcome of new embryos. This study employs an embryo-centered approach. Each embryo is represented with a data feature vector including 17 features related to patient characteristics, clinical diagnosis, treatment method and embryo morphological parameters. Our experimental results demonstrate a prediction accuracy of 82.7%. We have obtained the IVF dataset from Bahceci Women Health, Care Centre, in Istanbul, Turkey.

  3. Academic rankings: an approach to a Portuguese ranking

    OpenAIRE

    Bernardino, Pedro; Marques,Rui

    2009-01-01

    The academic rankings are a controversial subject in higher education. However, despite all the criticism, academic rankings are here to stay and more and more different stakeholders use rankings to obtain information about the institutions’ performance. The two most well-known rankings, The Times and the Shanghai Jiao Tong University rankings have different methodologies. The Times ranking is based on peer review, whereas the Shanghai ranking has only quantitative indicators and is mainly ba...

  4. Single-subject anxiety treatment outcome prediction using functional neuroimaging.

    Science.gov (United States)

    Ball, Tali M; Stein, Murray B; Ramsawh, Holly J; Campbell-Sills, Laura; Paulus, Martin P

    2014-04-01

    The possibility of individualized treatment prediction has profound implications for the development of personalized interventions for patients with anxiety disorders. Here we utilize random forest classification and pre-treatment functional magnetic resonance imaging (fMRI) data from individuals with generalized anxiety disorder (GAD) and panic disorder (PD) to generate individual subject treatment outcome predictions. Before cognitive behavioral therapy (CBT), 48 adults (25 GAD and 23 PD) reduced (via cognitive reappraisal) or maintained their emotional responses to negative images during fMRI scanning. CBT responder status was predicted using activations from 70 anatomically defined regions. The final random forest model included 10 predictors contributing most to classification accuracy. A similar analysis was conducted using the clinical and demographic variables. Activations in the hippocampus during maintenance and anterior insula, superior temporal, supramarginal, and superior frontal gyri during reappraisal were among the best predictors, with greater activation in responders than non-responders. The final fMRI-based model yielded 79% accuracy, with good sensitivity (0.86), specificity (0.68), and positive and negative likelihood ratios (2.73, 0.20). Clinical and demographic variables yielded poorer accuracy (69%), sensitivity (0.79), specificity (0.53), and likelihood ratios (1.67, 0.39). This is the first use of random forest models to predict treatment outcome from pre-treatment neuroimaging data in psychiatry. Together, random forest models and fMRI can provide single-subject predictions with good test characteristics. Moreover, activation patterns are consistent with the notion that greater activation in cortico-limbic circuitry predicts better CBT response in GAD and PD.

  5. A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

    Science.gov (United States)

    Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

    2017-01-01

    Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

  6. Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations.

    Science.gov (United States)

    Hoogendoorn, Mark; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

    2017-09-01

    Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients, we are able to show that we can predict therapy outcome with an area under the curve of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants, it is hard to generalize the results, but they do show great potential in this type of information.

  7. Predicting Social Anxiety Treatment Outcome based on Therapeutic Email Conversations

    NARCIS (Netherlands)

    Hoogendoorn, M.; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

    2016-01-01

    Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more

  8. Predicting Drug Court Treatment Completion Using the MMPI-2-RF

    Science.gov (United States)

    Mattson, Curtis; Powers, Bradley; Halfaker, Dale; Akeson, Steven; Ben-Porath, Yossef

    2012-01-01

    We examined the ability of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF; Ben-Porath & Tellegen, 2008) substantive scales to predict Drug Court treatment completion in a sample of individuals identified as being at risk for failure to complete the program. Higher scores on MMPI-2-RF scales…

  9. Ranking Economic History Journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    This study ranks - for the first time - 12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We...... also compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential...

  10. Ranking economic history journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    2010-01-01

    This study ranks-for the first time-12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We also...... compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential for economic...

  11. Recurrent fuzzy ranking methods

    Science.gov (United States)

    Hajjari, Tayebeh

    2012-11-01

    With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

  12. Preoperative distress predicts persistent pain after breast cancer treatment

    DEFF Research Database (Denmark)

    Mejdahl, Mathias Kvist; Mertz, Birgitte Goldschmidt; Bidstrup, Pernille Envold Hansen

    2015-01-01

    PURPOSE: Persistent pain after breast cancer treatment (PPBCT) affects 25% to 60% of breast cancer survivors and is recognized as a clinical problem, with 10% to 15% reporting moderate to severe pain several years after treatment. Psychological comorbidity is known to influence pain perception......, and evidence links signs of depression and anxiety with development of PPBCT. The purpose of this study was to assess preoperative distress as a predictive factor for development of PPBCT. METHODS: Between October 2008 and October 2009, 426 women diagnosed with primary breast cancer, undergoing surgery...... identification of patients at risk for PPBCT allows for further research in psychological and pharmacological treatment of this condition....

  13. Toward personalizing treatment for depression: predicting diagnosis and severity.

    Science.gov (United States)

    Huang, Sandy H; LePendu, Paea; Iyer, Srinivasan V; Tai-Seale, Ming; Carrell, David; Shah, Nigam H

    2014-01-01

    Depression is a prevalent disorder difficult to diagnose and treat. In particular, depressed patients exhibit largely unpredictable responses to treatment. Toward the goal of personalizing treatment for depression, we develop and evaluate computational models that use electronic health record (EHR) data for predicting the diagnosis and severity of depression, and response to treatment. We develop regression-based models for predicting depression, its severity, and response to treatment from EHR data, using structured diagnosis and medication codes as well as free-text clinical reports. We used two datasets: 35,000 patients (5000 depressed) from the Palo Alto Medical Foundation and 5651 patients treated for depression from the Group Health Research Institute. Our models are able to predict a future diagnosis of depression up to 12 months in advance (area under the receiver operating characteristic curve (AUC) 0.70-0.80). We can differentiate patients with severe baseline depression from those with minimal or mild baseline depression (AUC 0.72). Baseline depression severity was the strongest predictor of treatment response for medication and psychotherapy. It is possible to use EHR data to predict a diagnosis of depression up to 12 months in advance and to differentiate between extreme baseline levels of depression. The models use commonly available data on diagnosis, medication, and clinical progress notes, making them easily portable. The ability to automatically determine severity can facilitate assembly of large patient cohorts with similar severity from multiple sites, which may enable elucidation of the moderators of treatment response in the future. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  14. Ranking Adverse Drug Reactions With Crowdsourcing

    KAUST Repository

    Gottlieb, Assaf

    2015-03-23

    Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  15. Ranking adverse drug reactions with crowdsourcing.

    Science.gov (United States)

    Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

    2015-03-23

    There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  16. Intravoxel incoherent motion (IVIM histogram biomarkers for prediction of neoadjuvant treatment response in breast cancer patients

    Directory of Open Access Journals (Sweden)

    Gene Y. Cho

    Full Text Available Objective: To examine the prognostic capabilities of intravoxel incoherent motion (IVIM metrics and their ability to predict response to neoadjuvant treatment (NAT. Additionally, to observe changes in IVIM metrics between pre- and post-treatment MRI. Methods: This IRB-approved, HIPAA-compliant retrospective study observed 31 breast cancer patients (32 lesions. Patients underwent standard bilateral breast MRI along with diffusion-weighted imaging before and after NAT. Six patients underwent an additional IVIM-MRI scan 12–14 weeks after initial scan and 2 cycles of treatment. In addition to apparent diffusion coefficients (ADC from monoexponential decay, IVIM mean values (tissue diffusivity Dt, perfusion fraction fp, and pseudodiffusivity Dp and histogram metrics were derived using a biexponential model. An additional filter identified voxels of highly vascular tumor tissue (VTT, excluding necrotic or normal tissue. Clinical data include histology of biopsy and clinical response to treatment through RECIST assessment. Comparisons of treatment response were made using Wilcoxon rank-sum tests. Results: Average, kurtosis, and skewness of pseudodiffusion Dp significantly differentiated RECIST responders from nonresponders. ADC and Dt values generally increased (∼70% and VTT% values generally decreased (∼20% post-treatment. Conclusion: Dp metrics showed prognostic capabilities; slow and heterogeneous pseudodiffusion offer poor prognosis. Baseline ADC/Dt parameters were not significant predictors of response. This work suggests that IVIM mean values and heterogeneity metrics may have prognostic value in the setting of breast cancer NAT. Keywords: Breast cancer, Diffusion weighted MRI, Intravoxel incoherent motion, Neoadjuvant treatment, Response evaluation criteria in solid tumors

  17. Asset ranking manager (ranking index of components)

    Energy Technology Data Exchange (ETDEWEB)

    Maloney, S.M.; Engle, A.M.; Morgan, T.A. [Applied Reliability, Maracor Software and Engineering (United States)

    2004-07-01

    The Ranking Index of Components (RIC) is an Asset Reliability Manager (ARM), which itself is a Web Enabled front end where plant database information fields from several disparate databases are combined. That information is used to create a specific weighted number (Ranking Index) relating to that components health and risk to the site. The higher the number, the higher priority that any work associated with that component receives. ARM provides site Engineering, Maintenance and Work Control personnel with a composite real time - (current condition) look at the components 'risk of not working' to the plant. Information is extracted from the existing Computerized Maintenance management System (CMMS) and specific site applications and processed nightly. ARM helps to ensure that the most important work is placed into the workweeks and the non value added work is either deferred, frequency changed or deleted. This information is on the web, updated each night, and available for all employees to use. This effort assists the work management specialist when allocating limited resources to the most important work. The use of this tool has maximized resource usage, performing the most critical work with available resources. The ARM numbers are valued inputs into work scoping for the workweek managers. System and Component Engineers are using ARM to identify the components that are at 'risk of failure' and therefore should be placed into the appropriate work week schedule.

  18. Multiplex PageRank.

    Directory of Open Access Journals (Sweden)

    Arda Halu

    Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  19. Multiplex PageRank.

    Science.gov (United States)

    Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

    2013-01-01

    Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  20. Ranking of Rankings: Benchmarking Twenty-Five Higher Education Ranking Systems in Europe

    Science.gov (United States)

    Stolz, Ingo; Hendel, Darwin D.; Horn, Aaron S.

    2010-01-01

    The purpose of this study is to evaluate the ranking practices of 25 European higher education ranking systems (HERSs). Ranking practices were assessed with 14 quantitative measures derived from the Berlin Principles on Ranking of Higher Education Institutions (BPs). HERSs were then ranked according to their degree of congruence with the BPs.…

  1. Prediction of heat treatment in food processing machinery

    DEFF Research Database (Denmark)

    Karlson, Torben; Friis, Alan; Szabo, Peter

    1997-01-01

    The velocity and temperature fields of a shear thinning fluid in a co-rotating disc scraped surface heat exchanger (CDHE) are calculated using the finite element method. By tracking and timingparticles through the heat exchanger residence time and thermal time distributions are computed....... The residence time distributions are compared to experimentally obtained distributions. A prediction of the heat treatment of the fluid passing through several heat exchangers inseries is obtained using the thermal time distributions....

  2. From rankings to mission.

    Science.gov (United States)

    Kirch, Darrell G; Prescott, John E

    2013-08-01

    Since the 1980s, school ranking systems have been a topic of discussion among leaders of higher education. Various ranking systems are based on inadequate data that fail to illustrate the complex nature and special contributions of the institutions they purport to rank, including U.S. medical schools, each of which contributes uniquely to meeting national health care needs. A study by Tancredi and colleagues in this issue of Academic Medicine illustrates the limitations of rankings specific to primary care training programs. This commentary discusses, first, how each school's mission and strengths, as well as the impact it has on the community it serves, are distinct, and, second, how these schools, which are each unique, are poorly represented by overly subjective ranking methodologies. Because academic leaders need data that are more objective to guide institutional development, the Association of American Medical Colleges (AAMC) has been developing tools to provide valid data that are applicable to each medical school. Specifically, the AAMC's Medical School Admissions Requirements and its Missions Management Tool each provide a comprehensive assessment of medical schools that leaders are using to drive institutional capacity building. This commentary affirms the importance of mission while challenging the leaders of medical schools, teaching hospitals, and universities to use reliable data to continually improve the quality of their training programs to improve the health of all.

  3. Dynamic Matrix Rank

    DEFF Research Database (Denmark)

    Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

    2009-01-01

    We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

  4. Predicting the residual aluminum level in water treatment process

    Directory of Open Access Journals (Sweden)

    J. Tomperi

    2013-06-01

    Full Text Available In water treatment processes, aluminum salts are widely used as coagulation chemical. High dose of aluminum has been proved to be at least a minor health risk and some evidence points out that aluminum could increase the risk of Alzheimer's disease. Thus it is important to minimize the amount of residual aluminum in drinking water and water used at food industry. In this study, the data of a water treatment plant (WTP was analyzed and the residual aluminum in drinking water was predicted using Multiple Linear Regression (MLR and Artificial Neural Network (ANN models. The purpose was to find out which variables affect the amount of residual aluminum and create simple and reliable prediction models which can be used in an early warning system (EWS. Accuracy of ANN and MLR models were compared. The new nonlinear scaling method based on generalized norms and skewness was used to scale all measurement variables to range [−2...+2] before data-analysis and modeling. The effect of data pre-processing was studied by comparing prediction results to ones achieved in an earlier study. Results showed that it is possible to predict the baseline level of residual aluminum in drinking water with a simple model. Variables that affected the most the amount of residual aluminum were among others: raw water temperature, raw water KMnO4 and PAC/KMnO4 (Poly-Aluminum Chloride/Potassium permanganate-ratio. The accuracies of MLR and ANN models were found to be almost the same. Study also showed that data pre-processing affects to the final prediction result.

  5. Ranking beta sheet topologies of proteins

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2010-01-01

    One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all beta-topologies (partitions of beta-strands into sheets, orderings of strands within sheets and orientations...... of paired strands) of a given protein. We show that the beta-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many beta-strands. The results reported...... in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked beta-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly...

  6. Diversifying customer review rankings.

    Science.gov (United States)

    Krestel, Ralf; Dokoohaki, Nima

    2015-06-01

    E-commerce Web sites owe much of their popularity to consumer reviews accompanying product descriptions. On-line customers spend hours and hours going through heaps of textual reviews to decide which products to buy. At the same time, each popular product has thousands of user-generated reviews, making it impossible for a buyer to read everything. Current approaches to display reviews to users or recommend an individual review for a product are based on the recency or helpfulness of each review. In this paper, we present a framework to rank product reviews by optimizing the coverage of the ranking with respect to sentiment or aspects, or by summarizing all reviews with the top-K reviews in the ranking. To accomplish this, we make use of the assigned star rating for a product as an indicator for a review's sentiment polarity and compare bag-of-words (language model) with topic models (latent Dirichlet allocation) as a mean to represent aspects. Our evaluation on manually annotated review data from a commercial review Web site demonstrates the effectiveness of our approach, outperforming plain recency ranking by 30% and obtaining best results by combining language and topic model representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. OutRank

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

    2008-01-01

    Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

  8. An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

    Science.gov (United States)

    Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady

    2017-09-01

    Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights

  9. Prediction of Chinese green tea ranking by metabolite profiling using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS).

    Science.gov (United States)

    Jing, Jin; Shi, Yuanzhi; Zhang, Qunfeng; Wang, Jie; Ruan, Jianyun

    2017-04-15

    Metabolomics profiling provides comprehensive picture of the chemical composition in teas therefore may be used to assess tea quality objectively and reliably. In the present experiment, water and methanol extracts of green teas from China were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) with the objectives to establish a model for quality prediction and to identify potential marker metabolites. The blindly evaluated sensory score of green teas was predicted with excellent power (R(2)=0.87 and Q(2)=0.82) and accuracy (RMSEP=1.36) by a partial least-squares (PLS) regression model based on water extract. By contrast, methanol extract failed to reasonably predict the sensory scores. The levels in water extract of neotheaflavin, neotheaflavin 3-O-gallate, trigalloyl-β-d-glucopyranose, myricetin 3,3'-digalactoside, catechin-(4α→8)-epigallocatechin and kaempferol were significantly larger whereas those of theogallin and gallocatechin were less in the low (score<87) than in the high score (⩾90) group. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Prediction and tolerance intervals for dynamic treatment regimes.

    Science.gov (United States)

    Lizotte, Daniel J; Tahmasebi, Arezoo

    2017-08-01

    We develop and evaluate tolerance interval methods for dynamic treatment regimes (DTRs) that can provide more detailed prognostic information to patients who will follow an estimated optimal regime. Although the problem of constructing confidence intervals for DTRs has been extensively studied, prediction and tolerance intervals have received little attention. We begin by reviewing in detail different interval estimation and prediction methods and then adapting them to the DTR setting. We illustrate some of the challenges associated with tolerance interval estimation stemming from the fact that we do not typically have data that were generated from the estimated optimal regime. We give an extensive empirical evaluation of the methods and discussed several practical aspects of method choice, and we present an example application using data from a clinical trial. Finally, we discuss future directions within this important emerging area of DTR research.

  11. Executive Functioning at Baseline Prospectively Predicts Depression Treatment Response.

    Science.gov (United States)

    Dawson, Erica L; Caveney, Angela F; Meyers, Kortni K; Weisenbach, Sara L; Giordani, Bruno; Avery, Erich T; Schallmo, Michael-Paul; Bahadori, Armita; Bieliauskas, Linas A; Mordhorst, Matthew; Marcus, Sheila M; Kerber, Kevin; Zubieta, Jon-Kar; Langenecker, Scott A

    2017-02-09

    Existing cognitive and clinical predictors of treatment response to date are not of sufficient strength to meaningfully impact treatment decision making and are not readily employed in clinical settings. This study investigated whether clinical and cognitive markers used in a tertiary care clinic could predict response to usual treatment over a period of 4 to 6 months in a sample of 75 depressed adults. Patients (N = 384) were sequentially tested in 2 half-day clinics as part of a quality improvement project at an outpatient tertiary care center between August 2003 and September 2007; additional subjects evaluated in the clinic between 2007 and 2009 were also included. Diagnosis was according to DSM-IV-TR criteria and completed by residents and attending faculty. Test scores obtained at intake visits on a computerized neuropsychological screening battery were the Parametric Go/No-Go task and Facial Emotion Perception Task. Treatment outcome was assessed using 9-item Patient Health Questionnaire (PHQ-9) self-ratings at follow-up (n = 75). Usual treatment included psychotropic medication and psychotherapy. Decline in PHQ-9 scores was predicted on the basis of baseline PHQ-9 score and education, with neuropsychological variables entered in the second step. PHQ-9 scores declined by 46% at follow-up (56% responders). Using 2-step multiple regression, baseline PHQ-9 score (P ≤ .05) and education (P ≤ .01) were significant step 1 predictors of percent change in PHQ-9 follow-up scores. In step 2 of the model, faster processing speed with interference resolution (go reaction time) independently explained a significant amount of variance over and above variables in step 1 (12% of variance, P < .01), while other cognitive and affective skills did not. This 2-step model accounted for 28% of the variance in treatment change in PHQ-9 scores. Processing speed with interference resolution also accounted for 12% variance in treatment and follow-up attrition. Use of executive

  12. Improving Ranking Using Quantum Probability

    OpenAIRE

    Melucci, Massimo

    2011-01-01

    The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

  13. Model prediction for ranking lead-acid batteries according to expected lifetime in renewable energy systems and autonomous power-supply systems

    DEFF Research Database (Denmark)

    Schiffer, J.; Sauer, D.U.; Bindner, Henrik W.

    2007-01-01

    -of-discharge, the current rate, the existing acid stratification, and the time since the last full charging. The actual Ah throughput is continuously multiplied by a weight factor that represents the actual operating conditions. Even though the modelling approach is mainly heuristic, all of the effects that are taken......Predicting the lifetime of lead-acid batteries in applications with irregular operating conditions such as partial state-of-charge cycling, varying depth-of-discharge and different times between full charging is known as a difficult task. Experimental investigations in the laboratory are difficult...... because each application has its own specific operation profile. Therefore, an experimental investigation is necessary for each application and, moreover, for each operation strategy. This paper presents a lifetime model that allows comparison of the impact of different operating conditions, different...

  14. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating the parame......We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  15. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

    Science.gov (United States)

    Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

    2017-05-22

    PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age

  16. Predictive factors to targeted treatment in gastrointestinal carcinomas.

    Science.gov (United States)

    Silvestris, Nicola; Marech, Ilaria; Brunetti, Anna Elisabetta; Azzariti, Amalia; Numico, Gianmauro; Cicero, Giuseppe; Delcuratolo, Sabina; De Luca, Raffaele; Burz, Claudia; Lorusso, Vito

    2014-01-01

    Most cancers are traditionally treated with either chemotherapeutic agents, radiotherapy, or both. Identification of specific molecular characteristics of tumors and the advent of molecular-targeted drugs not only enhance the efficacy but also decrease the toxicity of treatment. These new therapies may target pathways critical to tumor development or specific driver mutations in cancer cells. This understanding of the molecular pathways of cancer cells has led to the ability to predict cancer development, behaviour and prognosis, as well as response or resistance to current therapeutic agents. As a result, pathologic analyses play a vital role in the detection of cancer biomarkers, which are important not only in the diagnosis of cancers but also in the selection of appropriate therapeutic agents and in the development of new targeted therapies.

  17. Can College Rankings Be Believed?

    Directory of Open Access Journals (Sweden)

    Meredith Davis

    Full Text Available The article summarizes literature on college and university rankings worldwide and the strategies used by various ranking organizations, including those of government and popular media. It traces the history of national and global rankings, indicators used by ranking systems, and the effect of rankings on academic programs and their institutions. Although ranking systems employ diverse criteria and most weight certain indicators over others, there is considerable skepticism that most actually measure educational quality. At the same time, students and their families increasingly consult these evaluations when making college decisions, and sponsors of faculty research consider reputation when forming academic partnerships. While there are serious concerns regarding the validity of ranking institutions when so little data can support differences between one institution and another, college rankings appear to be here to stay.

  18. Ranking Baltic States Researchers

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2017-10-01

    Full Text Available In this article, using the h-index and the total number of citations, the best 10 Lithuanian, Latvian and Estonian researchers from several disciplines are ranked. The list may be formed based on the h-index and the total number of citations, given in Web of Science, Scopus, Publish or Perish Program and Google Scholar database. Data for the first 10 researchers are presented. Google Scholar is the most complete. Therefore, to define a single indicator, h-index calculated by Google Scholar may be a good and simple one. The author chooses the Google Scholar database as it is the broadest one.

  19. Sync-rank: Robust Ranking, Constrained Ranking and Rank Aggregation via Eigenvector and SDP Synchronization

    Science.gov (United States)

    2015-04-28

    eigenvector of the associated Laplacian matrix (i.e., the Fiedler vector) matches that of the variables. In other words, this approach (reminiscent of...S1), i.e., Dii = ∑n j=1Gi,j is the degree of node i in the measurement graph G. 3: Compute the Fiedler vector of S (eigenvector corresponding to the...smallest nonzero eigenvalue of LS). 4: Output the ranking induced by sorting the Fiedler vector of S, with the global ordering (increasing or decreasing

  20. Rankings from Fuzzy Pairwise Comparisons

    NARCIS (Netherlands)

    van den Broek, P.M.; Noppen, J.A.R.; Mohammadian, M.

    2006-01-01

    We propose a new method for deriving rankings from fuzzy pairwise comparisons. It is based on the observation that quantification of the uncertainty of the pairwise comparisons should be used to obtain a better crisp ranking, instead of a fuzzified version of the ranking obtained from crisp pairwise

  1. PageRank (II): Mathematics

    African Journals Online (AJOL)

    maths/stats

    INTRODUCTION. PageRank is Google's system for ranking web pages. A page with a higher PageRank is deemed more important and is more likely to be listed above a ... Felix U. Ogban, Department of Mathematics/Statistics and Computer Science, Faculty of Science, University of ..... probability, 2004, 41, (3): 721-734.

  2. University Rankings and Social Science

    Science.gov (United States)

    Marginson, Simon

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

  3. Can hematologic parameters predict treatment of ectopic pregnancy?

    Science.gov (United States)

    Akkaya, Hatice; Uysal, Gulsum

    2017-01-01

    Ectopic pregnancy (EP) is the major cause of maternal morbidity and mortalityinthe first trimester of pregnancy. EP can be treated either medical or surgical approches. The purpose of our study wasto predict the treatment choice of tubal EP by usinghematologic parameters which are routinely used in clinical practice. After retrospectively data evaluation was done from Januaryu 2014 to Deceber 201. we had 153 patients with EP. Patientsadmitted to methotrexate (MTX) therapy was Group-1. Patients performed surgerywas Group-II. All patients' initial values including white blood cell (WBC), hemoglobin (Hgb), mean corpuscular volume (MCV), neutrophil and lymphocyte, neutrophil lymphocyte ratio (NLR), platelet, platelet lymphocyte ratio (PLR), red cell distribution width (RDW), platelet distribution width (PDW) and mean platelet volume (MPV)were recorded and compared between groups. Of 153 EP patients, there were 93 patients in MTX group and 60 patients in surgery group. RDW, MPV were significantly increased in MTX group (p=0.003, p=0.001, p=0.038, respectively). However, no statistically significant difference was observed between the groups in terms of WBC, Hgb, MCV, PLT, PLR, PDW. RDW, MPV values were independently associated with MTX therapy. Hematologic parameters can be helpful in the choice of the EP treatment.

  4. Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.

    Science.gov (United States)

    Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted

    2017-01-01

    Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.

  5. Ranking schools on external knowledge tests results

    Directory of Open Access Journals (Sweden)

    Gašper Cankar

    2007-01-01

    Full Text Available The paper discusses the use of external knowledge test results for school ranking and the implicit effect of such ranking. A question of validity is raised and a review of research literature and main known problems are presented. In many western countries publication of school results is a common practice and a similar trend can be observed in Slovenia. Experiences of other countries help to predict positive and negative aspects of such publication. Results of external knowledge tests produce very limited information about school quality—if we use other sources of information our ranking of schools can be very different. Nevertheless, external knowledge tests can yield useful information. If we want to improve quality in schools, we must allow schools to use this information themselves and improve from within. Broad public scrutiny is unnecessary and problematic—it moves the focus of school efforts from real improvement of quality to mere improvement of the school public image.

  6. A Cognitive Model for Aggregating People's Rankings

    Science.gov (United States)

    Lee, Michael D.; Steyvers, Mark; Miller, Brent

    2014-01-01

    We develop a cognitive modeling approach, motivated by classic theories of knowledge representation and judgment from psychology, for combining people's rankings of items. The model makes simple assumptions about how individual differences in knowledge lead to observed ranking data in behavioral tasks. We implement the cognitive model as a Bayesian graphical model, and use computational sampling to infer an aggregate ranking and measures of the individual expertise. Applications of the model to 23 data sets, dealing with general knowledge and prediction tasks, show that the model performs well in producing an aggregate ranking that is often close to the ground truth and, as in the “wisdom of the crowd” effect, usually performs better than most of individuals. We also present some evidence that the model outperforms the traditional statistical Borda count method, and that the model is able to infer people's relative expertise surprisingly well without knowing the ground truth. We discuss the advantages of the cognitive modeling approach to combining ranking data, and in wisdom of the crowd research generally, as well as highlighting a number of potential directions for future model development. PMID:24816733

  7. Predictive models in the diagnosis and treatment of autoimmune epilepsy.

    Science.gov (United States)

    Dubey, Divyanshu; Singh, Jaysingh; Britton, Jeffrey W; Pittock, Sean J; Flanagan, Eoin P; Lennon, Vanda A; Tillema, Jan-Mendelt; Wirrell, Elaine; Shin, Cheolsu; So, Elson; Cascino, Gregory D; Wingerchuk, Dean M; Hoerth, Matthew T; Shih, Jerry J; Nickels, Katherine C; McKeon, Andrew

    2017-07-01

    To validate predictive models for neural antibody positivity and immunotherapy response in epilepsy. We conducted a retrospective study of epilepsy cases at Mayo Clinic (Rochester-MN; Scottsdale-AZ, and Jacksonville-FL) in whom autoimmune encephalopathy/epilepsy/dementia autoantibody testing profiles were requested (06/30/2014-06/30/2016). An Antibody Prevalence in Epilepsy (APE) score, based on clinical characteristics, was assigned to each patient. Among patients who received immunotherapy, a Response to Immunotherapy in Epilepsy (RITE) score was assigned. Favorable seizure outcome was defined as >50% reduction of seizure frequency at the first follow-up. Serum and cerebrospinal fluid (CSF) from 1,736 patients were sent to the Mayo Clinic Neuroimmunology Laboratory for neural autoantibody evaluation. Three hundred eighty-seven of these patients met the diagnostic criteria for epilepsy. Central nervous system (CNS)-specific antibodies were detected in 44 patients. Certain clinical features such as new-onset epilepsy, autonomic dysfunction, viral prodrome, faciobrachial dystonic seizures/oral dyskinesia, inflammatory CSF profile, and mesial temporal magnetic resonance imaging (MRI) abnormalities had a significant association with positive antibody results. A significantly higher proportion of antibody-positive patients had an APE score ≥4 (97.7% vs. 21.6%, p < 0.01). Sensitivity and specificity of an APE score ≥4 to predict presence of specific neural auto-antibody were 97.7% and 77.9%, respectively. In the subset of patients who received immunotherapy (77), autonomic dysfunction, faciobrachial dystonic seizures/oral dyskinesia, early initiation of immunotherapy, and presence of antibodies targeting plasma membrane proteins (cell-surface antigens) were associated with favorable seizure outcome. Sensitivity and specificity of a RITE score ≥7 to predict favorable seizure outcome were 87.5% and 83.8%, respectively. APE and RITE scores can aid diagnosis

  8. Ranking REACH registered neutral, ionizable and ionic organic chemicals based on their aquatic persistency and mobility.

    Science.gov (United States)

    Arp, H P H; Brown, T N; Berger, U; Hale, S E

    2017-07-19

    The contaminants that have the greatest chances of appearing in drinking water are those that are mobile enough in the aquatic environment to enter drinking water sources and persistent enough to survive treatment processes. Herein a screening procedure to rank neutral, ionizable and ionic organic compounds for being persistent and mobile organic compounds (PMOCs) is presented and applied to the list of industrial substances registered under the EU REACH legislation as of December 2014. This comprised 5155 identifiable, unique organic structures. The minimum cut-off criteria considered for PMOC classification herein are a freshwater half-life >40 days, which is consistent with the REACH definition of freshwater persistency, and a log Doc organic carbon-water distribution coefficient). Experimental data were given the highest priority, followed by data from an array of available quantitative structure-activity relationships (QSARs), and as a third resort, an original Iterative Fragment Selection (IFS) QSAR. In total, 52% of the unique REACH structures made the minimum criteria to be considered a PMOC, and 21% achieved the highest PMOC ranking (half-life > 40 days, log Doc < 1.0 between pH 4-10). Only 9% of neutral substances received the highest PMOC ranking, compared to 30% of ionizable compounds and 44% of ionic compounds. Predicted hydrolysis products for all REACH parents (contributing 5043 additional structures) were found to have higher PMOC rankings than their parents, due to increased mobility but not persistence. The fewest experimental data available were for ionic compounds; therefore, their ranking is more uncertain than neutral and ionizable compounds. The most sensitive parameter for the PMOC ranking was freshwater persistency, which was also the parameter that QSARs performed the most poorly at predicting. Several prioritized drinking water contaminants in the EU and USA, and other contaminants of concern, were identified as PMOCs. This

  9. Ranking nodes in growing networks: When PageRank fails.

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-10

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  10. Post-treatment changes of tumour perfusion parameters can help to predict survival in patients with high-grade astrocytoma

    Energy Technology Data Exchange (ETDEWEB)

    Sanz-Requena, Roberto; Marti-Bonmati, Luis [Hospital Quironsalud Valencia, Radiology Department, Valencia (Spain); Hospital Universitari i Politecnic La Fe, Grupo de Investigacion Biomedica en Imagen, Valencia (Spain); Revert-Ventura, Antonio J.; Salame-Gamarra, Fares [Hospital de Manises, Radiology Department, Manises (Spain); Garcia-Marti, Gracian [Hospital Quironsalud Valencia, Radiology Department, Valencia (Spain); Hospital Universitari i Politecnic La Fe, Grupo de Investigacion Biomedica en Imagen, Valencia (Spain); CIBER-SAM, Instituto de Salud Carlos III, Madrid (Spain); Perez-Girbes, Alexandre [Hospital Universitari i Politecnic La Fe, Grupo de Investigacion Biomedica en Imagen, Valencia (Spain); Molla-Olmos, Enrique [Hospital La Ribera, Radiology Department, Alzira (Spain)

    2017-08-15

    Vascular characteristics of tumour and peritumoral volumes of high-grade gliomas change with treatment. This work evaluates the variations of T2*-weighted perfusion parameters as overall survival (OS) predictors. Forty-five patients with histologically confirmed high-grade astrocytoma (8 grade III and 37 grade IV) were included. All patients underwent pre- and post-treatment T2*-weighted contrast-enhanced magnetic resonance (MR) imaging. Tumour, peritumoral and control volumes were segmented. Relative variations of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), K{sup trans-T2*}, k{sub ep-T2*}, v{sub e-T2*} and v{sub p-T2*} were calculated. Differences regarding tumour grade and surgical resection extension were evaluated with ANOVA tests. For each parameter, two groups were defined by non-supervised clusterisation. Survival analysis were performed on these groups. For the tumour region, the 90th percentile increase or stagnation of CBV was associated with shorter survival, while a decrease related to longer survival (393 ± 189 vs 594 ± 294 days; log-rank p = 0.019; Cox hazard-ratio, 2.31; 95% confidence interval [CI], 1.12-4.74). K{sup trans-T2*} showed similar results (414 ± 177 vs 553 ± 312 days; log-rank p = 0.037; hazard-ratio, 2.19; 95% CI, 1.03-4.65). The peritumoral area values showed no relationship with OS. Post-treatment variations of the highest CBV and K{sup trans-T2*} values in the tumour volume are predictive factors of OS in patients with high-grade gliomas. (orig.)

  11. International Study to Predict Optimized Treatment for Depression (iSPOT-D, a randomized clinical trial: rationale and protocol

    Directory of Open Access Journals (Sweden)

    Cooper Nicholas J

    2011-01-01

    : NCT00693849 URL: http://clinicaltrials.gov/ct2/show/NCT00693849?term=International+Study+to+Predict+Optimized+Treatment+for+Depression&rank=1

  12. Neophilia Ranking of Scientific Journals

    Science.gov (United States)

    Packalen, Mikko; Bhattacharya, Jay

    2017-01-01

    The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)—these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work. PMID:28713181

  13. Wikipedia ranking of world universities

    Science.gov (United States)

    Lages, José; Patt, Antoine; Shepelyansky, Dima L.

    2016-03-01

    We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

  14. Inhibition of osteoclastogenesis by RNA interference targeting RANK

    Directory of Open Access Journals (Sweden)

    Ma Ruofan

    2012-08-01

    Full Text Available Abstract Background Osteoclasts and osteoblasts regulate bone resorption and formation to allow bone remodeling and homeostasis. The balance between bone resorption and formation is disturbed by abnormal recruitment of osteoclasts. Osteoclast differentiation is dependent on the receptor activator of nuclear factor NF-kappa B (RANK ligand (RANKL as well as the macrophage colony-stimulating factor (M-CSF. The RANKL/RANK system and RANK signaling induce osteoclast formation mediated by various cytokines. The RANK/RANKL pathway has been primarily implicated in metabolic, degenerative and neoplastic bone disorders or osteolysis. The central role of RANK/RANKL interaction in osteoclastogenesis makes RANK an attractive target for potential therapies in treatment of osteolysis. The purpose of this study was to assess the effect of inhibition of RANK expression in mouse bone marrow macrophages on osteoclast differentiation and bone resorption. Methods Three pairs of short hairpin RNAs (shRNA targeting RANK were designed and synthesized. The optimal shRNA was selected among three pairs of shRNAs by RANK expression analyzed by Western blot and Real-time PCR. We investigated suppression of osteoclastogenesis of mouse bone marrow macrophages (BMMs using the optimal shRNA by targeting RANK. Results Among the three shRANKs examined, shRANK-3 significantly suppressed [88.3%] the RANK expression (p Conclusions These findings suggest that retrovirus-mediated shRNA targeting RANK inhibits osteoclast differentiation and osteolysis. It may appear an attractive target for preventing osteolysis in humans with a potential clinical application.

  15. Which set of embryo variables is most predictive for live birth? A prospective study in 6252 single embryo transfers to construct an embryo score for the ranking and selection of embryos.

    Science.gov (United States)

    Rhenman, A; Berglund, L; Brodin, T; Olovsson, M; Milton, K; Hadziosmanovic, N; Holte, J

    2015-01-01

    Which embryo score variables are most powerful for predicting live birth after single embryo transfer (SET) at the early cleavage stage? This large prospective study of visual embryo scoring variables shows that blastomere number (BL), the proportion of mononucleated blastomeres (NU) and the degree of fragmentation (FR) have independent prognostic power to predict live birth. Other studies suggest prognostic power, at least univariately and for implantation potential, for all five variables. A previous study from the same centre on double embryo transfers with implantation as the end-point resulted in the integrated morphology cleavage (IMC) score, which incorporates BL, NU and EQ. A prospective cohort study of IVF/ICSI SET on Day 2 (n = 6252) during a 6-year period (2006-2012). The five variables (BL NU, FR, EQ and symmetry of cleavage (SY)) were scored in 3- to 5-step scales and subsequently related to clinical pregnancy and LBR. A total of 4304 women undergoing IVF/ICSI in a university-affiliated private fertility clinic were included. Generalized estimating equation models evaluated live birth (yes/no) as primary outcome using the embryo variables as predictors. Odds ratios with 95% confidence intervals and P-values were presented for each predictor. The C statistic (i.e. area under receiver operating characteristic curve) was calculated for each model. Model calibration was assessed with the Hosmer-Lemeshow test. A shrinkage method was applied to remove bias in c statistics due to over-fitting. LBR was 27.1% (1693/6252). BL, NU, FR and EQ were univariately highly significantly associated with LBR. In a multivariate model, BL, NU and FR were independently significant, with c statistic 0.579 (age-adjusted c statistic 0.637). EQ did not retain significance in the multivariate model. Prediction model calibration was good for both pregnancy and live birth. We present a ranking tree with combinations of values of the BL, NU and FR embryo variables for optimal

  16. Statistical methods for ranking data

    CERN Document Server

    Alvo, Mayer

    2014-01-01

    This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

  17. Ranking nodes in growing networks: When PageRank fails

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-01

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  18. University Rankings in Critical Perspective

    Science.gov (United States)

    Pusser, Brian; Marginson, Simon

    2013-01-01

    This article addresses global postsecondary ranking systems by using critical-theoretical perspectives on power. This research suggests rankings are at once a useful lens for studying power in higher education and an important instrument for the exercise of power in service of dominant norms in global higher education. (Contains 1 table and 1…

  19. University Ranking as Social Exclusion

    Science.gov (United States)

    Amsler, Sarah S.; Bolsmann, Chris

    2012-01-01

    In this article we explore the dual role of global university rankings in the creation of a new, knowledge-identified, transnational capitalist class and in facilitating new forms of social exclusion. We examine how and why the practice of ranking universities has become widely defined by national and international organisations as an important…

  20. Post-treatment PET/CT and p16 status for predicting treatment outcomes in locally advanced head and neck cancer after definitive radiation

    Energy Technology Data Exchange (ETDEWEB)

    Awan, Musaddiq J.; Machtay, Mitchell; Yao, Min [Case Western Reserve University and University Hospitals, Department of Radiation Oncology, Cleveland, OH (United States); Lavertu, Pierre; Zender, Chad; Rezaee, Rod; Fowler, Nicole [University Hospitals, Department of Otolaryngology and Head and Neck Surgery, Cleveland, OH (United States); Karapetyan, Lilit; Gibson, Michael [University Hospitals, Department of Medical Oncology, Cleveland, OH (United States); Wasman, Jay [University Hospitals, Department of Pathology, Cleveland, OH (United States); Faulhaber, Peter [University Hospitals, Department of Nuclear Medicine and Radiology, Cleveland, OH (United States)

    2017-06-15

    To retrospectively review post-treatment (post-tx) FDG-PET/CT scans in patients with advanced head and neck squamous cell carcinoma (HNSCC) and known p16 status, treated with definitive (chemo)radiation (RT). A total of 108 eligible patients had N2A or greater HNSCC treated with chemoRT from August 1, 2008, to February 28, 2015, with post-tx PET/CT within 6 months after RT. Kaplan-Meier curves, log-rank statistics, and Cox proportional hazards regression were used for statistical analysis. Median follow-up was 2.38 years. Sixty-eight (63.0%) patients had p16+ and 40 (37.0%) had p16- status. Two-year overall survival and recurrence-free survival were 93.4% and 77.8%, respectively. The negative predictive value (NPV) of PET/CT for local recurrence (LR) was 100%. The NPV for regional recurrence (RR) was 96.5% for all patients, 100% for p16+ patients, and 88.5% for p16- patients. The positive predictive value (PPV) of PET/CT for recurrence was 77.3% for all patients, 50.0% for p16+, and 78.6% for p16-. The PPV for LR was 72.7% for all patients, 50.0% for p16+ patients, and 72.7% for p16- patients. The PPV for RR was 50.0% for all patients, 33% for p16+, and 66.6% for p16-. Post-tx PET/CT and p16 status were independent predictors of recurrence-free survival (p < 0.01). Post-tx PET/CT predicts treatment outcomes in both p16 + and p16- patients, and does so independently of p16 status. P16- patients with negative PET have a 10% risk of nodal recurrence, and closer follow-up in these patients is warranted. (orig.)

  1. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

  2. Performance of Remotely Controlled Mandibular Protrusion Sleep Studies for Prediction of Oral Appliance Treatment Response.

    Science.gov (United States)

    Sutherland, Kate; Ngiam, Joachim; Cistulli, Peter A

    2017-03-15

    Mandibular protrusion during sleep monitoring has been proposed as a method to predict oral appliance treatment outcome. A commercial remotely controlled mandibular protrusion (RCMP) device has become available for this purpose with predictive accuracy demonstrated in an initial study. Our aim was to validate this RCMP method for oral appliance treatment outcome prediction in a clinical sleep laboratory setting. Forty-two obstructive sleep apnea (OSA) patients (apnea-hypopnea index [AHI] > 10 events/h) were recruited to undergo a RCMP sleep study before commencing oral appliance treatment. The RCMP study was used to make a prediction of treatment "Success" or "Failure" based on a rule of ≤ 1 respiratory event per 5 min supine rapid eye movement sleep. Oral appliance treatment response was verified by polysomonography and defined as treatment AHI 30 events/h). Two participants (5%) were not able to tolerate the RCMP study. Oral appliance treatment outcome was verified in 33 participants (RCMP results: "Success" n = 10, "Failure" n = 15, "Inconclusive" n = 8). In those with a treatment outcome prediction (n = 25) the diagnostic characteristics of the RCMP test were sensitivity 81.8%, specificity 92.9%, positive predictive value 90%, and negative predictive value 86.7% (n = 3 misclassified). The RCMP device was well tolerated by patients and successfully used to perform mandibular protrusion sleep studies in our sleep laboratory. The RCMP sleep study showed good accuracy as a prediction technique for oral appliance treatment outcome, although there was a high rate of inconclusive tests.

  3. Cognitive, psychosocial, somatic and treatment factors predicting return to work after breast cancer treatment.

    Science.gov (United States)

    Hedayati, Elham; Johnsson, Aina; Alinaghizadeh, Hassan; Schedin, Anna; Nyman, Håkan; Albertsson, Maria

    2013-06-01

    Breast cancer (BC) may affect the ability to work. In this study, we want to identify any associations between cognitive, psychosocial, somatic and treatment factors with time to return to work (RTW) among women treated for BC. At eight (baseline) and 11(follow-up) months after BC diagnosis, women who had received adjuvant treatment for early BC at Stockholm South General Hospital completed the Headminder neuropsychological tests to obtain the Cognitive Stability Index (CSI), the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire and its Breast Cancer Module. At both time points, we compared the scores from women who had returned to work with those who had not. We also reviewed the medical certificates of women still on sick leave at 8, 11 and 18 months after diagnosis to determine why they had not returned to work. At baseline, 29 of 45 enroled women were working and 15 were not (one dropped out after baseline testing). The 14 women still not working 11 months after BC diagnosis had more advanced BC (OR = 3.64, 95% CI 2.01-7.31), lymph-node involvement (OR = 18.80, 95% CI 5.32-90.69) and Her 2-positive tumours (OR = 10.42,95% CI 2.19-65.32) than did working women. None of the scores for the four cognitive domains changed significantly at follow-up in either group. Comments on the medical certificates generally supported these findings. Independently of any adjuvant cancer therapy, overall quality of life improved and most women did RTW 18 months after BC diagnosis. Chemotherapy is associated with longer periods of sick leave. Cognitive functions do not predict RTW. Independently of any adjuvant therapy, most women eventually RTW in a few months. The ability to predict RTW after BC treatment should help prepare higher-risk patients for delayed RTW and allow earlier interventions to restore their social relations and quality of life. © 2012 Nordic College of Caring Science.

  4. Clinical prediction models in reproductive medicine: applications in untreated subfertility and in IVF treatment

    NARCIS (Netherlands)

    C.C. Hunault

    2006-01-01

    textabstractThis thesis deals with two prediction problems in reproductive medicine. The first is the prediction in infertile couples of the chance to conceive without treatment. The second deals with the prediction of the chance of conception in couples treated with in vitro fertilization (IVF).

  5. Social ranking effects on tooth-brushing behaviour.

    Science.gov (United States)

    Maltby, John; Paterson, Kevin; Day, Liz; Jones, Ceri; Kinnear, Hayley; Buchanan, Heather

    2016-05-01

    A tooth-brushing social rank hypothesis is tested suggesting tooth-brushing duration is influenced when individuals position their behaviour in a rank when comparing their behaviour with other individuals. Study 1 used a correlation design, Study 2 used a semi-experimental design, and Study 3 used a randomized intervention design to examine the tooth-brushing social rank hypothesis in terms of self-reported attitudes, cognitions, and behaviour towards tooth-brushing duration. Study 1 surveyed participants to examine whether the perceived health benefits of tooth-brushing duration could be predicted from the ranking of each person's tooth-brushing duration. Study 2 tested whether manipulating the rank position of the tooth-brushing duration influenced participant-perceived health benefits of tooth-brushing duration. Study 3 used a longitudinal intervention method to examine whether messages relating to the rank positions of tooth-brushing durations causally influenced the self-report tooth-brushing duration. Study 1 demonstrates that perceptions of the health benefits from tooth-brushing duration are predicted by the perceptions of how that behaviour ranks in comparison to other people's behaviour. Study 2 demonstrates that the perceptions of the health benefits of tooth-brushing duration can be manipulated experimentally by changing the ranked position of a person's tooth-brushing duration. Study 3 experimentally demonstrates the possibility of increasing the length of time for which individuals clean their teeth by focusing on how they rank among their peers in terms of tooth-brushing duration. The effectiveness of interventions using social-ranking methods relative to those that emphasize comparisons made against group averages or normative guidelines are discussed. What is already known on this subject? Individual make judgements based on social rank information. Social rank information has been shown to influence positive health behaviours such as exercise

  6. Universal scaling in sports ranking

    Science.gov (United States)

    Deng, Weibing; Li, Wei; Cai, Xu; Bulou, Alain; Wang, Qiuping A.

    2012-09-01

    Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters.

  7. Universal scaling in sports ranking

    CERN Document Server

    Deng, Weibing; Cai, Xu; Bulou, Alain; Wang, Qiuping A

    2011-01-01

    Ranking is a ubiquitous phenomenon in the human society. By clicking the web pages of Forbes, you may find all kinds of rankings, such as world's most powerful people, world's richest people, top-paid tennis stars, and so on and so forth. Herewith, we study a specific kind, sports ranking systems in which players' scores and prize money are calculated based on their performances in attending various tournaments. A typical example is tennis. It is found that the distributions of both scores and prize money follow universal power laws, with exponents nearly identical for most sports fields. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player will top the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simul...

  8. Factors predicting prolonged empirical antifungal treatment in critically ill patients.

    Science.gov (United States)

    Zein, Mohamed; Parmentier-Decrucq, Erika; Kalaoun, Amer; Bouton, Olivier; Wallyn, Frédéric; Baranzelli, Anne; Elmanser, Dia; Sendid, Boualem; Nseir, Saad

    2014-03-11

    To determine the incidence, risk factors, and impact on outcome of prolonged empirical antifungal treatment in ICU patients. Retrospective observational study performed during a one-year period. Patients who stayed in the ICU >48 h, and received empirical antifungal treatment were included. Patients with confirmed invasive fungal disease were excluded. Prolonged antifungal treatment was defined as percentage of days in the ICU with antifungals > median percentage in the whole cohort of patients. Among the 560 patients hospitalized for >48 h, 153 (27%) patients received empirical antifungal treatment and were included in this study. Fluconazole was the most frequently used antifungal (46% of study patients). Median length of ICU stay was 19 days (IQR 8, 34), median duration of antifungal treatment was 8 days (IQR 3, 16), and median percentage of days in the ICU with antifungals was 48% (IQR 25, 80). Seventy-seven patients (50%) received prolonged empirical antifungal treatment. Chemotherapy (OR [95% CI] 2.6 [1.07-6.69], p = 0.034), and suspected infection at ICU admission (3.1 [1.05-9.48], p = 0.041) were independently associated with prolonged empirical antifungal treatment. Duration of mechanical ventilation and ICU stay were significantly shorter in patients with prolonged empirical antifungal treatment compared with those with no prolonged empirical antifungal treatment. However, ICU mortality was similar in the two groups (46 versus 52%, p = 0.62). Empirical antifungal treatment was prescribed in a large proportion of study patients. Chemotherapy, and suspicion of infection at ICU admission are independently associated with prolonged empirical antifungal treatment.

  9. Validation and ranking of seven staging systems of hepatocellular carcinoma.

    Science.gov (United States)

    Chen, Zhan-Hong; Hong, Ying-Fen; Lin, Jinxiang; Li, Xing; Wu, Dong-Hao; Wen, Jing-Yun; Chen, Jie; Ruan, Dan-Yun; Lin, Qu; Dong, Min; Wei, Li; Wang, Tian-Tian; Lin, Ze-Xiao; Ma, Xiao-Kun; Wu, Xiang-Yuan; Xu, Ruihua

    2017-07-01

    The aim of the present study was to evaluate the ability of seven staging systems to predict 3- and 6-month and cumulative survival rates of patients with advanced hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). Data were collected from 220 patients with HBV-associated HCC who did not receive any standard anticancer treatment. Participants were patients at The Third Affiliated Hospital of Sun Yat-sen University from September 2008 to June 2010. The participants were classified according to the Chinese University Prognostic Index (CUPI), the Cancer of the Liver Italian Program (CLIP), Japan Integrated Staging (JIS), China Integrated Score (CIS) systems, Barcelona Clinic Liver Cancer (BCLC), Okuda and tumor-node-metastasis (TNM) staging systems at the time of diagnosis and during patient follow-up. The sensitivity and specificity of the predictive value of each staging system for 3- and 6-month mortality were analyzed by relative operating characteristic (ROC) curve analysis with a non-parametric test being used to compare the area under curve (AUC) of the ROC curves. In addition, log-rank tests and Kaplan-Meier estimator survival curves were applied to compare the overall survival rates of the patients with HCC defined as advanced using the various staging systems, and the Akaike information criterion (AIC) and likelihood ratio tests (LRTs) were used to evaluate the predictive value for overall survival in patients with advanced HCC. Using univariate and multivariate Cox's model analyses, the factors predictive of survival were also identified. A total of 220 patients with HBV-associated HCC were analyzed. Independent prognostic factors identified by multivariate analyses included tumor size, α-fetoprotein levels, blood urea nitrogen levels, the presence or absence of portal vein thrombus, Child-Pugh score and neutrophil count. When predicting 3-month survival, the AUCs of CLIP, CIS, CUPI, Okuda, TNM, JIS and BCLC were 0.806, 0.772, 0.751, 0

  10. DMARD use in Rheumatoid Arthritis: Can we Predict Treatment ...

    African Journals Online (AJOL)

    Objective: To review the current and emerging predictors of treatment response by DMARDS in Rheumatoid Arthritis (RA) patients. Data source: Published original research work and reviews were searched in English related to determinants of treatment response in rheumatoid arthritis on DMARDS. Study design: Only ...

  11. Probabilistic Low-Rank Multitask Learning.

    Science.gov (United States)

    Kong, Yu; Shao, Ming; Li, Kang; Fu, Yun

    2017-01-04

    In this paper, we consider the problem of learning multiple related tasks simultaneously with the goal of improving the generalization performance of individual tasks. The key challenge is to effectively exploit the shared information across multiple tasks as well as preserve the discriminative information for each individual task. To address this, we propose a novel probabilistic model for multitask learning (MTL) that can automatically balance between low-rank and sparsity constraints. The former assumes a low-rank structure of the underlying predictive hypothesis space to explicitly capture the relationship of different tasks and the latter learns the incoherent sparse patterns private to each task. We derive and perform inference via variational Bayesian methods. Experimental results on both regression and classification tasks on real-world applications demonstrate the effectiveness of the proposed method in dealing with the MTL problems.

  12. PageRank of integers

    Science.gov (United States)

    Frahm, K. M.; Chepelianskii, A. D.; Shepelyansky, D. L.

    2012-10-01

    We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers.

  13. Factors that might be predictive of completion of vaginismus treatment.

    Science.gov (United States)

    Özdel, Kadir; Yılmaz Özpolat, Ayşegül; Çeri, Özge; Kumbasar, Hakan

    2012-01-01

    Vaginismus is defined as a recurrent or persistent involuntary spasm of the musculature of the outer third of the vagina that interferes with sexual intercourse. The aim of this study was to assess the level of symptoms of depression, anxiety, obsessive-compulsive symptoms, and perfectionism among patients with vaginismus, as well as to determine if these clinical variables are related to the completion of treatment. The study included 20 women with vaginismus and their spouses that were referred as outpatients to Ankara University, School of Medicine, Department of Psychiatry, Consultation and Liaison Unit. All couples underwent cognitive behavioral therapy, which was administered as 40-60-min weekly sessions. At the first (assessment) session, the female patients were assessed using a sociodemographic evaluation form, the Hamilton Rating Scale for Depression (HAM-D), the Hamilton Rating Scale for Anxiety (HAM-A), the Maudsley Obsessive-Compulsive Inventory (MOCI), the Multidimensional Perfectionism Scale (MPS), and the Golombok Rust Inventory of Sexual Satisfaction (GRISS). The male spouses were evaluated using the GRISS. The same scales were administered after the completion of treatment to those that completed the treatment. The correlation between completion of treatment, and an elevated level of anxiety and self-oriented perfectionism was significant (P Vaginismus is not only a sexual dysfunction, but it is related to multiple components of mental health. Anxiety and a perfectionist personality trait were important factors associated with the completion of treatment; therefore, these factors should be evaluated before treatment.

  14. EGFR gene copy number predicts response to anti-EGFR treatment in RAS wild type and RAS/BRAF/PIK3CA wild type metastatic colorectal cancer.

    Science.gov (United States)

    Ålgars, Annika; Sundström, Jari; Lintunen, Minnamaija; Jokilehto, Terhi; Kytölä, Soili; Kaare, Milja; Vainionpää, Reetta; Orpana, Arto; Österlund, Pia; Ristimäki, Ari; Carpen, Olli; Ristamäki, Raija

    2017-02-15

    Anti-EGFR antibodies are used for the treatment of RAS wild type metastatic colorectal cancer. We previously showed that EGFR gene copy number (GCN) predicts response to anti-EGFR therapy in KRAS exon 2 wild type metastatic colorectal cancer. The aim of our study was to analyse the predictive role of EGFR GCN in RAS/BRAF/PIK3CA wild type metastatic colorectal cancer. The material included 102 patients with KRAS exon 2 wild type metastatic colorectal cancer treated with anti-EGFR ± cytotoxic therapy. Next generation sequencing was used for KRAS, NRAS, BRAF and PIK3CA gene mutation analyses. EGFR GCN was analysed by EGFR immunohistochemistry guided automated silver in situ hybridisation. Increased EGFR GCN (≥4.0) predicted a better response and prolonged progression free survival in anti-EGFR treated RAS/BRAF/PIK3CA wild type patients (Log-rank test, p = 0.0004). In contrast, survival of RAS/BRAF/PIK3CA wild type, EGFR GCN below 4.0 patients did not differ from patients with mutant RAS, BRAF or PIK3CA. Our study indicates that EGFR GCN predicts anti-EGFR treatment efficacy in patients with RAS/BRAF/PIK3CA wt metastatic CRC. Tumours with EGFR GCN below 4.0 appear to be as refractory to anti-EGFR treatment as tumours with mutation in any of the RAS/RAF/PIK3CA pathway genes. © 2016 UICC.

  15. Poor Response to Periodontal Treatment May Predict Future Cardiovascular Disease.

    Science.gov (United States)

    Holmlund, A; Lampa, E; Lind, L

    2017-07-01

    Periodontal disease has been associated with cardiovascular disease (CVD), but whether the response to the treatment of periodontal disease affects this association has not been investigated in any large prospective study. Periodontal data obtained at baseline and 1 y after treatment were available in 5,297 individuals with remaining teeth who were treated at a specialized clinic for periodontal disease. Poor response to treatment was defined as having >10% sites with probing pocket depth >4 mm deep and bleeding on probing at ≥20% of the sites 1 y after active treatment. Fatal/nonfatal incidence rate of CVD (composite end point of myocardial infarction, stroke, and heart failure) was obtained from the Swedish cause-of-death and hospital discharge registers. Poisson regression analysis was performed to analyze future risk of CVD. During a median follow-up of 16.8 y (89,719 person-years at risk), those individuals who did not respond well to treatment (13.8% of the sample) had an increased incidence of CVD ( n = 870) when compared with responders (23.6 vs. 15.3%, P 4 mm, and number of teeth, the incidence rate ratio for CVD among poor responders was 1.28 (95% CI, 1.07 to 1.53; P = 0.007) as opposed to good responders. The incidence rate ratio among poor responders increased to 1.39 (95% CI, 1.13 to 1.73; P = 0.002) for those with the most remaining teeth. Individuals who did not respond well to periodontal treatment had an increased risk for future CVD, indicating that successful periodontal treatment might influence progression of subclinical CVD.

  16. Ranking stability and super-stable nodes in complex networks.

    Science.gov (United States)

    Ghoshal, Gourab; Barabási, Albert-László

    2011-07-19

    Pagerank, a network-based diffusion algorithm, has emerged as the leading method to rank web content, ecological species and even scientists. Despite its wide use, it remains unknown how the structure of the network on which it operates affects its performance. Here we show that for random networks the ranking provided by pagerank is sensitive to perturbations in the network topology, making it unreliable for incomplete or noisy systems. In contrast, in scale-free networks we predict analytically the emergence of super-stable nodes whose ranking is exceptionally stable to perturbations. We calculate the dependence of the number of super-stable nodes on network characteristics and demonstrate their presence in real networks, in agreement with the analytical predictions. These results not only deepen our understanding of the interplay between network topology and dynamical processes but also have implications in all areas where ranking has a role, from science to marketing.

  17. Predicting substance abuse treatment completion using a new scale based on the theory of planned behavior.

    Science.gov (United States)

    Zemore, Sarah E; Ajzen, Icek

    2014-02-01

    We examined whether a 9-item scale based on the theory of planned behavior (TPB) predicted substance abuse treatment completion. Data were collected at a public, outpatient program among clients initiating treatment (N=200). Baseline surveys included measures of treatment-related attitudes, norms, perceived control, and intention; discharge status was collected from program records. As expected, TPB attitude and control components independently predicted intention (model R-squared=.56), and intention was positively associated with treatment completion even including clinical and demographic covariates (model R-squared=.24). TPB components were generally associated with the alternative readiness scales as expected, and the TPB remained predictive at higher levels of coercion. Meanwhile, none of the standard measures of readiness (e.g., the URICA and TREAT) or treatment coercion were positively associated with treatment participation. Results suggest promise for application of the TPB to treatment completion and support use of the intention component as a screener, though some refinements are suggested. © 2013.

  18. RANK and RANK ligand expression in primary human osteosarcoma

    Directory of Open Access Journals (Sweden)

    Daniel Branstetter

    2015-09-01

    Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

  19. Mental health indicator interaction in predicting substance abuse treatment outcomes in nevada.

    Science.gov (United States)

    Greenfield, Lawrence; Wolf-Branigin, Michael

    2009-01-01

    Indicators of co-occurring mental health and substance abuse problems routinely collected at treatment admission in 19 State substance abuse treatment systems include a dual diagnosis and a State mental health (cognitive impairment) agency referral. These indicators have yet to be compared as predictors of treatment outcomes. 1. Compare both indices as outcomes predictors individually and interactively. 2. Assess relationship of both indices to other client risk factors, e.g., physical/sexual abuse. Client admission and discharge records from the Nevada substance abuse treatment program, spanning 1995-2001 were reviewed (n = 17,591). Logistic regression analyses predicted treatment completion with significant improvement (33%) and treatment readmission following discharge (21%). Using Cox regression, the number of days from discharge to treatment readmission was predicted. Examined as predictors were two mental health indicators and their interaction with other admission and treatment variables controlled. Neither mental health indicator alone significantly predicted any of the three outcomes; however, the interaction between the two indicators significantly predicted each outcome (p abuse, domestic violence, homelessness, out of labor force and prior treatment. Indicator interactions may help improve substance abuse treatment outcomes prediction.

  20. Ranking structures and Rank-Rank Correlations of Countries. The FIFA and UEFA cases

    CERN Document Server

    Ausloos, Marcel; Gadomski, Adam; Vitanov, Nikolay K

    2014-01-01

    Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures, in both cases.

  1. Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

    Science.gov (United States)

    Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

    2014-04-01

    Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

  2. Individualized Cardiovascular Disease Prevention: Prediction of risk and treatment effect

    NARCIS (Netherlands)

    Leeuw, J. van der

    2014-01-01

    In the present era of evidence-based medicine, the study of groups is the dominant paradigm to establish causes of disease and to determine the efficacy of treatment. The results of these studies are usually presented as average group-level estimates, which are not informative of the individual

  3. Predicting chromium (VI) adsorption rate in the treatment of liquid ...

    African Journals Online (AJOL)

    The adsorption rate of chromium (VI) on commercial activated carbon during the treatment of the flocculation effluent of liquid-phase oil-based drill-cuttings has been investigated in terms of contact time and initial chromium (VI) ion concentration. Homogenizing 1 g of the activated carbon with 100 ml of the flocculation ...

  4. Factors predicting the outcome following treatment for lumbar spondylolysis

    OpenAIRE

    Debnath, Ujjwal Kanti

    2010-01-01

    Abstract of Study 1 Study design A non �randomised continuous retrospective cross sectional and observational study Objective 1) To evaluate the results of nonoperative treatment of symptomatic lumbar pars stress injuries or spondylolysis in sporting as well as non sporting individuals 2) To determine the factors responsible for non-operative method of managing symptomatic lumbar spondylolysis in young population 3) To evaluate the outcome in different types of...

  5. Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis.

    Science.gov (United States)

    Soler, Zachary M; Hyer, J Madison; Rudmik, Luke; Ramakrishnan, Viswanathan; Smith, Timothy L; Schlosser, Rodney J

    2016-04-01

    Current clinical classifications of chronic rhinosinusitis (CRS) have weak prognostic utility regarding treatment outcomes. Simplified discriminant analysis based on unsupervised clustering has identified novel phenotypic subgroups of CRS, but prognostic utility is unknown. We sought to determine whether discriminant analysis allows prognostication in patients choosing surgery versus continued medical management. A multi-institutional prospective study of patients with CRS in whom initial medical therapy failed who then self-selected continued medical management or surgical treatment was used to separate patients into 5 clusters based on a previously described discriminant analysis using total Sino-Nasal Outcome Test-22 (SNOT-22) score, age, and missed productivity. Patients completed the SNOT-22 at baseline and for 18 months of follow-up. Baseline demographic and objective measures included olfactory testing, computed tomography, and endoscopy scoring. SNOT-22 outcomes for surgical versus continued medical treatment were compared across clusters. Data were available on 690 patients. Baseline differences in demographics, comorbidities, objective disease measures, and patient-reported outcomes were similar to previous clustering reports. Three of 5 clusters identified by means of discriminant analysis had improved SNOT-22 outcomes with surgical intervention when compared with continued medical management (surgery was a mean of 21.2 points better across these 3 clusters at 6 months, P clusters had similar outcomes when comparing surgery with continued medical management. A simplified discriminant analysis based on 3 common clinical variables is able to cluster patients and provide prognostic information regarding surgical treatment versus continued medical management in patients with CRS. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2015-01-01

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

  7. University Ranking Systems; Criteria and Critiques

    OpenAIRE

    Saka, Yavuz; YAMAN, Süleyman

    2011-01-01

    The purpose of this paper is to explore international university ranking systems. As a compilation study this paper provides specific criteria that each ranking system uses and main critiques regarding these ranking systems. Since there are many ranking systems in this area of research, this study focused on only most cited and referred ranking systems. As there is no consensus in terms of the criteria that these systems use, this paper has no intention of identifying the best ranking system ...

  8. Prediction of Infertility Treatment Outcomes Using Classification Trees

    Directory of Open Access Journals (Sweden)

    Milewska Anna Justyna

    2016-12-01

    Full Text Available Infertility is currently a common problem with causes that are often unexplained, which complicates treatment. In many cases, the use of ART methods provides the only possibility of getting pregnant. Analysis of this type of data is very complex. More and more often, data mining methods or artificial intelligence techniques are appropriate for solving such problems. In this study, classification trees were used for analysis. This resulted in obtaining a group of patients characterized most likely to get pregnant while using in vitro fertilization.

  9. Prediction of rehabilitation needs after treatment of cervical cancer

    DEFF Research Database (Denmark)

    Mikkelsen, Tina Broby; Sørensen, Bente; Dieperink, Karin B

    2017-01-01

    sent to all participants. RESULTS: The participation rate was 85/107 (79%). Participants below 45 years had significantly more menopausal symptoms and lower body image scores compared to elderly women. The frequency of participants with menopausal symptoms decreased with time since diagnosis. Symptom...... showed impaired quality of life, e.g., a lower body image and self-efficacy score, correlated with increasing BMI. Women who had surgery had greater risk of lymphedema, and women who received chemotherapy during treatment had a lower quality of life. All but one received radiotherapy. CONCLUSION...

  10. Ranking species in mutualistic networks.

    Science.gov (United States)

    Domínguez-García, Virginia; Muñoz, Miguel A

    2015-02-02

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic "nested" structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm--similar in spirit to Google's PageRank but with a built-in non-linearity--here we propose a method which--by exploiting their nested architecture--allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

  11. University rankings in computer science

    DEFF Research Database (Denmark)

    Ehret, Philip; Zuccala, Alesia Ann; Gipp, Bela

    2017-01-01

    This is a research-in-progress paper concerning two types of institutional rankings, the Leiden and QS World ranking, and their relationship to a list of universities’ ‘geo-based’ impact scores, and Computing Research and Education Conference (CORE) participation scores in the field of computer...... science. A ‘geo-based’ impact measure examines the geographical distribution of incoming citations to a particular university’s journal articles for a specific period of time. It takes into account both the number of citations and the geographical variability in these citations. The CORE participation...... score is calculated on the basis of the number of weighted proceedings papers that a university has contributed to either an A*, A, B, or C conference as ranked by the Computing Research and Education Association of Australasia. In addition to calculating the correlations between the distinct university...

  12. An Obesity Dietary Quality Index Predicts Abdominal Obesity in Women: Potential Opportunity for New Prevention and Treatment Paradigms

    Directory of Open Access Journals (Sweden)

    Dolores M. Wolongevicz

    2010-01-01

    Full Text Available Background. Links between dietary quality and abdominal obesity are poorly understood. Objective. To examine the association between an obesity-specific dietary quality index and abdominal obesity risk in women. Methods. Over 12 years, we followed 288 Framingham Offspring/Spouse Study women, aged 30–69 years, without metabolic syndrome risk factors, cardiovascular disease, cancer, or diabetes at baseline. An 11-nutrient obesity-specific dietary quality index was derived using mean ranks of nutrient intakes from 3-day dietary records. Abdominal obesity (waist circumference >88 cm was assessed during follow-up. Results. Using multiple logistic regression, women with poorer dietary quality were more likely to develop abdominal obesity compared to those with higher dietary quality (OR 1.87; 95% CI, 1.01, 3.47; P for trend =.048 independent of age, physical activity, smoking, and menopausal status. Conclusions. An obesity-specific dietary quality index predicted abdominal obesity in women, suggesting targets for dietary quality assessment, intervention, and treatment to address abdominal adiposity.

  13. Prediction of long-term success of orthopedic treatment in skeletal Class III malocclusions.

    Science.gov (United States)

    Choi, Yoon Jeong; Chang, Jeong Eun; Chung, Chooryung J; Tahk, Ji Hyun; Kim, Kyung-Ho

    2017-08-01

    We investigated the long-term success of orthopedic treatment in skeletal Class III malocclusions, established a model to predict its long-term success, and verified previously reported success rates and prediction models. Fifty-nine patients who underwent successful facemask treatment and were followed until growth completion were evaluated. After completion of growth, the patients were divided into successful and unsuccessful groups according to overjet, overbite, and facial profile. Pretreatment cephalometric measurements were compared between groups, and logistic regression analysis was used to identify the predictors of long-term success. Four previously published articles were selected to verify the success rate and predictability of the prediction models with regard to our patient sample. The treatment success rate was 62.7%. The AB-mandibular plane angle, Wits appraisal, and the articular angle were identified as predictors. The success rates differed according to success criteria and patient characteristics. The prediction models proposed by the 4 previous studies and our study showed similar predictabilities (61.0%-64.4%) for our patient sample. The predictability for the unsuccessful group was low. Our results suggest that no particular method or factor can predict the long-term success of orthopedic treatment for skeletal Class III malocclusion. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

  14. Does cognitive flexibility predict treatment gains in Internet-delivered psychological treatment of social anxiety disorder, depression, or tinnitus?

    Directory of Open Access Journals (Sweden)

    Philip Lindner

    2016-04-01

    Full Text Available Little is known about the individual factors that predict outcomes in Internet-administered psychological treatments. We hypothesized that greater cognitive flexibility (i.e. the ability to simultaneously consider several concepts and tasks and switch effortlessly between them in response to changes in environmental contingencies would provide a better foundation for learning and employing the cognitive restructuring techniques taught and exercised in therapy, leading to greater treatment gains. Participants in three trials featuring Internet-administered psychological treatments for depression (n = 36, social anxiety disorder (n = 115 and tinnitus (n = 53 completed the 64-card Wisconsin Card Sorting Test (WCST prior to treatment. We found no significant associations between perseverative errors on the WCST and treatment gains in any group. We also found low accuracy in the classification of treatment responders. We conclude that lower cognitive flexibility, as captured by perseverative errors on the WCST, should not impede successful outcomes in Internet-delivered psychological treatments.

  15. Topical Treatment with Xiaozheng Zhitong Paste (XZP Alleviates Bone Destruction and Bone Cancer Pain in a Rat Model of Prostate Cancer-Induced Bone Pain by Modulating the RANKL/RANK/OPG Signaling

    Directory of Open Access Journals (Sweden)

    Yanju Bao

    2015-01-01

    Full Text Available To explore the effects and mechanisms of Xiaozheng Zhitong Paste (XZP on bone cancer pain, Wistar rats were inoculated with vehicle or prostate cancer PC-3 into the tibia bone and treated topically with inert paste, XZP at 15.75, 31.5, or 63 g/kg twice per day for 21 days. Their bone structural damage, nociceptive behaviors, bone osteoclast and osteoblast activity, and the levels of OPG, RANL, RNAK, PTHrP, IGF-1, M-CSF, IL-8, and TNF-α were examined. In comparison with that in the placebo group, significantly reduced numbers of invaded cancer cells, decreased levels of bone damage and mechanical threshold and paw withdrawal latency, lower levels of serum TRACP5b, ICTP, PINP, and BAP, and less levels of bone osteoblast and osteoclast activity were detected in the XZP-treated rats (P<0.05. Moreover, significantly increased levels of bone OPG but significantly decreased levels of RANL, RNAK, PTHrP, IGF-1, M-CSF, IL-8, and TNF-α were detected in the XZP-treated rats (P<0.05 for all. Together, XZP treatment significantly mitigated the cancer-induced bone damage and bone osteoclast and osteoblast activity and alleviated prostate cancer-induced bone pain by modulating the RANKL/RANK/OPG pathway and bone cancer-related inflammation in rats.

  16. The role of attachment in predicting CBT treatment outcome in children with anxiety disorders

    DEFF Research Database (Denmark)

    Walczak, Monika Anna; Normann, Nicoline; Tolstrup, Marie

    2015-01-01

    Introduction: Child’s insecure attachment to parents and insecure parental attachment has been linked to childhood anxiety (Brumariu & Kerns, 2010; Manassis et al.,1994).Whether attachment patterns can predict treatment outcome, is yet to be investigated. We examined the role of children......’s attachment to parents, and parental attachment in predicting treatment outcome in anxious children receiving cognitive-behavioral treatment. Method: A total of 69 children aged 7-13 years were diagnosed at intake and post-treatment, using Anxiety Disorders Interview Schedule for DSM-IV (Silverman and Albano...... of maternal attachment anxiety and it was found to significantly add to the model (Exp(B) =.958, CI0.95= [ .925, .994]; p=.021), even while controlling for symptom severity. Discussion: Maternal attachment anxiety was found to have a significant role in predicting treatment outcome. These results suggest...

  17. Money and happiness: rank of income, not income, affects life satisfaction.

    Science.gov (United States)

    Boyce, Christopher J; Brown, Gordon D A; Moore, Simon C

    2010-04-01

    Does money buy happiness, or does happiness come indirectly from the higher rank in society that money brings? We tested a rank-income hypothesis, according to which people gain utility from the ranked position of their income within a comparison group. The rank hypothesis contrasts with traditional reference-income hypotheses, which suggest that utility from income depends on comparison to a social reference-group norm. We found that the ranked position of an individual's income predicts general life satisfaction, whereas absolute income and reference income have no effect. Furthermore, individuals weight upward comparisons more heavily than downward comparisons. According to the rank hypothesis, income and utility are not directly linked: Increasing an individual's income will increase his or her utility only if ranked position also increases and will necessarily reduce the utility of others who will lose rank.

  18. Complete hazard ranking to analyze right-censored data: An ALS survival study.

    Science.gov (United States)

    Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan; Goutman, Stephen A; Mukherjee, Bhramar; Dinov, Ivo D; Guan, Yuanfang

    2017-12-01

    Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

  19. Complete hazard ranking to analyze right-censored data: An ALS survival study.

    Directory of Open Access Journals (Sweden)

    Zhengnan Huang

    2017-12-01

    Full Text Available Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

  20. Rank distributions: Frequency vs. magnitude.

    Science.gov (United States)

    Velarde, Carlos; Robledo, Alberto

    2017-01-01

    We examine the relationship between two different types of ranked data, frequencies and magnitudes. We consider data that can be sorted out either way, through numbers of occurrences or size of the measures, as it is the case, say, of moon craters, earthquakes, billionaires, etc. We indicate that these two types of distributions are functional inverses of each other, and specify this link, first in terms of the assumed parent probability distribution that generates the data samples, and then in terms of an analog (deterministic) nonlinear iterated map that reproduces them. For the particular case of hyperbolic decay with rank the distributions are identical, that is, the classical Zipf plot, a pure power law. But their difference is largest when one displays logarithmic decay and its counterpart shows the inverse exponential decay, as it is the case of Benford law, or viceversa. For all intermediate decay rates generic differences appear not only between the power-law exponents for the midway rank decline but also for small and large rank. We extend the theoretical framework to include thermodynamic and statistical-mechanical concepts, such as entropies and configuration.

  1. Rankings Methodology Hurts Public Institutions

    Science.gov (United States)

    Van Der Werf, Martin

    2007-01-01

    In the 1980s, when the "U.S. News & World Report" rankings of colleges were based solely on reputation, the nation's public universities were well represented at the top. However, as soon as the magazine began including its "measures of excellence," statistics intended to define quality, public universities nearly disappeared from the top. As the…

  2. Let Us Rank Journalism Programs

    Science.gov (United States)

    Weber, Joseph

    2014-01-01

    Unlike law, business, and medical schools, as well as universities in general, journalism schools and journalism programs have rarely been ranked. Publishers such as "U.S. News & World Report," "Forbes," "Bloomberg Businessweek," and "Washington Monthly" do not pay them much mind. What is the best…

  3. A network-based dynamical ranking system for competitive sports

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-12-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  4. A network-based dynamical ranking system for competitive sports.

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  5. Multiple graph regularized protein domain ranking

    Directory of Open Access Journals (Sweden)

    Wang Jim

    2012-11-01

    Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  6. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-11-19

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  7. The Globalization of College and University Rankings

    Science.gov (United States)

    Altbach, Philip G.

    2012-01-01

    In the era of globalization, accountability, and benchmarking, university rankings have achieved a kind of iconic status. The major ones--the Academic Ranking of World Universities (ARWU, or the "Shanghai rankings"), the QS (Quacquarelli Symonds Limited) World University Rankings, and the "Times Higher Education" World…

  8. Startle and spider phobia : Unilateral probes and the prediction of treatment effects

    NARCIS (Netherlands)

    de Jong, Peter J.; Visser, Sylvia; Merckelbach, Harald

    1996-01-01

    The present study explored two issues: (1) the predictive value of startle responses for treatment success and (2) the lateralization of affect-modulated startle responses. Approximately 40 days before behavioral treatment, monaural startle probes were presented to 20 women who were spider phobic

  9. Unsuccessful treatment in pulmonary tuberculosis: factors and a consequent predictive model.

    Science.gov (United States)

    Costa-Veiga, Ana; Briz, Teodoro; Nunes, Carla

    2017-10-03

    Cure is particularly valuable in pulmonary cases (PTB), as unsuccessful treatment fuels incidence and resistance to antibiotics. This study aims to identify individual factors of PTB unsuccessful treatment in Portugal and to develop a consequent predictive model. Methods: Using the Portuguese TB surveillance database (SVIG-TB), PTB cases older than 15 years notified from 2000 to 2012 in Continental Portugal were analyzed. Unsuccessful treatment included the WHO categories (failure, default, death and transferred out). Based on a literature review, predictors involved sociodemographic, behavioral, disease-related and treatment-related factors. Binary logistic regression was used to estimate unsuccessful treatment factors and to develop the predictive risk model. The unsuccessful outcome rate in PTB patients was of 11.9%. The predictive model included the following factors: TB/HIV co-infection (OR 4.93), age over 64 years (OR 4.37), IV drugs abuse (OR 2.29), other diseases (excluding HIV and Diabetes, OR 2.09) and retreatment (OR 1.44), displaying a rather good validity. The overall treatment unsuccessful treatment rate in PTB patients complies with the 85% WHO success threshold. The predictive model of unsuccessful treatment proved well. Nomogram representation allows an early, intuitive identification of PTB patients at increased risk. The model is liable to widespread use as a prognostic tool.

  10. Nonverbal interpersonal attunement and extravert personality predict outcome of light treatment in seasonal affective disorder

    NARCIS (Netherlands)

    Geerts, E; Kouwert, E; Bouhuys, N; Meesters, Y; Jansen, J

    We investigated whether personality and nonverbal interpersonal processes can predict the subsequent response to light treatment in seasonal affective disorder (SAD) patients. In 60 SAD patients, Neuroticism and Extraversion were assessed prior to light treatment (4 days with 30 min of 10.000 lux).

  11. Functional network architecture predicts psychologically mediated analgesia related to treatment in chronic knee pain patients.

    Science.gov (United States)

    Hashmi, Javeria Ali; Kong, Jian; Spaeth, Rosa; Khan, Sheraz; Kaptchuk, Ted J; Gollub, Randy L

    2014-03-12

    Placebo analgesia is an indicator of how efficiently the brain translates psychological signals conveyed by a treatment procedure into pain relief. It has been demonstrated that functional connectivity between distributed brain regions predicts placebo analgesia in chronic back pain patients. Greater network efficiency in baseline brain networks may allow better information transfer and facilitate adaptive physiological responses to psychological aspects of treatment. Here, we theorized that topological network alignments in resting state scans predict psychologically conditioned analgesic responses to acupuncture treatment in chronic knee osteoarthritis pain patients (n = 45). Analgesia was induced by building positive expectations toward acupuncture treatment with verbal suggestion and heat pain conditioning on a test site of the arm. This procedure induced significantly more analgesia after sham or real acupuncture on the test site than in a control site. The psychologically conditioned analgesia was invariant to sham versus real treatment. Efficiency of information transfer within local networks calculated with graph-theoretic measures (local efficiency and clustering coefficients) significantly predicted conditioned analgesia. Clustering coefficients in regions associated with memory, motivation, and pain modulation were closely involved in predicting analgesia. Moreover, women showed higher clustering coefficients and marginally greater pain reduction than men. Overall, analgesic response to placebo cues can be predicted from a priori resting state data by observing local network topology. Such low-cost synchronizations may represent preparatory resources that facilitate subsequent performance of brain circuits in responding to adaptive environmental cues. This suggests a potential utility of network measures in predicting placebo response for clinical use.

  12. Guidelines for patient treatment matching In the substance abuse treatment system: Feasibility, predictive validity and improvement

    NARCIS (Netherlands)

    Merkx, M.J.M.

    2016-01-01

    Substance use disorders (SUD) are highly prevalent, the patient population with these disorders is heterogeneous and there is a diversity of evidence based treatments available. Important element in a treatment of patients with a SUD is patient-treatment matching which is to select from amongst all

  13. Therapeutic Alliances Predict Session by Session Drinking Behavior in the Treatment of Alcohol Use Disorders

    Science.gov (United States)

    Connors, Gerard J.; Maisto, Stephen A.; Schlauch, Robert C.; Dearing, Ronda L.; Prince, Mark A.; Duerr, Mark R.

    2016-01-01

    Objective The therapeutic alliance is recognized as an important contributor to treatment outcomes. In this study, the session-to-session interplay of the alliance (as perceived by the patient) and alcohol involvement (drinking days and heavy drinking days between successive treatment sessions) was examined. The analyses also tested the extent to which pretreatment changes in drinking altered these interrelationships. Method Participants (N = 63) seeking treatment for an alcohol use disorder received 12-weeks of CBT for alcohol dependence and completed weekly assessments of the alliance. Results Higher session alliance scores at a given session significantly predicted lower alcohol involvement (both drinking days and heavy drinking days) in the period until the next treatment session, controlling for previous alcohol involvement. This relationship was further moderated by pretreatment change (changes in drinking prior to the first treatment session). Among those who demonstrated low pretreatment change, alliances continued to predict alcohol involvement. In contrast, alliances were not associated with alcohol involvement among those who significantly reduced their drinking prior to the first treatment session (high pretreatment changers). Finally, alcohol involvement during the period preceding a treatment session did not significantly predict alliance ratings. Conclusions These data demonstrate that more positive patient ratings of the alliance at any given treatment session are associated with less alcohol involvement during the period until the next treatment session, most particularly among patients who have not initiated reductions in their drinking prior to the first treatment session. For such patients, efforts to maximize therapeutic alliances may be warranted and productive. PMID:27548032

  14. Neural Reactivity to Angry Faces Predicts Treatment Response in Pediatric Anxiety.

    Science.gov (United States)

    Bunford, Nora; Kujawa, Autumn; Fitzgerald, Kate D; Swain, James E; Hanna, Gregory L; Koschmann, Elizabeth; Simpson, David; Connolly, Sucheta; Monk, Christopher S; Phan, K Luan

    2017-02-01

    Although cognitive-behavioral psychotherapy (CBT) and pharmacotherapy are evidence-based treatments for pediatric anxiety, many youth with anxiety disorders fail to respond to these treatments. Given limitations of clinical measures in predicting treatment response, identifying neural predictors is timely. In this study, 35 anxious youth (ages 7-19 years) completed an emotional face-matching task during which the late positive potential (LPP), an event-related potential (ERP) component that indexes sustained attention towards emotional stimuli, was measured. Following the ERP measurement, youth received CBT or selective serotonin reuptake inhibitor (SSRI) treatment, and the LPP was examined as a predictor of treatment response. Findings indicated that, accounting for pre-treatment anxiety severity, neural reactivity to emotional faces predicted anxiety severity post- CBT and SSRI treatment such that enhanced electrocortical response to angry faces was associated with better treatment response. An enhanced LPP to angry faces may predict treatment response insofar as it may reflect greater emotion dysregulation or less avoidance and/or enhanced engagement with environmental stimuli in general, including with treatment.

  15. Time evolution of Wikipedia network ranking

    Science.gov (United States)

    Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

    2013-12-01

    We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

  16. Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment

    DEFF Research Database (Denmark)

    Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo

    2016-01-01

    Background: Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have...... considered combination treatments. The current study modeled bacterial growth in the intestine of pigs after intramuscular combination treatment (i.e. using two antibiotics simultaneously) and sequential treatments (i.e. alternating between two antibiotics) in order to identify the factors that favor...... generated by a mathematical model of the competitive growth of multiple strains of Escherichia coli.Results: Simulation studies showed that sequential use of tetracycline and ampicillin reduced the level of double resistance, when compared to the combination treatment. The effect of the cycling frequency...

  17. A computer-aided diagnosis system of nuclear cataract via ranking.

    Science.gov (United States)

    Huang, Wei; Li, Huiqi; Chan, Kap Luk; Lim, Joo Hwee; Liu, Jiang; Wong, Tien Yin

    2009-01-01

    A novel computer-aided diagnosis system of nuclear cataract via ranking is firstly proposed in this paper. The grade of nuclear cataract in a slit-lamp image is predicted based on its neighboring labeled images in a ranked images list, which is achieved using an optimal ranking function. A new ranking evaluation measure is proposed for learning the optimal ranking function via direct optimization. Our system has been tested by a large dataset composed of 1000 slit-lamp images from 1000 different cases. Both experimental results and comparison with several state-of-the-art methods indicate the superiority of our system.

  18. The value of initial cavitation to predict re-treatment with pulmonary tuberculosis.

    Science.gov (United States)

    Huang, Qiusheng; Yin, Yongmei; Kuai, Shougang; Yan, Yan; Liu, Jun; Zhang, YingYing; Shan, Zhongbao; Gu, Lan; Pei, Hao; Wang, Jun

    2016-05-06

    Pulmonary cavitation is the classic hallmark of pulmonary tuberculosis (PTB) and is the site of very high mycobacterial burden associated with antimycobacterial drug resistance and treatment failure. The objective of this study was to investigate the relationship between re-treatment PTB and initial pulmonary cavitation coordinated with other clinical factors. We conducted a case-control study of 291 newly diagnosed cases of pulmonary TB in The Infectious Hospital of Wuxi from Dec 2009 to Dec 2011 with complete follow-up information until December 31st of 2014. 68 patients were followed-up with PTB re-treatment; the rest of the PTB patients (n = 223) had completed anti-TB treatment, and cured without re-treatment were selected as controls. The univariate analysis [hazard ratio (HR) 1.885, 95 % CI 1.170-3.035, P = 0.009] and the multivariable analysis (HR 2.242, 95 % CI 1.294-3.882, P = 0.004) demonstrated that the initial pulmonary cavitation was a prognostic predictor for TB re-treatment. Additionally, the re-treatment rates in PTB patients with cavitation and no-cavitation were 27.1 and 15.5 %, respectively, with significant difference (log-rank test; P = 0.010). Other factors, age of ≥60 and history of smoking, were also prognostic variables. Initial pulmonary cavitation of chest X-ray was a significant predictor for PTB re-treatment.

  19. Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results.

    Science.gov (United States)

    Crowe, S B; Kairn, T; Kenny, J; Knight, R T; Hill, B; Langton, C M; Trapp, J V

    2014-09-01

    The planning of IMRT treatments requires a compromise between dose conformity (complexity) and deliverability. This study investigates established and novel treatment complexity metrics for 122 IMRT beams from prostate treatment plans. The Treatment and Dose Assessor software was used to extract the necessary data from exported treatment plan files and calculate the metrics. For most of the metrics, there was strong overlap between the calculated values for plans that passed and failed their quality assurance (QA) tests. However, statistically significant variation between plans that passed and failed QA measurements was found for the established modulation index and for a novel metric describing the proportion of small apertures in each beam. The 'small aperture score' provided threshold values which successfully distinguished deliverable treatment plans from plans that did not pass QA, with a low false negative rate.

  20. Predictive value of early {sup 18}F-FDG PET/CT studies for treatment response evaluation to ipilimumab in metastatic melanoma: preliminary results of an ongoing study

    Energy Technology Data Exchange (ETDEWEB)

    Sachpekidis, Christos; Pan, Leyun; Dimitrakopoulou-Strauss, Antonia [German Cancer Research Center, Clinical Cooperation Unit Nuclear Medicine, Heidelberg (Germany); Larribere, Lionel [German Cancer Research Center, Clinical Cooperation Unit Dermato-Oncology, Heidelberg (Germany); Haberkorn, Uwe [German Cancer Research Center, Clinical Cooperation Unit Nuclear Medicine, Heidelberg (Germany); University of Heidelberg, Division of Nuclear Medicine, Heidelberg (Germany); Hassel, Jessica C. [University Hospital Heidelberg, Skin Cancer Center, Department of Dermatology, Heidelberg (Germany); National Center for Tumor Diseases Heidelberg, Heidelberg (Germany)

    2014-10-31

    significant for both early and late responses (log-rank p < 0.001). Median OS among patients with late PMD was 9.1 months (mean 11.2 months) and among those with late SMD 9.8 months (mean 10.7 months). The difference in OS between the two groups was statistically significant (log-rank p = 0.013). The median OS among patients with early PMD was 8.8 months (mean 12.0 months) and among those with early SMD 9.8 months (mean 10.0 months). The difference in OS between the two groups was statistically significant (log-rank p < 0.001). {sup 18}F-FDG PET/CT after two cycles of ipilimumab is highly predictive of the final treatment outcome in patients with PMD and SMD. (orig.)

  1. Accuracy of teledentistry examinations at predicting actual treatment modality in a pediatric dentistry clinic.

    Science.gov (United States)

    McLaren, Sean W; Kopycka-Kedzierawski, Dorota T; Nordfelt, Jed

    2017-09-01

    Objectives The purpose of this study was to assess the accuracy of predicting dental treatment modalities for children seen initially by means of a live-video teledentistry consultation. Methods A retrospective dental record review was completed of 251 rural pediatric patients from the Finger Lakes region of New York State who had an initial teledentistry appointment with a board-certified pediatric dentist located remotely at the Eastman Institute for Oral Health in Rochester, NY. Proportions of children who were referred for specific treatment modalities and who completed treatment and proportions of children for whom the treatment recommendation was changed were calculated. Fisher's exact test was used to assess statistical significance. Results The initial treatment modality was not changed for 221/251 (88%) children initially seen for a teledentistry consultation. Thirty (12%) children had the initial treatment modality changed, most frequently children who were initially suggested treatment with nitrous oxide. Based on the initial treatment modality, changes to a different treatment modality were statistically significant (Fisher's exact test, p < 0.0001). Conclusions Our data suggest that the use of a live-video teledentistry consultation can be an effective way of predicting the best treatment modality for rural children with significant dental disease. A live-video teledentistry consultation can be an effective intervention to facilitate completion of complex treatment plans for children from a rural area that have extensive dental needs.

  2. Validating rankings in soccer championships

    Directory of Open Access Journals (Sweden)

    Annibal Parracho Sant'Anna

    2012-08-01

    Full Text Available The final ranking of a championship is determined by quality attributes combined with other factors which should be filtered out of any decision on relegation or draft for upper level tournaments. Factors like referees' mistakes and difficulty of certain matches due to its accidental importance to the opponents should have their influence reduced. This work tests approaches to combine classification rules considering the imprecision of the number of points as a measure of quality and of the variables that provide reliable explanation for it. Two home-advantage variables are tested and shown to be apt to enter as explanatory variables. Independence between the criteria is checked against the hypothesis of maximal correlation. The importance of factors and of composition rules is evaluated on the basis of correlation between rank vectors, number of classes and number of clubs in tail classes. Data from five years of the Brazilian Soccer Championship are analyzed.

  3. Prediction of treatment outcomes to exercise in patients with nonremitted major depressive disorder.

    Science.gov (United States)

    Rethorst, Chad D; South, Charles C; Rush, A John; Greer, Tracy L; Trivedi, Madhukar H

    2017-12-01

    Only one-third of patients with major depressive disorder (MDD) achieve remission with initial treatment. Consequently, current clinical practice relies on a "trial-and-error" approach to identify an effective treatment for each patient. The purpose of this report was to determine whether we could identify a set of clinical and biological parameters with potential clinical utility for prescription of exercise for treatment of MDD in a secondary analysis of the Treatment with Exercise Augmentation in Depression (TREAD) trial. Participants with nonremitted MDD were randomized to one of two exercise doses for 12 weeks. Participants were categorized as "remitters" (≤12 on the IDS-C), nonresponders (depressive symptom severity, and higher postexercise positive affect. Predictors of treatment nonresponse were low cardiorespiratory fitness, lower levels of IL-6 and BDNF, and lower postexercise positive affect. Models including these predictors resulted in predictive values greater than 70% (true predicted remitters/all predicted remitters) with specificities greater than 25% (true predicted remitters/all remitters). Results indicate feasibility in identifying patients who will either remit or not respond to exercise as a treatment for MDD utilizing a clinical decision model that incorporates multiple patient characteristics. © 2017 Wiley Periodicals, Inc.

  4. Minkowski metrics in creating universal ranking algorithms

    Directory of Open Access Journals (Sweden)

    Andrzej Ameljańczyk

    2014-06-01

    Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

  5. Combined Reduced-Rank Transform

    Directory of Open Access Journals (Sweden)

    Anatoli Torokhti

    2006-04-01

    Full Text Available We propose and justify a new approach to constructing optimal nonlinear transforms of random vectors. We show that the proposed transform improves such characteristics of {rank-reduced} transforms as compression ratio, accuracy of decompression and reduces required computational work. The proposed transform ${mathcal T}_p$ is presented in the form of a sum with $p$ terms where each term is interpreted as a particular rank-reduced transform. Moreover, terms in ${mathcal T}_p$ are represented as a combination of three operations ${mathcal F}_k$, ${mathcal Q}_k$ and ${oldsymbol{varphi}}_k$ with $k=1,ldots,p$. The prime idea is to determine ${mathcal F}_k$ separately, for each $k=1,ldots,p$, from an associated rank-constrained minimization problem similar to that used in the Karhunen--Lo`{e}ve transform. The operations ${mathcal Q}_k$ and ${oldsymbol{varphi}}_k$ are auxiliary for f/inding ${mathcal F}_k$. The contribution of each term in ${mathcal T}_p$ improves the entire transform performance. A corresponding unconstrained nonlinear optimal transform is also considered. Such a transform is important in its own right because it is treated as an optimal filter without signal compression. A rigorous analysis of errors associated with the proposed transforms is given.

  6. Functional Multiplex PageRank

    Science.gov (United States)

    Iacovacci, Jacopo; Rahmede, Christoph; Arenas, Alex; Bianconi, Ginestra

    2016-10-01

    Recently it has been recognized that many complex social, technological and biological networks have a multilayer nature and can be described by multiplex networks. Multiplex networks are formed by a set of nodes connected by links having different connotations forming the different layers of the multiplex. Characterizing the centrality of the nodes in a multiplex network is a challenging task since the centrality of the node naturally depends on the importance associated to links of a certain type. Here we propose to assign to each node of a multiplex network a centrality called Functional Multiplex PageRank that is a function of the weights given to every different pattern of connections (multilinks) existent in the multiplex network between any two nodes. Since multilinks distinguish all the possible ways in which the links in different layers can overlap, the Functional Multiplex PageRank can describe important non-linear effects when large relevance or small relevance is assigned to multilinks with overlap. Here we apply the Functional Page Rank to the multiplex airport networks, to the neuronal network of the nematode C. elegans, and to social collaboration and citation networks between scientists. This analysis reveals important differences existing between the most central nodes of these networks, and the correlations between their so-called pattern to success.

  7. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

    Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  8. A geometric atlas to predict lung tumor shrinkage for radiotherapy treatment planning

    Science.gov (United States)

    Zhang, Pengpeng; Rimner, Andreas; Yorke, Ellen; Hu, Yu-Chi; Kuo, Licheng; Apte, Aditya; Lockney, Natalie; Jackson, Andrew; Mageras, Gig; Deasy, Joseph O.

    2017-02-01

    To develop a geometric atlas that can predict tumor shrinkage and guide treatment planning for non-small-cell lung cancer. To evaluate the impact of the shrinkage atlas on the ability of tumor dose escalation. The creation of a geometric atlas included twelve patients with lung cancer who underwent both planning CT and weekly CBCT for radiotherapy planning and delivery. The shrinkage pattern from the original pretreatment to the residual posttreatment tumor was modeled using a principal component analysis, and used for predicting the spatial distribution of the residual tumor. A predictive map was generated by unifying predictions from each individual patient in the atlas, followed by correction for the tumor’s surrounding tissue distribution. Sensitivity, specificity, and accuracy of the predictive model for classifying voxels inside the original gross tumor volume were evaluated. In addition, a retrospective study of predictive treatment planning (PTP) escalated dose to the predicted residual tumor while maintaining the same level of predicted complication rates for a clinical plan delivering uniform dose to the entire tumor. The effect of uncertainty on the predictive model’s ability to escalate dose was also evaluated. The sensitivity, specificity and accuracy of the predictive model were 0.73, 0.76, and 0.74, respectively. The area under the receiver operating characteristic curve for voxel classification was 0.87. The Dice coefficient and mean surface distance between the predicted and actual residual tumor averaged 0.75, and 1.6 mm, respectively. The PTP approach allowed elevation of PTV D95 and mean dose to the actual residual tumor by 6.5 Gy and 10.4 Gy, respectively, relative to the clinical uniform dose approach. A geometric atlas can provide useful information on the distribution of resistant tumors and effectively guide dose escalation to the tumor without compromising the organs at risk complications. The atlas can be further refined by using

  9. Predicting CD4 count changes among patients on antiretroviral treatment: Application of data mining techniques.

    Science.gov (United States)

    Kebede, Mihiretu; Zegeye, Desalegn Tigabu; Zeleke, Berihun Megabiaw

    2017-12-01

    To monitor the progress of therapy and disease progression, periodic CD4 counts are required throughout the course of HIV/AIDS care and support. The demand for CD4 count measurement is increasing as ART programs expand over the last decade. This study aimed to predict CD4 count changes and to identify the predictors of CD4 count changes among patients on ART. A cross-sectional study was conducted at the University of Gondar Hospital from 3,104 adult patients on ART with CD4 counts measured at least twice (baseline and most recent). Data were retrieved from the HIV care clinic electronic database and patients` charts. Descriptive data were analyzed by SPSS version 20. Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was followed to undertake the study. WEKA version 3.8 was used to conduct a predictive data mining. Before building the predictive data mining models, information gain values and correlation-based Feature Selection methods were used for attribute selection. Variables were ranked according to their relevance based on their information gain values. J48, Neural Network, and Random Forest algorithms were experimented to assess model accuracies. The median duration of ART was 191.5 weeks. The mean CD4 count change was 243 (SD 191.14) cells per microliter. Overall, 2427 (78.2%) patients had their CD4 counts increased by at least 100 cells per microliter, while 4% had a decline from the baseline CD4 value. Baseline variables including age, educational status, CD8 count, ART regimen, and hemoglobin levels predicted CD4 count changes with predictive accuracies of J48, Neural Network, and Random Forest being 87.1%, 83.5%, and 99.8%, respectively. Random Forest algorithm had a superior performance accuracy level than both J48 and Artificial Neural Network. The precision, sensitivity and recall values of Random Forest were also more than 99%. Nearly accurate prediction results were obtained using Random Forest algorithm. This algorithm could be

  10. Purpose in Life Predicts Treatment Outcome Among Adult Cocaine Abusers in Treatment

    Science.gov (United States)

    Martin, Rosemarie A.; MacKinnon, Selene; Johnson, Jennifer; Rohsenow, Damaris J.

    2010-01-01

    A sense of purpose in life has been positively associated with mental health and well-being and has been negatively associated with alcohol use in correlational and longitudinal studies, but has not been studied as a predictor of cocaine treatment outcome. This study examined pre-treatment purpose in life as a predictor of response to a 30-day residential substance use treatment program among 154 participants with cocaine dependence. Purpose in life was unrelated to cocaine or alcohol use during the 6 months pretreatment. After controlling for age, baseline use, and depressive symptoms, purpose in life significantly (p purpose in life may be an important aspect of treatment among cocaine dependent patients. PMID:21129893

  11. Implicit identification with death predicts change in suicide ideation during psychiatric treatment in adolescents.

    Science.gov (United States)

    Glenn, Catherine R; Kleiman, Evan M; Coppersmith, Daniel D L; Santee, Angela C; Esposito, Erika C; Cha, Christine B; Nock, Matthew K; Auerbach, Randy P

    2017-12-01

    Suicidal thoughts and behaviors are major public health concerns in youth. Unfortunately, knowledge of reliable predictors of suicide risk in adolescents is limited. Promising research using a death stimuli version of the Implicit Association Test (Death IAT) indicates that stronger identification with death differs between adults with and without a history of suicidal thoughts and behaviors and uniquely predicts suicide ideation and behavior. However, research in adolescents is lacking and existing findings have been mixed. This study extends previous research by testing whether implicit identification with death predicts changes in suicide ideation during psychiatric treatment in adolescents. Participants included 276 adolescents, ages 13-19, admitted to a short-term residential treatment program. At hospital admission and discharge, adolescents completed the Death IAT and measures of recent suicidal thoughts. At admission, implicit identification with death was associated with recent suicide ideation, but did not differ between those who engaged in prior suicidal behavior and those who did not. Prospectively, adolescents' implicit identification with death at admission significantly predicted their suicide ideation severity at discharge, above and beyond explicit suicide ideation. However, this effect only was significant for adolescents with longer treatment stays (i.e., more than 13 days). Implicit identification with death predicts suicidal thinking among adolescents in psychiatric treatment. Findings clarify over what period of time implicit cognition about death may predict suicide risk in adolescents. © 2017 Association for Child and Adolescent Mental Health.

  12. Prediction Score for Antimony Treatment Failure in Patients with Ulcerative Leishmaniasis Lesions

    Science.gov (United States)

    Dujardin, Jean Claude; Llanos-Cuentas, Alejandro; Chappuis, François; Zimic, Mirko

    2012-01-01

    Background Increased rates for failure in leishmaniasis antimony treatment have been recently recognized worldwide. Although several risk factors have been identified there is no clinical score to predict antimony therapy failure of cutaneous leishmaniasis. Methods A case control study was conducted in Peru from 2001 to 2004. 171 patients were treated with pentavalent antimony and followed up to at least 6 months to determine cure or failure. Only patients with ulcerative cutaneous leishmaniasis (N = 87) were considered for data analysis. Epidemiological, demographical, clinical and laboratory data were analyzed to identify risk factors for treatment failure. Two prognostic scores for antimonial treatment failure were tested for sensitivity and specificity to predict antimony therapy failure by comparison with treatment outcome. Results Among 87 antimony-treated patients, 18 (21%) failed the treatment and 69 (79%) were cured. A novel risk factor for treatment failure was identified: presence of concomitant distant lesions. Patients presenting concomitant-distant lesions showed a 30.5-fold increase in the risk of treatment failure compared to other patients. The best prognostic score for antimonial treatment failure showed a sensitivity of 77.78% and specificity of 95.52% to predict antimony therapy failure. Conclusions A prognostic score including a novel risk factor was able to predict antimonial treatment failure in cutaneous leishmaniasis with high specificity and sensitivity. This prognostic score presents practical advantages as it relies on clinical and epidemiological characteristics, easily obtained by physicians or health workers, and makes it a promising clinical tool that needs to be validated before their use for developing countries. PMID:22720098

  13. Predicting Treatment Success in Child and Parent Therapy Among Families in Poverty.

    Science.gov (United States)

    Mattek, Ryan J; Harris, Sara E; Fox, Robert A

    2016-01-01

    Behavior problems are prevalent in young children and those living in poverty are at increased risk for stable, high-intensity behavioral problems. Research has demonstrated that participation in child and parent therapy (CPT) programs significantly reduces problematic child behaviors while increasing positive behaviors. However, CPT programs, particularly those implemented with low-income populations, frequently report high rates of attrition (over 50%). Parental attributional style has shown some promise as a contributing factor to treatment attendance and termination in previous research. The authors examined if parental attributional style could predict treatment success in a CPT program, specifically targeting low-income urban children with behavior problems. A hierarchical logistic regression was used with a sample of 425 families to assess if parent- and child-referent attributions variables predicted treatment success over and above demographic variables and symptom severity. Parent-referent attributions, child-referent attributions, and child symptom severity were found to be significant predictors of treatment success. Results indicated that caregivers who viewed themselves as a contributing factor for their child's behavior problems were significantly more likely to demonstrate treatment success. Alternatively, caregivers who viewed their child as more responsible for their own behavior problems were less likely to demonstrate treatment success. Additionally, more severe behavior problems were also predictive of treatment success. Clinical and research implications of these results are discussed.

  14. Prediction of lip response to orthodontic treatment using a multivariable regression model.

    Science.gov (United States)

    Shirvani, Amin; Sadeghian, Saeid; Abbasi, Safieh

    2016-01-01

    This was a retrospective cephalometric study to develop a more precise estimation of soft tissue changes related to underlying tooth movment than simple relatioship betweenhard and soft tissues. The lateral cephalograms of 61 adult patients undergoing orthodontic treatment (31 = premolar extraction, 31 = nonextraction) were obtained, scanned and digitized before and immediately after the end of treatment. Hard and soft tissues, angular and linear measures were calculated by Viewbox 4.0 software. The changes of the values were analyzed using paired t-test. The accuracy of predictions of soft tissue changes were compared with two methods: (1) Use of ratios of the means of soft tissue to hard tissue changes (Viewbox 4.0 Software), (2) use of stepwise multivariable regression analysis to create prediction equations for soft tissue changes at superior labial sulcus, labrale superius, stomion superius, inferior labial sulcus, labrale inferius, stomion inferius (all on a horizontal plane). Stepwise multiple regressions to predict lip movements showed strong relations for the upper lip (adjusted R (2) = 0.92) and the lower lip (adjusted R (2) = 0.91) in the extraction group. Regression analysis showed slightly weaker relations in the nonextraction group. Within the limitation of this study, multiple regression technique was slightly more accurate than the ratio of mean prediction (Viewbox4.0 software) and appears to be useful in the prediction of soft tissue changes. As the variability of the predicted individual outcome seems to be relatively high, caution should be taken in predicting hard and soft tissue positional changes.

  15. Psychological stress as a measure for treatment response prediction in idiopathic sudden hearing loss.

    Science.gov (United States)

    Roh, Daeyoung; Chao, Janet Ren; Kim, Do Hoon; Yoon, Kyung Hee; Jung, Jae Hoon; Lee, Chang Hyun; Shin, Ji-Hyeon; Kim, Min Jae; Park, Chan Hum; Lee, Jun Ho

    2017-11-01

    Early prediction of therapeutic outcomes could reduce exposure to ineffective treatments and optimize clinical outcomes. However, none of the known otologic predictors is amenable to therapeutic intervention for idiopathic sudden sensorineural hearing loss (ISSNHL). The aims of this study were to investigate psychological stress as a potential predictor to discriminate outcomes in ISSNHL. Various psychological measures were conducted including structured interview assessment tools in patients with recently diagnosed ISSNHL before initiating treatment. Using logistic regression analysis, we identified the predictors of treatment response and estimated the probability of treatment response in 50 ISSNHL patients who participated in a clinical trial. Treatment non-responders were significantly differentiated from responders by various psychological problems. The depression subscore of Modified form of Stress Response Inventory (SRI-MF) (p=0.007) and duration of hearing loss (p=0.045) significantly predicted treatment response after controlling other clinical correlates. The same predictors were identified from different treatment response measured using Siegel's criteria. The most discriminative measure for treatment response was SRI-MF depression score with an overall classification accuracy of 73%. We found depressive stress response to be the strong predictor of treatment response in patients with ISSNHL. Our results highlight the potential use of the psychiatric approach as a tool for enhancing therapeutic outcomes. Future stress intervention studies with larger number of ISSNHL patients are needed. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Purpose in life predicts treatment outcome among adult cocaine abusers in treatment.

    Science.gov (United States)

    Martin, Rosemarie A; MacKinnon, Selene; Johnson, Jennifer; Rohsenow, Damaris J

    2011-03-01

    A sense of purpose in life has been positively associated with mental health and well-being and has been negatively associated with alcohol use in correlational and longitudinal studies but has not been studied as a predictor of cocaine treatment outcome. This study examined pretreatment purpose in life as a predictor of response to a 30-day residential substance use treatment program among 154 participants with cocaine dependence. Purpose in life was unrelated to cocaine or alcohol use during the 6 months pretreatment. After controlling for age, baseline use, and depressive symptoms, purpose in life significantly (p purpose in life may be an important aspect of treatment among cocaine-dependent patients. Copyright © 2011 Elsevier Inc. All rights reserved.

  17. Predicting post-traumatic stress disorder treatment response in refugees: Multilevel analysis.

    Science.gov (United States)

    Haagen, Joris F G; Ter Heide, F Jackie June; Mooren, Trudy M; Knipscheer, Jeroen W; Kleber, Rolf J

    2017-03-01

    Given the recent peak in refugee numbers and refugees' high odds of developing post-traumatic stress disorder (PTSD), finding ways to alleviate PTSD in refugees is of vital importance. However, there are major differences in PTSD treatment response between refugees, the determinants of which are largely unknown. This study aimed at improving PTSD treatment for adult refugees by identifying PTSD treatment response predictors. A prospective longitudinal multilevel modelling design was used to predict PTSD severity scores over time. We analysed data from a randomized controlled trial with pre-, post-, and follow-up measurements of the safety and efficacy of eye movement desensitization and reprocessing and stabilization in asylum seekers and refugees suffering from PTSD. Lack of refugee status, comorbid depression, demographic, trauma-related and treatment-related variables were analysed as potential predictors of PTSD treatment outcome. Treatment outcome data from 72 participants were used. The presence (B = 6.5, p = .03) and severity (B = 6.3, p Refugee patients who suffer from PTSD and severe comorbid depression benefit less from treatment aimed at alleviating PTSD. Results highlight the need for treatment adaptations for PTSD and comorbid severe depression in traumatized refugees, including testing whether initial targeting of severe depressive symptoms increases PTSD treatment effectiveness. There are differences in post-traumatic stress disorder (PTSD) treatment response between traumatized refugees. Comorbid depressive disorder and depression severity predict poor PTSD response. Refugees with PTSD and severe depression may not benefit from PTSD treatment. Targeting comorbid severe depression before PTSD treatment is warranted. This study did not correct for multiple hypothesis testing. Comorbid depression may differentially impact alternative PTSD treatments. © 2016 The British Psychological Society.

  18. Predictive score for the systemic treatment of unruptured ectopic pregnancy with a single dose of methotrexate.

    Science.gov (United States)

    Elito, J; Reichmann, A P; Uchiyama, M N; Camano, L

    1999-11-01

    To evaluate the efficacy of a predictive score for the systemic treatment of unruptured ectopic pregnancy with a single dose of methotrexate in order to select the best cases for the medical treatment. Our study included 40 patients. The inclusion criteria were: hemodynamic stability; adnexal mass or = 5 were treated successfully (29/30 - 97%), while those with grade or = 5. Federation of Gynecology and Obstetrics.

  19. Therapygenetics: Using genetic markers to predict response to psychological treatment for mood and anxiety disorders

    OpenAIRE

    Lester, Kathryn J; Eley, Thalia C

    2013-01-01

    Abstract Considerable variation is evident in response to psychological therapies for mood and anxiety disorders. Genetic factors alongside environmental variables and gene-environment interactions are implicated in the etiology of these disorders and it is plausible that these same factors may also be important in predicting individual differences in response to psychological treatment. In this article, we review the evidence that genetic variation influences psychological treatment outcomes...

  20. Does impulsivity predict outcome in treatment for binge eating disorder? A multimodal investigation

    OpenAIRE

    Manasse, Stephanie M.; Espel, Hallie M.; Schumacher, Leah M.; Kerrigan, Stephanie G.; Zhang, Fengqing; Forman, Evan M.; Juarascio, Adrienne S.

    2016-01-01

    Multiple dimensions of impulsivity (e.g., affect-driven impulsivity, impulsive inhibition – both general and food-specific, and impulsive decision-making) are associated with binge eating pathology cross-sectionally, yet the literature on whether impulsivity predicts treatment outcome is limited. The present pilot study explored impulsivity-related predictors of 20-week outcome in a small open trial (n=17) of a novel treatment for binge eating disorder. Overall, dimensions of impulsivity rela...

  1. DCE-MRI for Pre-Treatment Prediction and Post-Treatment Assessment of Treatment Response in Sites of Squamous Cell Carcinoma in the Head and Neck.

    Directory of Open Access Journals (Sweden)

    Ann D King

    Full Text Available It is important to identify patients with head and neck squamous cell carcinoma (SCC who fail to respond to chemoradiotherapy so that they can undergo post-treatment salvage surgery while the disease is still operable. This study aimed to determine the diagnostic performance of dynamic contrast enhanced (DCE-MRI using a pharmacokinetic model for pre-treatment predictive imaging, as well as post-treatment diagnosis, of residual SCC at primary and nodal sites in the head and neck.Forty-nine patients with 83 SCC sites (primary and/or nodal underwent pre-treatment DCE-MRI, and 43 patients underwent post-treatment DCE-MRI, of which 33 SCC sites had a residual mass amenable to analysis. Pre-treatment, post-treatment and % change in the mean Ktrans, kep, ve and AUGC were obtained from SCC sites. Logistic regression was used to correlate DCE parameters at each SCC site with treatment response at the same site, based on clinical outcome at that site at a minimum of two years.None of the pre-treatment DCE-MRI parameters showed significant correlations with SCC site failure (SF (29/83 sites or site control (SC (54/83 sites. Post-treatment residual masses with SF (14/33 had significantly higher kep (p = 0.05, higher AUGC (p = 0.02, and lower % reduction in AUGC (p = 0.02, than residual masses with SC (19/33, with the % change in AUGC remaining significant on multivariate analysis.Pre-treatment DCE-MRI did not predict which SCC sites would fail treatment, but post-treatment DCE-MRI showed potential for identifying residual masses that had failed treatment.

  2. Prediction of treatment outcome with bioimpedance measurements in breast cancer related lymphedema patients.

    Science.gov (United States)

    Kim, Leesuk; Jeon, Jae Yong; Sung, In Young; Jeong, Soon Yong; Do, Jung Hwa; Kim, Hwa Jung

    2011-10-01

    To investigate the usefulness of bioimpedance measurement for predicting the treatment outcome in breast cancer related lymphedema (BCRL) patients. Unilateral BCRL patients who received complex decongestive therapy (CDT) for 2 weeks (5 days per week) were enrolled in this study. We measured the ratio of extracellular fluid (ECF) volume by using bioelectrical impedance spectroscopy (BIS), and single frequency bioimpedance analysis (SFBIA) at a 5 kHz frequency before treatment. Arm circumferences were measured at 10 cm above and below the elbow before and after treatment. We also investigated whether there is correlation between ECF ratio and SFBIA ratio with the change of arm circumference after CDT. A total of 73 patients were enrolled in this study. The higher ECF ratio was significantly correlated with higher reduction of arm circumference at both above and below the elbow after treatment, but the higher SFBIA ratio was correlated only with the higher reduction of arm circumference below the elbow. These results show that ECF volume measurements and SFBIA before treatment are useful tools for predicting the outcome of patients with lymphedema. We concluded that ECF volume measure can be used as a screening tool for predicting treatment outcome of BCRL patients.

  3. Pre-treatment cortisol awakening response predicts symptom reduction in posttraumatic stress disorder after treatment

    NARCIS (Netherlands)

    Rapcencu, A E; Gorter, R; Kennis, M; van Rooij, S J H; Geuze, E

    Dysfunction of the HPA-axis has frequently been found in the aftermath of trauma exposure with or without PTSD. Decreasing HPA-axis reactivity to different stress cues has been reported during PTSD treatment. The cortisol awakening response (CARi) is a well-validated, standardized measure of

  4. Do treatment quality indicators predict cardiovascular outcomes in patients with diabetes?

    Directory of Open Access Journals (Sweden)

    Grigory Sidorenkov

    Full Text Available BACKGROUND: Landmark clinical trials have led to optimal treatment recommendations for patients with diabetes. Whether optimal treatment is actually delivered in practice is even more important than the efficacy of the drugs tested in trials. To this end, treatment quality indicators have been developed and tested against intermediate outcomes. No studies have tested whether these treatment quality indicators also predict hard patient outcomes. METHODS: A cohort study was conducted using data collected from >10.000 diabetes patients in the Groningen Initiative to Analyze Type 2 Treatment (GIANTT database and Dutch Hospital Data register. Included quality indicators measured glucose-, lipid-, blood pressure- and albuminuria-lowering treatment status and treatment intensification. Hard patient outcome was the composite of cardiovascular events and all-cause death. Associations were tested using Cox regression adjusting for confounding, reporting hazard ratios (HR with 95% confidence intervals. RESULTS: Lipid and albuminuria treatment status, but not blood pressure lowering treatment status, were associated with the composite outcome (HR = 0.77, 0.67-0.88; HR = 0.75, 0.59-0.94. Glucose lowering treatment status was associated with the composite outcome only in patients with an elevated HbA1c level (HR = 0.72, 0.56-0.93. Treatment intensification with glucose-lowering but not with lipid-, blood pressure- and albuminuria-lowering drugs was associated with the outcome (HR = 0.73, 0.60-0.89. CONCLUSION: Treatment quality indicators measuring lipid- and albuminuria-lowering treatment status are valid quality measures, since they predict a lower risk of cardiovascular events and mortality in patients with diabetes. The quality indicators for glucose-lowering treatment should only be used for restricted populations with elevated HbA1c levels. Intriguingly, the tested indicators for blood pressure-lowering treatment did not predict patient

  5. Predicting brain stimulation treatment outcomes of depressed patients through the classification of EEG oscillations.

    Science.gov (United States)

    Al-Kaysi, Alaa M; Al-Ani, Ahmed; Loo, Colleen K; Breakspear, Michael; Boonstra, Tjeerd W

    2016-08-01

    Major depressive disorder (MDD) is a mental disorder that is characterized by negative thoughts, mood and behavior. Transcranial direct current stimulation (tDCS) has recently emerged as a promising brain-stimulation treatment for MDD. A standard tDCS treatment involves numerous sessions that run over a few weeks, however, not all participants respond to this type of treatment. This study aims to predict which patients improve in mood and cognition in response to tDCS treatment by analyzing electroencephalography (EEG) of MDD patients that was collected at the start of tDCS treatment. This is achieved through classifying power spectral density (PSD) of resting-state EEG using support vector machine (SVM), linear discriminate analysis (LDA) and extreme learning machine (ELM). Participants were labelled as improved/not improved based on the change in mood and cognitive scores. The obtained classification results of all channel pair combinations are used to identify the most relevant brain regions and channels for this classification task. We found the frontal channels to be particularly informative for the prediction of the clinical outcome of the tDCS treatment. Subject independent results reveal that our proposed method enables the correct identification of the treatment outcome for seven of the ten participants for mood improvement and nine of ten participants for cognitive improvement. This represents an encouraging sign that EEG-based classification may help to tailor the selection of patients for treatment with tDCS brain stimulation.

  6. Predictive value of early 18F-FDG PET/CT studies for treatment response evaluation to ipilimumab in metastatic melanoma: preliminary results of an ongoing study.

    Science.gov (United States)

    Sachpekidis, Christos; Larribere, Lionel; Pan, Leyun; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia; Hassel, Jessica C

    2015-03-01

    both early and late responses (log-rank p PET/CT after two cycles of ipilimumab is highly predictive of the final treatment outcome in patients with PMD and SMD.

  7. Predictive Factors for Delivery within 7 Days after Successful 48-Hour Treatment of Threatened Preterm Labor

    NARCIS (Netherlands)

    Roos, Carolien; Schuit, Ewoud; Scheepers, Hubertina C J; Bloemenkamp, Kitty W M; Bolte, Antoinette C; Duvekot, Hans J J; van Eyck, Jim; Kok, Joke H; Kwee, Anneke; Merién, Ashley E R; Opmeer, Brent C; Oudijk, Martijn A; van Pampus, Mariëlle G; Papatsonis, Dimitri N M; Porath, Martina M; Sollie, Krystyna M; Spaanderman, Marc E A; Vijgen, Sylvia M C; Willekes, Christine; Lotgering, Fred K; van der Post, Joris A M; Mol, Ben Willem J

    2015-01-01

    Objective The aim of this study was to assess which characteristics and results of vaginal examination are predictive for delivery within 7 days, in women with threatened preterm labor after initial treatment. Study Design A secondary analysis of a randomized controlled trial on maintenance

  8. Predictive Factors for Delivery within 7 Days after Successful 48-Hour Treatment of Threatened Preterm Labor

    NARCIS (Netherlands)

    Roos, C.; Schuit, E.; Scheepers, H.C.; Bloemenkamp, K.W.; Bolte, A.C.; Duvekot, H.J.; Eyck, J. van; Kok, J.H.; Kwee, A.; Merien, A.E.; Opmeer, B.C.; Oudijk, M.A.; Pampus, M.G. van; Papatsonis, D.N.; Porath, M.M.; Sollie, K.M.; Spaanderman, M.E.; Vijgen, S.M.; Willekes, C.; Lotgering, F.K.; Post, J.A. van der; Mol, B.W.

    2015-01-01

    Objective The aim of this study was to assess which characteristics and results of vaginal examination are predictive for delivery within 7 days, in women with threatened preterm labor after initial treatment. Study Design A secondary analysis of a randomized controlled trial on maintenance

  9. Predictive Factors for Delivery within 7 Days after Successful 48-Hour Treatment of Threatened Preterm Labor.

    NARCIS (Netherlands)

    Roos, Carolien; Schuit, Ewoud; Scheepers, Hubertina C J; Bloemenkamp, Kitty W M; Bolte, Antoinette C; Duvekot, Hans J J; van Eyck, Jim; Kok, Joke H; Kwee, Anneke; Merién, Ashley E R; Opmeer, Brent C; Oudijk, Martijn A; van Pampus, Mariëlle G; Papatsonis, Dimitri N M; Porath, Martina M; Sollie, Krystyna M; Spaanderman, Marc E A; Vijgen, Sylvia M C; Willekes, Christine; Lotgering, Fred K; van der Post, Joris A M; Mol, Ben Willem J

    2015-01-01

    Objective The aim of this study was to assess which characteristics and results of vaginal examination are predictive for delivery within 7 days, in women with threatened preterm labor after initial treatment. Study Design A secondary analysis of a randomized controlled trial on maintenance

  10. Prediction of immunophenotype, treatment response, and relapse in childhood acute lymphoblastic leukemia using DNA microarrays

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Juncker, Agnieszka; Schmiegelow, K.

    2004-01-01

    Gene expression profiling is a promising tool for classification of pediatric acute lymphoblastic leukemia ( ALL). We analyzed the gene expression at the time of diagnosis for 45 Danish children with ALL. The prediction of 5-year event-free survival or relapse after treatment by NOPHO-ALL92 or 2000...

  11. Predictive Properties of the Gesell School Readiness Screening Test within Samples from Two Treatment Contexts.

    Science.gov (United States)

    Banerji, Madhabi

    The predictive properties of the Gesell School Readiness Screening Test (GSRT) were examined, taking into account the stated purposes of the test and the context of test use. Two samples were used: (1) a control sample of 55 students (21 males and 34 females) whose GSRT scores were not used for placement or tracking; and (2) a treatment sample of…

  12. Prediction of the outcome of orthodontic treatment of Class III malocclusions--a systematic review

    NARCIS (Netherlands)

    Fudalej, P.S.; Dragan, M.; Wedrychowska-Szulc, B.

    2011-01-01

    The purpose of this study was to systematically review the orthodontic literature to assess the effectiveness of a prediction of outcome of orthodontic treatment in subjects with a Class III malocclusion. A structured search of electronic databases, as well as hand searching, retrieved 232

  13. Treatment Gain for Sexual Offenders against Children Predicts Reduced Recidivism: A Comparative Validity Study

    Science.gov (United States)

    Beggs, Sarah M.; Grace, Randolph C.

    2011-01-01

    Objective: To determine whether pro-social treatment change in sexual offenders would predict reductions in recidivism beyond static and dynamic risk factors measured at pretreatment and whether different methods for assessing change based on self-reports and structured clinical rating systems would show convergent validity. Method: We compared 3…

  14. Diagnostic Agreement Predicts Treatment Process and Outcomes in Youth Mental Health Clinics

    Science.gov (United States)

    Jensen-Doss, Amanda; Weisz, John R.

    2008-01-01

    Several studies have documented low rates of agreement between clinician- and researcher-generated diagnoses. However, little is known about whether this lack of agreement has implications for the processes and outcomes of subsequent treatment. To study this possibility, the authors used diagnostic agreement to predict therapy engagement and…

  15. Predictive value of self-reported and observer-rated defense style in depression treatment.

    NARCIS (Netherlands)

    Van, H.L.; Dekker, J.J.M.; Peen, J.; Abraham, R.E.; Schoevers, R.

    2009-01-01

    This study explored the predictive value of observer-rated and self-reported defensive functioning on the outcome of psychotherapy for the treatment of depression. Defense styles were measured according to the Developmental Profile (DP) and the Defense Style Questionnaire (DSQ) in 81 moderately

  16. RAMAN SPECTROSCOPIC STUDY ON PREDICTION OF TREATMENT RESPONSE IN CERVICAL CANCERS

    Directory of Open Access Journals (Sweden)

    S. RUBINA

    2013-04-01

    Full Text Available Concurrent chemoradiotherapy (CCRT is the choice of treatment for locally advanced cervical cancers; however, tumors exhibit diverse response to treatment. Early prediction of tumor response leads to individualizing treatment regimen. Response evaluation criteria in solid tumors (RECIST, the current modality of tumor response assessment, is often subjective and carried out at the first visit after treatment, which is about four months. Hence, there is a need for better predictive tool for radioresponse. Optical spectroscopic techniques, sensitive to molecular alteration, are being pursued as potential diagnostic tools. Present pilot study aims to explore the fiber-optic-based Raman spectroscopy approach in prediction of tumor response to CCRT, before taking up extensive in vivo studies. Ex vivo Raman spectra were acquired from biopsies collected from 11 normal (148 spectra, 16 tumor (201 spectra and 13 complete response (151 CR spectra, one partial response (8 PR spectra and one nonresponder (8 NR spectra subjects. Data was analyzed using principal component linear discriminant analysis (PC-LDA followed by leave-one-out cross-validation (LOO-CV. Findings suggest that normal tissues can be efficiently classified from both pre- and post-treated tumor biopsies, while there is an overlap between pre- and post-CCRT tumor tissues. Spectra of CR, PR and NR tissues were subjected to principal component analysis (PCA and a tendency of classification was observed, corroborating previous studies. Thus, this study further supports the feasibility of Raman spectroscopy in prediction of tumor radioresponse and prospective noninvasive in vivo applications.

  17. Threat Related Selective Attention Predicts Treatment Success in Childhood Anxiety Disorders

    Science.gov (United States)

    Legerstee, Jeroen S.; Tulen, Joke H. M.; Kallen, Victor L.; Dieleman, Gwen C.; Treffers, Philip D. A.; Verhulst, Frank C.; Utens, Elisabeth M. W. J.

    2009-01-01

    Threat-related selective attention was found to predict the success of the treatment of childhood anxiety disorders through administering a pictorial dot-probe task to 131 children with anxiety disorders prior to cognitive behavioral therapy. The diagnostic status of the subjects was evaluated with a semistructured clinical interview at both pre-…

  18. Predictive validity of the Structured Assessment of Violence Risk in Youth (SAVRY) during residential treatment

    NARCIS (Netherlands)

    Lodewijks, H.P.B.; Doreleijers, T.A.H.; de Ruiter, C.; Borum, R.

    2008-01-01

    This prospective study examines the predictive validity of the Dutch version of the Structured Assessment of Violence Risk in Youth (SAVRY) by examining relationships between SAVRY scores and various types of disruptive behavior during residential treatment. The SAVRY, a risk assessment instrument,

  19. Brain potentials measured during a Go/NoGo task predict completion of substance abuse treatment.

    Science.gov (United States)

    Steele, Vaughn R; Fink, Brandi C; Maurer, J Michael; Arbabshirani, Mohammad R; Wilber, Charles H; Jaffe, Adam J; Sidz, Anna; Pearlson, Godfrey D; Calhoun, Vince D; Clark, Vincent P; Kiehl, Kent A

    2014-07-01

    U.S. nationwide estimates indicate that 50% to 80% of prisoners have a history of substance abuse or dependence. Tailoring substance abuse treatment to specific needs of incarcerated individuals could improve effectiveness of treating substance dependence and preventing drug abuse relapse. We tested whether pretreatment neural measures of a response inhibition (Go/NoGo) task would predict which individuals would or would not complete a 12-week cognitive behavioral substance abuse treatment program. Adult incarcerated participants (n = 89; women n = 55) who volunteered for substance abuse treatment performed a Go/NoGo task while event-related potentials (ERPs) were recorded. Stimulus- and response-locked ERPs were compared between participants who completed (n = 68; women = 45) and discontinued (n = 21; women = 10) treatment. As predicted, stimulus-locked P2, response-locked error-related negativity (ERN/Ne), and response-locked error positivity (Pe), measured with windowed time-domain and principal component analysis, differed between groups. Using logistic regression and support-vector machine (i.e., pattern classifiers) models, P2 and Pe predicted treatment completion above and beyond other measures (i.e., N2, P300, ERN/Ne, age, sex, IQ, impulsivity, depression, anxiety, motivation for change, and years of drug abuse). Participants who discontinued treatment exhibited deficiencies in sensory gating, as indexed by smaller P2; error-monitoring, as indexed by smaller ERN/Ne; and adjusting response strategy posterror, as indexed by larger Pe. The combination of P2 and Pe reliably predicted 83.33% of individuals who discontinued treatment. These results may help in the development of individualized therapies, which could lead to more favorable, long-term outcomes. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

  20. A support vector machine tool for adaptive tomotherapy treatments: Prediction of head and neck patients criticalities.

    Science.gov (United States)

    Guidi, Gabriele; Maffei, Nicola; Vecchi, Claudio; Ciarmatori, Alberto; Mistretta, Grazia Maria; Gottardi, Giovanni; Meduri, Bruno; Baldazzi, Giuseppe; Bertoni, Filippo; Costi, Tiziana

    2015-07-01

    Adaptive radiation therapy (ART) is an advanced field of radiation oncology. Image-guided radiation therapy (IGRT) methods can support daily setup and assess anatomical variations during therapy, which could prevent incorrect dose distribution and unexpected toxicities. A re-planning to correct these anatomical variations should be done daily/weekly, but to be applicable to a large number of patients, still require time consumption and resources. Using unsupervised machine learning on retrospective data, we have developed a predictive network, to identify patients that would benefit of a re-planning. 1200 MVCT of 40 head and neck (H&N) cases were re-contoured, automatically, using deformable hybrid registration and structures mapping. Deformable algorithm and MATLAB(®) homemade machine learning process, developed, allow prediction of criticalities for Tomotherapy treatments. Using retrospective analysis of H&N treatments, we have investigated and predicted tumor shrinkage and organ at risk (OAR) deformations. Support vector machine (SVM) and cluster analysis have identified cases or treatment sessions with potential criticalities, based on dose and volume discrepancies between fractions. During 1st weeks of treatment, 84% of patients shown an output comparable to average standard radiation treatment behavior. Starting from the 4th week, significant morpho-dosimetric changes affect 77% of patients, suggesting need for re-planning. The comparison of treatment delivered and ART simulation was carried out with receiver operating characteristic (ROC) curves, showing monotonous increase of ROC area. Warping methods, supported by daily image analysis and predictive tools, can improve personalization and monitoring of each treatment, thereby minimizing anatomic and dosimetric divergences from initial constraints. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  1. HER2 status for prognosis and prediction of treatment efficacy in adenocarcinomas: a review.

    Science.gov (United States)

    Thibault, Constance; Khodari, Wassim; Lequoy, Marie; Gligorov, Joseph; Belkacémi, Yazid

    2013-10-01

    The past few years have seen flourish new biologic parameters for cancer prognosis that are revolutionizing therapeutic strategies. HER-2 is in this perspective a striking example, as it is now a key element for the care of 15-20% of breast cancer. HER-2 overexpression has first been reported as a prognostic factor before its consideration as a main parameter to predict treatment efficacy. However, although HER-2 status is now also used as a prognostic factor for many cancers, its ability to predict the action of trastuzumab in these new contexts is much lower than in breast cancer. In this literature review, we aimed to discuss HER-2 overexpression as a prognostic factor and as a predictive parameter of treatment response in selected solid tumors with a focus on adenocarcinomas. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  2. The Privilege of Ranking: Google Plays Ball.

    Science.gov (United States)

    Wiggins, Richard

    2003-01-01

    Discussion of ranking systems used in various settings, including college football and academic admissions, focuses on the Google search engine. Explains the PageRank mathematical formula that scores Web pages by connecting the number of links; limitations, including authenticity and accuracy of ranked Web pages; relevancy; adjusting algorithms;…

  3. Methodology, Meaning and Usefulness of Rankings

    Science.gov (United States)

    Williams, Ross

    2008-01-01

    University rankings are having a profound effect on both higher education systems and individual universities. In this paper we outline these effects, discuss the desirable characteristics of a good ranking methodology and document existing practice, with an emphasis on the two main international rankings (Shanghai Jiao Tong and THES-QS). We take…

  4. Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.

    Science.gov (United States)

    Kalincik, Tomas; Manouchehrinia, Ali; Sobisek, Lukas; Jokubaitis, Vilija; Spelman, Tim; Horakova, Dana; Havrdova, Eva; Trojano, Maria; Izquierdo, Guillermo; Lugaresi, Alessandra; Girard, Marc; Prat, Alexandre; Duquette, Pierre; Grammond, Pierre; Sola, Patrizia; Hupperts, Raymond; Grand'Maison, Francois; Pucci, Eugenio; Boz, Cavit; Alroughani, Raed; Van Pesch, Vincent; Lechner-Scott, Jeannette; Terzi, Murat; Bergamaschi, Roberto; Iuliano, Gerardo; Granella, Franco; Spitaleri, Daniele; Shaygannejad, Vahid; Oreja-Guevara, Celia; Slee, Mark; Ampapa, Radek; Verheul, Freek; McCombe, Pamela; Olascoaga, Javier; Amato, Maria Pia; Vucic, Steve; Hodgkinson, Suzanne; Ramo-Tello, Cristina; Flechter, Shlomo; Cristiano, Edgardo; Rozsa, Csilla; Moore, Fraser; Luis Sanchez-Menoyo, Jose; Laura Saladino, Maria; Barnett, Michael; Hillert, Jan; Butzkueven, Helmut

    2017-09-01

    Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of

  5. Tool for Ranking Research Options

    Science.gov (United States)

    Ortiz, James N.; Scott, Kelly; Smith, Harold

    2005-01-01

    Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

  6. Issue Management Risk Ranking Systems

    Energy Technology Data Exchange (ETDEWEB)

    Novack, Steven David; Marshall, Frances Mc Clellan; Stromberg, Howard Merion; Grant, Gary Michael

    1999-06-01

    Thousands of safety issues have been collected on-line at the Idaho National Engineering and Environmental Laboratory (INEEL) as part of the Issue Management Plan. However, there has been no established approach to prioritize collected and future issues. The authors developed a methodology, based on hazards assessment, to identify and risk rank over 5000 safety issues collected at INEEL. This approach required that it was easily applied and understandable for site adaptation and commensurate with the Integrated Safety Plan. High-risk issues were investigated and mitigative/preventive measures were suggested and ranked based on a cost-benefit scheme to provide risk-informed safety measures. This methodology was consistent with other integrated safety management goals and tasks providing a site-wide risk informed decision tool to reduce hazardous conditions and focus resources on high-risk safety issues. As part of the issue management plan, this methodology was incorporated at the issue collection level and training was provided to management to better familiarize decision-makers with concepts of safety and risk. This prioritization methodology and issue dissemination procedure will be discussed. Results of issue prioritization and training efforts will be summarized. Difficulties and advantages of the process will be reported. Development and incorporation of this process into INEELs lessons learned reporting and the site-wide integrated safety management program will be shown with an emphasis on establishing self reliance and ownership of safety issues.

  7. An IL28B genotype-based clinical prediction model for treatment of chronic hepatitis C.

    Directory of Open Access Journals (Sweden)

    Thomas R O'Brien

    Full Text Available Genetic variation in IL28B and other factors are associated with sustained virological response (SVR after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC. Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables.HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC.Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p10% (43.3% of subjects had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study.A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC.

  8. Predictive factors for the methotrexate treatment outcome in ectopic pregnancy: A comparative study of 400 cases.

    Science.gov (United States)

    Bonin, Lucie; Pedreiro, Cécile; Moret, Stéphanie; Chene, Gautier; Gaucherand, Pascal; Lamblin, Géry

    2017-01-01

    We sought to evaluate the global success rate of intramuscular methotrexate for the treatment of ectopic pregnancy, identify factors predictive of treatment success or failure, and study methotrexate tolerability in a large patient cohort. For this single-center retrospective observational study, we retrieved the records of all women who had a clinically or echographically confirmed ectopic pregnancy with a Fernandez score ectopic pregnancy. The medical treatment protocol was effective for 314 patients, i.e., an overall success rate of 78.5%. A single methotrexate dose was sufficient for 63.5% of the women and a second dose was successful for 73.2% of the remaining women. The medical treatment success rate fell as initial hCG levels climbed. The main factors associated with methotrexate failure included day (D) 0, D4 and D7 hCG levels, pretherapeutic blood progesterone, hematosalpinx at D0 and pain at D7. Early favorable kinetics of hCG levels was predictive of success. Methotrexate treatment was successful in 90% of women who had D0 hCG ectopic pregnancy was 80.7%. In this study, we showed that an initial hCG value ectopic pregnancy by methotrexate, and hematosalpinx and pretherapeutic blood progesterone >5ng/ml at diagnosis were predictive of its failure. We also confirmed good tolerability for single-dose methotrexate protocols. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Consumer Factors Predicting Level of Treatment Response to Illness Management and Recovery.

    Science.gov (United States)

    White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

    2017-09-14

    This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

    Energy Technology Data Exchange (ETDEWEB)

    Fagedet, Dorothee, E-mail: DFagedet@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de medecine interne, Pole Pluridisciplinaire de Medecine (France); Thony, Frederic, E-mail: FThony@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Timsit, Jean-Francois, E-mail: JFTimsit@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de reanimation, Pole Medecine Aiguee Communautaire (France); Rodiere, Mathieu, E-mail: MRodiere@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Monnin-Bares, Valerie, E-mail: v-monnin@chu-montpellier.fr [CHRU Arnaud de Villeneuve, Imagerie Medicale Thoracique Cardiovasculaire (France); Ferretti, Gilbert R., E-mail: GFerretti@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Vesin, Aurelien; Moro-Sibilot, Denis, E-mail: DMoro.pneumo@chu-grenoble.fr [University Grenoble 1 e Albert Bonniot Institute, Inserm U823 (France)

    2013-02-15

    To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable rate of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.

  11. Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

    Science.gov (United States)

    Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2015-01-01

    Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin β4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.

  12. Predicting objective function weights from patient anatomy in prostate IMRT treatment planning.

    Science.gov (United States)

    Lee, Taewoo; Hammad, Muhannad; Chan, Timothy C Y; Craig, Tim; Sharpe, Michael B

    2013-12-01

    Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. A regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, using l2 distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights

  13. Toward an online cognitive and emotional battery to predict treatment remission in depression

    Directory of Open Access Journals (Sweden)

    Gordon E

    2015-02-01

    Full Text Available Evian Gordon,1 A John Rush,2 Donna M Palmer,3,4 Taylor A Braund,3 William Rekshan1 1Brain Resource, San Francisco, CA, USA; 2Duke-NUS, Singapore; 3Brain Resource, Sydney, NSW, Australia; 4Brain Dynamics Center, Sydney Medical School – Westmead and Westmead Millennium Institute, The University of Sydney, Sydney, NSW, Australia Purpose: To evaluate the performance of a cognitive and emotional test battery in a representative sample of depressed outpatients to inform likelihood of remission over 8 weeks of treatment with each of three common antidepressant medications. Patients and methods: Outpatients 18–65 years old with nonpsychotic major depressive disorder (17 sites were randomized to escitalopram, sertraline or venlafaxine-XR (extended release. Participants scored ≥12 on the baseline 16-item Quick Inventory of Depressive Symptomatology – Self-Report and completed 8 weeks of treatment. The baseline test battery measured cognitive and emotional status. Exploratory multivariate logistic regression models predicting remission (16-item Quick Inventory of Depressive Symptomatology – Self-Report score ≤5 at 8 weeks were developed independently for each medication in subgroups stratified by age, sex, or cognitive and emotional test performance. The model with the highest cross-validated accuracy determined the participant proportion in each arm for whom remission could be predicted with an accuracy ≥10% above chance. The proportion for whom a prediction could be made with very high certainty (positive predictive value and negative predictive value exceeding 80% was calculated by incrementally increasing test battery thresholds to predict remission/non-remission. Results: The test battery, individually developed for each medication, improved identification of remitting and non-remitting participants by ≥10% beyond chance for 243 of 467 participants. The overall remission rates were escitalopram: 40.8%, sertraline: 30.3%, and

  14. Prognostic and Predictive Values and Statistical Interactions in the Era of Targeted Treatment.

    Science.gov (United States)

    Satagopan, Jaya M; Iasonos, Alexia; Zhou, Qin

    2015-11-01

    The current era of targeted treatment has accelerated the interest in studying gene-treatment, gene-gene, and gene-environment interactions using statistical models in the health sciences. Interactions are incorporated into models as product terms of risk factors. The statistical significance of interactions is traditionally examined using a likelihood ratio test (LRT). Epidemiological and clinical studies also evaluate interactions in order to understand the prognostic and predictive values of genetic factors. However, it is not clear how different types and magnitudes of interaction effects are related to prognostic and predictive values. The contribution of interaction to prognostic values can be examined via improvements in the area under the receiver operating characteristic curve due to the inclusion of interaction terms in the model (ΔAUC). We develop a resampling based approach to test the significance of this improvement and show that it is equivalent to LRT. Predictive values provide insights into whether carriers of genetic factors benefit from specific treatment or preventive interventions relative to noncarriers, under some definition of treatment benefit. However, there is no unique definition of the term treatment benefit. We show that ΔAUC and relative excess risk due to interaction (RERI) measure predictive values under two specific definitions of treatment benefit. We investigate the properties of LRT, ΔAUC, and RERI using simulations. We illustrate these approaches using published melanoma data to understand the benefits of possible intervention on sun exposure in relation to the MC1R gene. The goal is to evaluate possible interventions on sun exposure in relation to MC1R. © 2015 WILEY PERIODICALS, INC.

  15. Cross-trial prediction of treatment outcome in depression: a machine learning approach.

    Science.gov (United States)

    Chekroud, Adam Mourad; Zotti, Ryan Joseph; Shehzad, Zarrar; Gueorguieva, Ralitza; Johnson, Marcia K; Trivedi, Madhukar H; Cannon, Tyrone D; Krystal, John Harrison; Corlett, Philip Robert

    2016-03-01

    Antidepressant treatment efficacy is low, but might be improved by matching patients to interventions. At present, clinicians have no empirically validated mechanisms to assess whether a patient with depression will respond to a specific antidepressant. We aimed to develop an algorithm to assess whether patients will achieve symptomatic remission from a 12-week course of citalopram. We used patient-reported data from patients with depression (n=4041, with 1949 completers) from level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D; ClinicalTrials.gov, number NCT00021528) to identify variables that were most predictive of treatment outcome, and used these variables to train a machine-learning model to predict clinical remission. We externally validated the model in the escitalopram treatment group (n=151) of an independent clinical trial (Combining Medications to Enhance Depression Outcomes [COMED]; ClinicalTrials.gov, number NCT00590863). We identified 25 variables that were most predictive of treatment outcome from 164 patient-reportable variables, and used these to train the model. The model was internally cross-validated, and predicted outcomes in the STAR*D cohort with accuracy significantly above chance (64·6% [SD 3·2]; pbuproprion treatment group in COMED (n=134; accuracy 59·7%, p=0·023), but not in a combined venlafaxine-mirtazapine group (n=140; accuracy 51·4%, p=0·53), suggesting specificity of the model to underlying mechanisms. Building statistical models by mining existing clinical trial data can enable prospective identification of patients who are likely to respond to a specific antidepressant. Yale University. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Utilization of low rank coal and agricultural by-products

    Energy Technology Data Exchange (ETDEWEB)

    Ekinci, E.; Yardim, M.F.; Petrova, B.; Budinova, T.; Petrov, N. [Istanbul Technical University, Maslak-Istanbul (Turkey). Department of Chemical Engineering

    2007-07-01

    The present investigation deals with alternative utilization processes to convert low rank coal and agricultural by products into solid, liquid and gaseous products for a more efficient exploitation of these materials. Low rank coals and different agricultural by-products were subjected to different thermochemical treatments. The composition and physico-chemical properties of liquid products obtained from agricultural by-products were investigated. The identified compounds are predominantly oxygen derivatives of phenol, dihydroxybenzenes, guaiacol, syringol, vanilin, veratrol, furan and acids. Liquids from low rank coals contain higher quality of aromatic compounds predominantly mono- and bicyclic. The amount of oxygen containing structures is high as well. By thermo-chemical treatment of liquid products from agricultural by-products, low rank coals and their mixtures with H{sub 2}SO{sub 4} carbon adsorbents with very low ash and sulfur content are obtained. Using different activation reagents large scale carbon adsorbents are prepared from agricultural by-products and coals. The results of the investigations open-up possibilities for utilization of low rank coals and agricultural by-products. 18 refs., 5 figs., 7 tabs.

  17. Two-dimensional ranking of Wikipedia articles

    Science.gov (United States)

    Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

    2010-10-01

    The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

  18. Executive function predicts response to antiaggression treatment in schizophrenia: a randomized controlled trial.

    Science.gov (United States)

    Krakowski, Menahem I; Czobor, Pal

    2012-01-01

    Despite extensive experience with antipsychotic medications, we have limited capacity to predict which patients will benefit from which medications and for what symptoms. Such prediction is of particular importance for the proper treatment of violence. Our goal was to determine whether executive function predicts outcome of treatment for aggressive behavior and whether such prediction varies across medication groups. Ninety-nine physically aggressive inpatients (aged 18-60 years) with schizophrenia or schizoaffective disorder (diagnosed according to DSM-IV) who completed tests of executive function were randomly assigned in a double-blind, parallel-group, 12-week trial to clozapine (n = 32), olanzapine (n = 32), or haloperidol (n = 35). The number and severity of aggressive events as measured by the Modified Overt Aggression Scale (MOAS) were the outcome measures. Psychopathology and medication side effects were also assessed. The study was conducted from 1999 to 2004. Poor executive function predicted higher levels of aggression, as measured by MOAS scores over the 12-week period, in all 3 medication groups (F(1,98) = 222.2, P aggression in patients with schizophrenia. clinicaltrials.gov Identifier: NCT01123408. © Copyright 2012 Physicians Postgraduate Press, Inc.

  19. Automatic avoidance tendencies for alcohol cues predict drinking after detoxification treatment in alcohol dependence.

    Science.gov (United States)

    Field, Matt; Di Lemma, Lisa; Christiansen, Paul; Dickson, Joanne

    2017-03-01

    Alcohol dependence is characterized by conflict between approach and avoidance motivational orientations for alcohol that operate in automatic and controlled processes. This article describes the first study to investigate the predictive validity of these motivational orientations for relapse to drinking after discharge from alcohol detoxification treatment in alcohol-dependent patients. One hundred twenty alcohol-dependent patients who were nearing the end of inpatient detoxification treatment completed measures of self-reported (Approach and Avoidance of Alcohol Questionnaire; AAAQ) and automatic (modified Stimulus-Response Compatibility task) approach and avoidance motivational orientations for alcohol. Their drinking behavior was assessed via telephone follow-ups at 2, 4, and 6 months after discharge from treatment. Results indicated that, after controlling for the severity of alcohol dependence, strong automatic avoidance tendencies for alcohol cues were predictive of higher percentage of heavy drinking days (PHDD) at 4-month (β = 0.22, 95% CI [0.07, 0.43]) and 6-month (β = 0.22, 95% CI [0.01, 0.42]) follow-ups. We failed to replicate previous demonstrations of the predictive validity of approach subscales of the AAAQ for relapse to drinking, and there were no significant predictors of PHDD at 2-month follow-up. In conclusion, strong automatic avoidance tendencies predicted relapse to drinking after inpatient detoxification treatment, but automatic approach tendencies and self-reported approach and avoidance tendencies were not predictive in this study. Our results extend previous findings and help to resolve ambiguities with earlier studies that investigated the roles of automatic and controlled cognitive processes in recovery from alcohol dependence. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. Predicting tDCS treatment outcomes of patients with major depressive disorder using automated EEG classification.

    Science.gov (United States)

    Al-Kaysi, Alaa M; Al-Ani, Ahmed; Loo, Colleen K; Powell, Tamara Y; Martin, Donel M; Breakspear, Michael; Boonstra, Tjeerd W

    2017-01-15

    Transcranial direct current stimulation (tDCS) is a promising treatment for major depressive disorder (MDD). Standard tDCS treatment involves numerous sessions running over a few weeks. However, not all participants respond to this type of treatment. This study aims to investigate the feasibility of identifying MDD patients that respond to tDCS treatment based on resting-state electroencephalography (EEG) recorded prior to treatment commencing. We used machine learning to predict improvement in mood and cognition during tDCS treatment from baseline EEG power spectra. Ten participants with a current diagnosis of MDD were included. Power spectral density was assessed in five frequency bands: delta (0.5-4Hz), theta (4-8Hz), alpha (8-12Hz), beta (13-30Hz) and gamma (30-100Hz). Improvements in mood and cognition were assessed using the Montgomery-Åsberg Depression Rating Scale and Symbol Digit Modalities Test, respectively. We trained the classifiers using three algorithms (support vector machine, extreme learning machine and linear discriminant analysis) and a leave-one-out cross-validation approach. Mood labels were accurately predicted in 8 out of 10 participants using EEG channels FC4-AF8 (accuracy=76%, p=0.034). Cognition labels were accurately predicted in 10 out of 10 participants using channels pair CPz-CP2 (accuracy=92%, p=0.004). Due to the limited number of participants (n=10), the presented results mainly aim to serve as a proof of concept. These finding demonstrate the feasibility of using machine learning to identify patients that will respond to tDCS treatment. These promising results warrant a larger study to determine the clinical utility of this approach. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study

    Science.gov (United States)

    Chan, H. M.; van der Velden, B. H. M.; E Loo, C.; Gilhuijs, K. G. A.

    2017-08-01

    We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data. The model for prediction of survival after treatment (median follow-up time 86 months) was based on logistic regression. Receiver operating characteristic (ROC) analysis was applied and area-under-the-curve (AUC) values were computed as measures of training and cross-validated performances. The discriminating potential of the model was confirmed using Kaplan-Meier survival curves and log-rank tests. From the 322 principal components that explained 90% of the variance of the data, the LASSO selected 28 components. The ROC curves of the model yielded AUC values of 0.88, 0.77 and 0.73, for the training, leave-one-out cross-validated and bootstrapped performances, respectively. The bootstrapped Kaplan-Meier survival curves confirmed significant separation for all tumors (P  breast cancer.

  2. Cognitive performance predicts treatment decisional abilities in mild to moderate dementia.

    Science.gov (United States)

    Gurrera, R J; Moye, J; Karel, M J; Azar, A R; Armesto, J C

    2006-05-09

    To examine the contribution of neuropsychological test performance to treatment decision-making capacity in community volunteers with mild to moderate dementia. The authors recruited volunteers (44 men, 44 women) with mild to moderate dementia from the community. Subjects completed a battery of 11 neuropsychological tests that assessed auditory and visual attention, logical memory, language, and executive function. To measure decision making capacity, the authors administered the Capacity to Consent to Treatment Interview, the Hopemont Capacity Assessment Interview, and the MacCarthur Competence Assessment Tool--Treatment. Each of these instruments individually scores four decisional abilities serving capacity: understanding, appreciation, reasoning, and expression of choice. The authors used principal components analysis to generate component scores for each ability across instruments, and to extract principal components for neuropsychological performance. Multiple linear regression analyses demonstrated that neuropsychological performance significantly predicted all four abilities. Specifically, it predicted 77.8% of the common variance for understanding, 39.4% for reasoning, 24.6% for appreciation, and 10.2% for expression of choice. Except for reasoning and appreciation, neuropsychological predictor (beta) profiles were unique for each ability. Neuropsychological performance substantially and differentially predicted capacity for treatment decisions in individuals with mild to moderate dementia. Relationships between elemental cognitive function and decisional capacity may differ in individuals whose decisional capacity is impaired by other disorders, such as mental illness.

  3. A genome-wide association study points to multiple loci predicting antidepressant treatment outcome in depression

    Science.gov (United States)

    Binder, Elisabeth B.; Bettecken, Thomas; Uhr, Manfred; Ripke, Stephan; Kohli, Martin A.; Hennings, Johannes M.; Horstmann, Sonja; Kloiber, Stefan; Menke, Andreas; Bondy, Brigitta; Rupprecht, Rainer; Domschke, Katharina; Baune, Bernhard T.; Arolt, Volker; Rush, A. John; Holsboer, Florian; Müller-Myhsok, Bertram

    2015-01-01

    Context Efficacy of antidepressant treatment in depression is unsatisfactory as one in three patients does not fully recover even after several treatment trials. Genetic factors and clinical characteristics contribute to the failure of a favorable treatment outcome. Objective To identify genetic and clinical determinants of antidepressant treatment outcome in depression. Design Genome-wide pharmacogenetic association study with two independent replication samples. Setting We performed a genome-wide association (GWA) study in patients from the Munich-Antidepressant-Response-Signature (MARS) project and in pooled DNA from an independent German replication sample. A set of 328 single nucleotide polymorphisms (SNPs) highly related to outcome in both GWA studies was genotyped in a sample of the Sequenced-Treatment-Alternatives-to-Relieve-Depression (STAR*D) study. Participants 339 inpatients suffering from a depressive episode (MARS sample), further 361 depressed inpatients (German replication sample), and 832 outpatients with major depression (STAR*D sample). Main Outcome Measures We generated a multi-locus genetic variable describing the individual number of alleles of the selected SNPs associated with beneficial treatment outcome in the MARS sample (“response” alleles) to evaluate additive genetic effects on antidepressant treatment outcome. Results Multi-locus analysis revealed a significant contribution of a binary variable categorizing patients as carriers of a high vs. low number of response alleles in predicting antidepressant treatment outcome in both samples, MARS and STAR*D. In addition, we observed that patients with a comorbid anxiety disorder in combination with a low number of response alleles showed the least favorable outcome. Conclusion Our results demonstrate the importance of multiple genetic factors in combination with clinical features to predict antidepressant treatment outcome underscoring the multifactorial nature of this trait. PMID

  4. On the Schwartz space isomorphism theorem for rank one ...

    Indian Academy of Sciences (India)

    Abstract. In this paper we give a simpler proof of the Lp-Schwartz space isomorphism. (0 < p ≤ 2) under the Fourier transform for the class of functions of left δ-type on a. Riemannian symmetric space of rank one. Our treatment rests on Anker's [2] proof of the corresponding result in the case of left K-invariant functions on X.

  5. On the Schwartz space isomorphism theorem for rank one ...

    Indian Academy of Sciences (India)

    In this paper we give a simpler proof of the L p -Schwartz space isomorphism (0 < ≤ 2) under the Fourier transform for the class of functions of left -type on a Riemannian symmetric space of rank one. Our treatment rests on Anker's [2] proof of the corresponding result in the case of left -invariant functions on . Thus we ...

  6. Does impulsivity predict outcome in treatment for binge eating disorder? A multimodal investigation.

    Science.gov (United States)

    Manasse, Stephanie M; Espel, Hallie M; Schumacher, Leah M; Kerrigan, Stephanie G; Zhang, Fengqing; Forman, Evan M; Juarascio, Adrienne S

    2016-10-01

    Multiple dimensions of impulsivity (e.g., affect-driven impulsivity, impulsive inhibition - both general and food-specific, and impulsive decision-making) are associated with binge eating pathology cross-sectionally, yet the literature on whether impulsivity predicts treatment outcome is limited. The present pilot study explored impulsivity-related predictors of 20-week outcome in a small open trial (n = 17) of a novel treatment for binge eating disorder. Overall, dimensions of impulsivity related to emotions (i.e., negative urgency) and food cues emerged as predictors of treatment outcomes (i.e., binge eating frequency and global eating pathology as measured by the Eating Disorders Examination), while more general measures of impulsivity were statistically unrelated to global eating pathology or binge frequency. Specifically, those with higher levels of negative urgency at baseline experienced slower and less pronounced benefit from treatment, and those with higher food-specific impulsivity had more severe global eating pathology at baseline that was consistent at post-treatment and follow-up. These preliminary findings suggest that patients high in negative urgency and with poor response inhibition to food cues may benefit from augmentation of existing treatments to achieve optimal outcomes. Future research will benefit from replication with a larger sample, parsing out the role of different dimensions of impulsivity in treatment outcome for eating disorders, and identifying how treatment can be improved to accommodate higher levels of baseline impulsivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Brain potentials predict substance abuse treatment completion in a prison sample.

    Science.gov (United States)

    Fink, Brandi C; Steele, Vaughn R; Maurer, Michael J; Fede, Samantha J; Calhoun, Vince D; Kiehl, Kent A

    2016-08-01

    National estimates suggest that up to 80% of prison inmates meet diagnostic criteria for a substance use disorder. Because more substance abuse treatment while incarcerated is associated with better post-release outcomes, including a reduced risk of accidental overdose death, the stakes are high in developing novel predictors of substance abuse treatment completion in inmate populations. Using electroencephalography (EEG), this study investigated stimulus-locked ERP components elicited by distractor stimuli in three tasks (VO-Distinct, VO-Repeated, Go/NoGo) as a predictor of treatment discontinuation in a sample of male and female prison inmates. We predicted that those who discontinued treatment early would exhibit a less positive P3a amplitude elicited by distractor stimuli. Our predictions regarding ERP components were partially supported. Those who discontinued treatment early exhibited a less positive P3a amplitude and a less positive PC4 in the VO-D task. In the VO-R task, however, those who discontinued treatment early exhibited a more negative N200 amplitude rather than the hypothesized less positive P3a amplitude. The discontinuation group also displayed less positive PC4 amplitude. Surprisingly, there were no time-domain or principle component differences among the groups in the Go/NoGo task. Support Vector Machine (SVM) models of the three tasks accurately classified individuals who discontinued treatment with the best model accurately classifying 75% of inmates. PCA techniques were more sensitive in differentiating groups than the classic time-domain windowed approach. Our pattern of findings are consistent with the context-updating theory of P300 and may help identify subtypes of ultrahigh-risk substance abusers who need specialized treatment programs.

  8. Predicting biopsychosocial outcomes for heroin users in primary care treatment: a prospective longitudinal cohort study.

    Science.gov (United States)

    Parmenter, Jamie; Mitchell, Caroline; Keen, Jenny; Oliver, Phillip; Rowse, Georgina; Neligan, Isabel; Keil, Christopher; Mathers, Nigel

    2013-07-01

    Opiate substitution treatment for heroin users reduces mortality, illicit drug use, crime, and risk-taking behaviour, and improves physical, mental and social functioning. Few extended studies have been carried out in UK primary care to study factors predicting recovery. To establish whether primary care opiate substitution treatment is associated with improvements in outcomes over 11 years, in delivering recovery, and to identify predictive factors. A prospective longitudinal cohort study, with repeated measures in the Primary Care Addiction Service, Sheffield, 1999-2011. A total of 123 eligible patients were assessed using the Opiate Treatment Index at entry to treatment and at 1, 5, and 11 years. Clinical records were used to assess factors including employment and discharge status. At 11 years, there was a high rate of drug-free discharge (22.0%) and medically-assisted recovery (30.9%), and low mortality (6.5%). Continuous treatment was associated with being discharged drug free (P = 0.005). For those still in treatment, there were highly significant reductions in heroin use and injecting, and significantly improved psychosocial functioning. There were strong positive correlations between mental health, physical health, and social functioning. Patients in employment had significantly better psychological and social functioning (P = 0.017, P = 0.007, respectively). Opiate substitution treatment is associated over 11 years with full recovery, drug-free discharge and medically-assisted recovery. There is a strong association between the psychosocial variables, suggesting that intervention in any one of these areas may have extended benefits, by impacting on related variables and employment. The best predictor of a drug-free discharge was continuous uninterrupted treatment.

  9. Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies.

    Science.gov (United States)

    Thase, Michael E

    2014-12-01

    Major depressive disorder (MDD) is a heterogeneous condition with a variable response to a wide range of treatments. Despite intensive efforts, no biomarker has been identified to date that can reliably predict response or non-response to any form of treatment, nor has one been identified that can be used to identify those at high risk of developing treatment-resistant depression (ie, non-response to a sequence of treatments delivered for adequate duration and intensity). This manuscript reviews some past areas of research that have proved informative, such as studies using indexes of hypercortisolism or sleep disturbance, and more recent research findings using measures of inflammation and different indicators of regional cortical activation to predict treatment response. It is concluded that, although no method has yet been demonstrated to be sufficiently accurate to be applied in clinical practice, progress has been made. It thus seems likely that--at some point in the not-too-distant future--it will be possible to prospectively identify, at least for some MDD patients, the likelihood of response or non-response to cognitive therapy or various antidepressant medications.

  10. Dissociation predicts treatment response in eye-movement desensitization and reprocessing for posttraumatic stress disorder.

    Science.gov (United States)

    Bae, Hwallip; Kim, Daeho; Park, Yong Chon

    2016-01-01

    Using clinical data from a specialized trauma clinic, this study investigated pretreatment clinical factors predicting response to eye-movement desensitization and reprocessing (EMDR) among adult patients diagnosed with posttraumatic stress disorder (PTSD). Participants were evaluated using the Clinician-Administered PTSD Scale (CAPS), the Symptom Checklist-90-Revised, the Beck Depression Inventory, and the Dissociative Experiences Scale before treatment and were reassessed using the CAPS after treatment and at 6-month follow-up. A total of 69 patients underwent an average of 4 sessions of EMDR, and 60 (87%) completed the posttreatment evaluation, including 8 participants who terminated treatment prematurely. Intent-to-treat analysis revealed that 39 (65%) of the 60 patients were classified as responders and 21 (35%) as nonresponders when response was defined as more than a 30% decrease in total CAPS score. The nonresponders had higher levels of dissociation (depersonalization and derealization) and numbing symptoms, but other PTSD symptoms, such as avoidance, hyperarousal, and intrusion, were not significantly different. The number of psychiatric comorbidities was also associated with treatment nonresponse. The final logistic regression model yielded 2 significant variables: dissociation (p < .001) and more than 2 comorbidities compared to none (p < .05). These results indicate that complex symptom patterns in PTSD may predict treatment response and support the inclusion of the dissociative subtype of PTSD in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

  11. An integrated prediction and optimization model of biogas production system at a wastewater treatment facility.

    Science.gov (United States)

    Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih

    2015-11-01

    This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Contextual effects on the perceived health benefits of exercise: the exercise rank hypothesis.

    Science.gov (United States)

    Maltby, John; Wood, Alex M; Vlaev, Ivo; Taylor, Michael J; Brown, Gordon D A

    2012-12-01

    Many accounts of social influences on exercise participation describe how people compare their behaviors to those of others. We develop and test a novel hypothesis, the exercise rank hypothesis, of how this comparison can occur. The exercise rank hypothesis, derived from evolutionary theory and the decision by sampling model of judgment, suggests that individuals' perceptions of the health benefits of exercise are influenced by how individuals believe the amount of exercise ranks in comparison with other people's amounts of exercise. Study 1 demonstrated that individuals' perceptions of the health benefits of their own current exercise amounts were as predicted by the exercise rank hypothesis. Study 2 demonstrated that the perceptions of the health benefits of an amount of exercise can be manipulated by experimentally changing the ranked position of the amount within a comparison context. The discussion focuses on how social norm-based interventions could benefit from using rank information.

  13. Predictive value of self-reported and observer-rated defense style in depression treatment.

    OpenAIRE

    Van, H.L.; Dekker, J.J.M.; Peen, J.; Abraham, R.E.; Schoevers, R.

    2009-01-01

    This study explored the predictive value of observer-rated and self-reported defensive functioning on the outcome of psychotherapy for the treatment of depression. Defense styles were measured according to the Developmental Profile (DP) and the Defense Style Questionnaire (DSQ) in 81 moderately severely depressed patients. All patients were treated with Short-term Psychodynamic Supportive Psychotherapy (SPSP). At baseline, women appeared to have a more mature level of overall defensive functi...

  14. Predicting post-treatment survivability of patients with breast cancer using Artificial Neural Network methods.

    Science.gov (United States)

    Wang, Tan-Nai; Cheng, Chung-Hao; Chiu, Hung-Wen

    2013-01-01

    In the last decade, the use of data mining techniques has become widely accepted in medical applications, especially in predicting cancer patients' survival. In this study, we attempted to train an Artificial Neural Network (ANN) to predict the patients' five-year survivability. Breast cancer patients who were diagnosed and received standard treatment in one hospital during 2000 to 2003 in Taiwan were collected for train and test the ANN. There were 604 patients in this dataset excluding died not in breast cancer. Among them 140 patients died within five years after their first radiotherapy treatment. The artificial neural networks were created by STATISTICA(®) software. Five variables (age, surgery and radiotherapy type, tumor size, regional lymph nodes, distant metastasis) were selected as the input features for ANN to predict the five-year survivability of breast cancer patients. We trained 100 artificial neural networks and chose the best one to analyze. The accuracy rate is 85% and area under the receiver operating characteristic (ROC) curve is 0.79. It shows that artificial neural network is a good tool to predict the five-year survivability of breast cancer patients.

  15. Temperamental factors predict long-term modifications of eating disorders after treatment.

    Science.gov (United States)

    Segura-García, Cristina; Chiodo, Dora; Sinopoli, Flora; De Fazio, Pasquale

    2013-11-07

    Eating Disorders (EDs) are complex psychiatric pathologies characterized by moderate to poor response to treatment. Criteria of remission and recovery are not yet well defined. Simultaneously, personality plays a key role among the factors that determine treatment outcome. The aim of the present research is to evaluate the possibility of temperamental and character traits to predict the long-term outcome of ED. A sample of 25 AN and 28 BN female patients were re-assessed face-to-face after a minimum 5-years-follow-up through SCID-I, EDI-2 and TCI-R. Regression Analyses were performed to ascertain the possibility of TCI-R dimensions at the first visit to predict the long-term outcome. Clinical and psychopathological symptoms significantly decreased over the time and 23% of participants no longer received a categorical ED diagnosis after at least 5 years of follow-up. TCI-R dimensions failed to predict the absence of a DSM-IV-TR diagnosis in the long term, but Novelty Seeking, Harm Avoidance and Reward Dependence demonstrated to predict the clinical improvement of several EDI-2 scales. Our results support the idea that temperamental dimensions are relevant to the long-term improvement of clinical variables of ED. Low Novelty Seeking is the strongest predictor of poor outcome.

  16. Rank Modulation for Translocation Error Correction

    CERN Document Server

    Farnoud, Farzad; Milenkovic, Olgica

    2012-01-01

    We consider rank modulation codes for flash memories that allow for handling arbitrary charge drop errors. Unlike classical rank modulation codes used for correcting errors that manifest themselves as swaps of two adjacently ranked elements, the proposed \\emph{translocation rank codes} account for more general forms of errors that arise in storage systems. Translocations represent a natural extension of the notion of adjacent transpositions and as such may be analyzed using related concepts in combinatorics and rank modulation coding. Our results include tight bounds on the capacity of translocation rank codes, construction techniques for asymptotically good codes, as well as simple decoding methods for one class of structured codes. As part of our exposition, we also highlight the close connections between the new code family and permutations with short common subsequences, deletion and insertion error-correcting codes for permutations and permutation arrays.

  17. Error analysis of stochastic gradient descent ranking.

    Science.gov (United States)

    Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

    2013-06-01

    Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

  18. Ranking in Swiss system chess team tournaments

    OpenAIRE

    Csató, László

    2015-01-01

    The paper uses paired comparison-based scoring procedures for ranking the participants of a Swiss system chess team tournament. We present the main challenges of ranking in Swiss system, the features of individual and team competitions as well as the failures of official lexicographical orders. The tournament is represented as a ranking problem, our model is discussed with respect to the properties of the score, generalized row sum and least squares methods. The proposed procedure is illustra...

  19. A universal rank-size law

    CERN Document Server

    Ausloos, Marcel

    2016-01-01

    A mere hyperbolic law, like the Zipf's law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the "best (or optimal) distribution", is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations.

  20. Predicting success of methotrexate treatment by pretreatment HCG level and 24-hour HCG increment.

    Science.gov (United States)

    Levin, Gabriel; Saleh, Narjes A; Haj-Yahya, Rani; Matan, Liat S; Avi, Benshushan

    2017-11-20

    To evaluate β-human chorionic gonadotropin (β-HCG) level and its 24-hour increment as predictors of successful methotrexate treatment for ectopic pregnancy. Data were retrospectively reviewed from women with ectopic pregnancy who were treated by single-dose methotrexate (50 mg/m 2 ) at a university hospital in Jerusalem, Israel, between January 1, 2000, and June 30, 2015. Serum β-HCG before treatment and its percentage increment in the 24 hours before treatment were compared between treatment success and failure groups. Sixty-nine women were included in the study. Single-dose methotrexate treatment was successful for 44 (63.8%) women. Both mean β-HCG level and its 24-hour increment were lower for women with successful treatment than for those with failed treatment (respectively, 1224 IU\\L vs 2362 IU\\L, P=0.018; and 13.5% vs 29.6%, P=0.009). Receiver operator characteristic curve analysis yielded cutoff values of 1600 IU\\L and 14% increment with a positive predictive value of 75% and 82%, respectively, for treatment success. β-HCG level and its 24-hour increment were independent predictors of treatment outcome by logistic regression (both PHCG increment of less than 14% in the 24 hours before single-dose methotrexate and serum β-HCG of less than 1600 IU\\L were found to be good predictors of treatment success. © 2017 International Federation of Gynecology and Obstetrics.

  1. Methodology for ranking restoration options

    Energy Technology Data Exchange (ETDEWEB)

    Hedemann Jensen, Per

    1999-04-01

    The work described in this report has been performed as a part of the RESTRAT Project FI4P-CT95-0021a (PL 950128) co-funded by the Nuclear Fission Safety Programme of the European Commission. The RESTRAT project has the overall objective of developing generic methodologies for ranking restoration techniques as a function of contamination and site characteristics. The project includes analyses of existing remediation methodologies and contaminated sites, and is structured in the following steps: characterisation of relevant contaminated sites; identification and characterisation of relevant restoration techniques; assessment of the radiological impact; development and application of a selection methodology for restoration options; formulation of generic conclusions and development of a manual. The project is intended to apply to situations in which sites with nuclear installations have been contaminated with radioactive materials as a result of the operation of these installations. The areas considered for remedial measures include contaminated land areas, rivers and sediments in rivers, lakes, and sea areas. Five contaminated European sites have been studied. Various remedial measures have been envisaged with respect to the optimisation of the protection of the populations being exposed to the radionuclides at the sites. Cost-benefit analysis and multi-attribute utility analysis have been applied for optimisation. Health, economic and social attributes have been included and weighting factors for the different attributes have been determined by the use of scaling constants. (au)

  2. Ranking documents with a thesaurus.

    Science.gov (United States)

    Rada, R; Bicknell, E

    1989-09-01

    This article reports on exploratory experiments in evaluating and improving a thesaurus through studying its effect on retrieval. A formula called DISTANCE was developed to measure the conceptual distance between queries and documents encoded as sets of thesaurus terms. DISTANCE references MeSH (Medical Subject Headings) and assesses the degree of match between a MeSH-encoded query and document. The performance of DISTANCE on MeSH is compared to the performance of people in the assessment of conceptual distance between queries and documents, and is found to simulate with surprising accuracy the human performance. The power of the computer simulation stems both from the tendency of people to rely heavily on broader-than (BT) relations in making decisions about conceptual distance and from the thousands of accurate BT relations in MeSH. One source for discrepancy between the algorithms' measurement of closeness between query and document and people's measurement of closeness between query and document is occasional inconsistency in the BT relations. Our experiments with adding non-BT relations to MeSH showed how these non-BT non-BT relations to MeSH showed how these non-BT relations could improve document ranking, if DISTANCE were also appropriately revised to treat these relations differently from BT relations.

  3. Do symptom-specific stages of change predict eating disorder treatment outcome?

    Science.gov (United States)

    Ackard, Diann M; Cronemeyer, Catherine L; Richter, Sara; Egan, Amber

    2015-03-01

    Interview methods to assess stages of change (SOC) in eating disorders (ED) indicate that SOC are positively correlated with symptom improvement over time. However, interviews require significant time and staff training and global measures of SOC do not capture varying levels of motivation across ED symptoms. This study used a self-report, ED symptom-specific SOC measure to determine prevalence of stages across symptoms and identify if SOC predict treatment outcome. Participants [N = 182; age 13-58 years; 92% Caucasian; 96% female; average BMI 21.7 (SD = 5.9); 50% ED not otherwise specified (EDNOS), 30.8% bulimia nervosa (BN), 19.2% anorexia nervosa (AN)] seeking ED treatment at a diverse-milieu multi-disciplinary facility in the United States completed stages of change, behavioral (ED symptom use and frequency) and psychological (ED concerns, anxiety, depression) measures at intake assessment and at 3, 6 and 12 months thereafter. Descriptive summaries were generated using ANOVA or Kruskal-Wallis (continuous) and χ (2) (categorical) tests. Repeated measures linear regression models with autoregressive correlation structure predicted treatment outcome. At intake assessment, 53.3% of AN, 34.0% of BN and 18.1% of EDNOS patients were in Preparation/Action. Readiness to change specific symptoms was highest for binge-eating (57.8%) and vomiting (56.5%). Frequency of fasting and restricting behaviors, and scores on all eating disorder and psychological measures improved over time regardless of SOC at intake assessment. Symptom-specific SOC did not predict reductions in ED symptom frequency. Overall SOC predicted neither improvement in Eating Disorder Examination Questionnaire (EDE-Q) scores nor reduction in depression or trait anxiety; however, higher overall SOC predicted lower state anxiety across follow-up. Readiness to change ED behaviors varies considerably. Most patients reduced eating disorder behaviors and increased psychological functioning regardless of stages

  4. Communities in Large Networks: Identification and Ranking

    DEFF Research Database (Denmark)

    Olsen, Martin

    2008-01-01

    We study the problem of identifying and ranking the members of a community in a very large network with link analysis only, given a set of representatives of the community. We define the concept of a community justified by a formal analysis of a simple model of the evolution of a directed graph. ...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

  5. Citation graph based ranking in Invenio

    CERN Document Server

    Marian, Ludmila; Rajman, Martin; Vesely, Martin

    2010-01-01

    Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

  6. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha

    2014-12-08

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  7. Early perfusion changes within 1 week of systemic treatment measured by dynamic contrast-enhanced MRI may predict survival in patients with advanced hepatocellular carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Bang-Bin; Yu, Chih-Wei; Liang, Po-Chin [National Taiwan University College of Medicine and Hospital, Department of Medical Imaging and Radiology, Taipei City (China); Hsu, Chao-Yu [National Taiwan University College of Medicine and Hospital, Department of Medical Imaging and Radiology, Taipei City (China); Taipei Hospital, Ministry of Health and Welfare, Department of Radiology, New Taipei City (China); Hsu, Chiun; Hsu, Chih-Hung; Cheng, Ann-Lii [National Taiwan University College of Medicine and Hospital, Department of Oncology, Taipei City (China); Shih, Tiffany Ting-Fang [National Taiwan University College of Medicine and Hospital, Department of Medical Imaging and Radiology, Taipei City (China); Taipei City Hospital, Department of Medical Imaging, Taipei City (China); National Taiwan University Hospital, Department of Medical Imaging, Taipei (China)

    2017-07-15

    To correlate early changes in the parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) within 1 week of systemic therapy with overall survival (OS) in patients with advanced hepatocellular carcinoma (HCC). Eighty-nine patients with advanced HCC underwent DCE-MRI before and within 1 week following systemic therapy. The relative changes of six DCE-MRI parameters (Peak, Slope, AUC, Ktrans, Kep and Ve) of the tumours were correlated with OS using the Kaplan-Meier model and the double-sided log-rank test. All patients died and the median survival was 174 days. Among the six DCE-MRI parameters, reductions in Peak, AUC, and Ktrans, were significantly correlated with one another. In addition, patients with a high Peak reduction following treatment had longer OS (P = 0.023) compared with those with a low Peak reduction. In multivariate analysis, a high Peak reduction was an independent favourable prognostic factor in all patients [hazard ratio (HR), 0.622; P = 0.038] after controlling for age, sex, treatment methods, tumour size and stage, and Eastern Cooperative Oncology Group performance status. Early perfusion changes within 1 week following systemic therapy measured by DCE-MRI may aid in the prediction of the clinical outcome in patients with advanced HCC. (orig.)

  8. Predictive factors for compliance with transanal irrigation for the treatment of defecation disorders.

    Science.gov (United States)

    Bildstein, Clémence; Melchior, Chloé; Gourcerol, Guillaume; Boueyre, Estelle; Bridoux, Valérie; Vérin, Eric; Leroi, Anne-Marie

    2017-03-21

    To investigate compliance with transanal irrigation (TAI) one year after a training session and to identify predictive factors for compliance. The compliance of one hundred eight patients [87 women and 21 men; median age 55 years (range 18-83)] suffering from constipation or fecal incontinence (FI) was retrospectively assessed. The patients were trained in TAI over a four-year period at a single institution. They were classified as adopters if they continued using TAI for at least one year after beginning the treatment or as non-adopters if they stopped. Predictive factors of compliance with TAI were based on pretreatment assessments and training progress. The outcomes of the entire cohort of patients who had been recruited for the TAI treatment were expressed in terms of intention-to-treat. Forty-six of the 108 (43%) trained patients continued to use TAI one year after their training session. The patients with FI had the best results, with 54.5% remaining compliant with TAI. Only one-third of the patients who complained of slow transit constipation or obstructed defecation syndrome continued TAI. There was an overall discontinuation rate of 57%. The most common reason for discontinuing TAI was the lack of efficacy (41%). However, 36% of the patients who discontinued TAI gave reasons independent of the efficacy of the treatment such as technical problems (catheter expulsion, rectal balloon bursting, instilled water leakage or retention, pain during irrigation, anal bleeding, anal fissure) while 23% said that there were too many constraints. Of the patients who reported discontinuing TAI, the only predictive factor was the progress of the training (OR = 4.9, 1.3-18.9, P = 0.02). The progress of the training session was the only factor that predicted patient compliance with TAI.

  9. Persistent enhancement after treatment for cerebral toxoplasmosis in patients with AIDS: predictive value for subsequent recurrence.

    Science.gov (United States)

    Laissy, J P; Soyer, P; Parlier, C; Lariven, S; Benmelha, Z; Servois, V; Casalino, E; Bouvet, E; Sibert, A; Vachon, F

    1994-10-01

    To determine the predictive imaging (CT and/or MR) features of brain toxoplasmosis recurrences in acquired immunodeficiency syndrome. The imaging studies of patients with brain toxoplasmosis were retrospectively reviewed. Forty-three patients with significant decrease or disappearance of brain lesions under specific treatment on follow-up imaging examinations were included. MR examinations were performed using T2- and T1-weighted sequences, before and after intravenous administration of gadolinium-DOTA. A recurrence occurred in 11 (26%) of 43 cases. Ten (91%) of these 11 patients with recurrence showed focal persistent enhancement after the initial treatment of toxoplasmosis abscess. One of the 11 patients with recurrence showed no persistent enhancement; 3 patients showed persistent enhancement but had no recurrence. Recurrences of brain toxoplasmosis in our series correlated with persistent contrast enhancement. We hypothesize that demonstration of persistent areas of contrast enhancement after treatment for initial toxoplasmosis may be a valuable sign for identifying patients at risk for recurrence.

  10. Variations in toxicity of semi-coking wastewater treatment processes and their toxicity prediction.

    Science.gov (United States)

    Ma, Xiaoyan; Wang, Xiaochang; Liu, Yongjun; Gao, Jian; Wang, Yongkun

    2017-04-01

    Chemical analyses and bioassays using Vibrio fischeri and Daphnia magna were conducted to evaluate comprehensively the variation of biotoxicity caused by contaminants in wastewater from a semi-coking wastewater treatment plant (WWTP). Pretreatment units (including an oil-water separator, a phenols extraction tower, an ammonia stripping tower, and a regulation tank) followed by treatment units (including anaerobic-oxic treatment units, coagulation-sedimentation treatment units, and an active carbon adsorption column) were employed in the semi-coking WWTP. Five benzenes, 11 phenols, and five polycyclic aromatic hydrocarbons (PAHs) were investigated as the dominant contaminants in semi-coking wastewater. Because of residual extractant, the phenols extraction process increased acute toxicity to V. fischeri and immobilization and lethal toxicity to D. magna. The acute toxicity of pretreated wastewater to V. fischeri was still higher than that of raw semi-coking wastewater, even though 90.0% of benzenes, 94.8% of phenols, and 81.0% of PAHs were removed. After wastewater pretreatment, phenols and PAHs were mainly removed by anaerobic-oxic and coagulation-sedimentation treatment processes respectively, and a subsequent active carbon adsorption process further reduced the concentrations of all target chemicals to below detection limits. An effective biotoxicity reduction was found during the coagulation-sedimentation and active carbon adsorption treatment processes. The concentration addition model can be applied for toxicity prediction of wastewater from the semi-coking WWTP. The deviation between the measured and predicted toxicity results may result from the effects of compounds not detectable by instrumental analyses, the synergistic effect of detected contaminants, or possible transformation products. Copyright © 2016. Published by Elsevier Inc.

  11. Empirically derived personality subtyping for predicting clinical symptoms and treatment response in bulimia nervosa.

    Science.gov (United States)

    Haynos, Ann F; Pearson, Carolyn M; Utzinger, Linsey M; Wonderlich, Stephen A; Crosby, Ross D; Mitchell, James E; Crow, Scott J; Peterson, Carol B

    2017-05-01

    Evidence suggests that eating disorder subtypes reflecting under-controlled, over-controlled, and low psychopathology personality traits constitute reliable phenotypes that differentiate treatment response. This study is the first to use statistical analyses to identify these subtypes within treatment-seeking individuals with bulimia nervosa (BN) and to use these statistically derived clusters to predict clinical outcomes. Using variables from the Dimensional Assessment of Personality Pathology-Basic Questionnaire, K-means cluster analyses identified under-controlled, over-controlled, and low psychopathology subtypes within BN patients (n = 80) enrolled in a treatment trial. Generalized linear models examined the impact of personality subtypes on Eating Disorder Examination global score, binge eating frequency, and purging frequency cross-sectionally at baseline and longitudinally at end of treatment (EOT) and follow-up. In the longitudinal models, secondary analyses were conducted to examine personality subtype as a potential moderator of response to Cognitive Behavioral Therapy-Enhanced (CBT-E) or Integrative Cognitive-Affective Therapy for BN (ICAT-BN). There were no baseline clinical differences between groups. In the longitudinal models, personality subtype predicted binge eating (p = 0.03) and purging (p = 0.01) frequency at EOT and binge eating frequency at follow-up (p = 0.045). The over-controlled group demonstrated the best outcomes on these variables. In secondary analyses, there was a treatment by subtype interaction for purging at follow-up (p = 0.04), which indicated a superiority of CBT-E over ICAT-BN for reducing purging among the over-controlled group. Empirically derived personality subtyping appears to be a valid classification system with potential to guide eating disorder treatment decisions. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2017; 50:506-514). © 2016 Wiley Periodicals, Inc.

  12. Within treatment therapeutic alliance ratings profiles predict posttreatment frequency of alcohol use.

    Science.gov (United States)

    Prince, Mark A; Connors, Gerard J; Maisto, Stephen A; Dearing, Ronda L

    2016-03-01

    Although past research has demonstrated a positive relationship between the therapeutic alliance (TA) and improved drinking outcomes, specific aspects of the alliance have received less attention. In this study, we examined the association between alliance characteristics during treatment and 4-month follow-up drinking reports. Sixty-five treatment-seeking alcohol dependent clients who participated in 12 weeks of individual outpatient treatment provided weekly TA ratings during treatment and reported on pretreatment, during treatment, and posttreatment alcohol use. Latent profile analysis was conducted to discern distinct profiles of client and therapist ratings of therapeutic alliance with similar alliance characteristics. TA profiles were based on clients' and therapists' mean alliance rating, minimum alliance rating, maximum alliance rating, the range of alliance ratings, and the difference in session number between maximum and minimum alliance ratings. One- through 4-class models were fit to the data. Model fit was judged by comparative fit indices, substantive interpretability, and parsimony. Wald tests of mean equality determined whether classes differed on follow-up percentage of days abstinent (PDA) at 4-months posttreatment. Three-profile solutions provided the best fit for both client and therapist ratings of the therapeutic alliance. Client alliance rating profiles predicted drinking in the follow-up period, but therapist rating profiles did not. These results suggest that distinct profiles of the therapeutic alliance can be identified and that client alliance rating profiles are associated with frequency of alcohol use following outpatient treatment. (c) 2016 APA, all rights reserved).

  13. Serum biomarkers predictive of cure in Chagas disease patients after nifurtimox treatment.

    Science.gov (United States)

    Santamaria, Cynthia; Chatelain, Eric; Jackson, Yves; Miao, Qianqian; Ward, Brian J; Chappuis, François; Ndao, Momar

    2014-06-03

    Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, remains an important public health issue in many Central and South American countries, as well as non-endemic areas with high rates of immigration from these countries. Existing treatment options for CD are limited and often unsatisfactory. Moreover the lack of post-treatment tests of cure limits the development of new drugs. To address this issue, we sought to identify serum biomarkers following nifurtimox (Nfx) treatment that could be used as an early test of cure and/or markers of a therapeutic response. Human sera from Chagas patients pre- and post-treatment with Nfx (n = 37) were compared to samples from healthy subjects (n = 37) using a range of proteomic and immunologic techniques. Biomarker peaks with the best discriminatory power were further characterized. Using serum samples (n = 111), we validated the presence of five key biomarkers identified in our previous study, namely human apolipoprotein A-I (APOA1) and specific fragments thereof and one fragment of human fibronectin (FN1). In chagasic serum samples all biomarkers except full-length APOA1 were upregulated. These five biomarkers returned to normal in 43% (16/37) of the patients treated with Nfx at three years after treatment. The normalization of biomarker patterns strongly associated with CD suggests that these markers can be used to identify patients in whom Nfx treatment is successful. We believe that these are the first biomarkers predictive of cure in CD patients.

  14. Do personality traits predict outcome of psychodynamically oriented psychosomatic inpatient treatment beyond initial symptoms?

    Science.gov (United States)

    Steinert, Christiane; Klein, Susanne; Leweke, Frank; Leichsenring, Falk

    2015-03-01

    Whether personality characteristics have an impact on treatment outcome is an important question in psychotherapy research. One of the most common approaches for the description of personality is the five-factor model of personality. Only few studies investigated whether patient personality as measured with the NEO-Five-Factor Inventory (NEO-FFI, Costa & McCrae [1992b]. Revised NEO-PI-R and NEO-FFI. Professional manual. Odessa, FL: Psychological Assessment Recources) predicts outcome. Results were inconsistent. Studies reporting personality to be predictive of outcome did not control for baseline symptoms, while studies controlling initial symptoms could not support these findings. We hypothesized that after taking into account baseline symptoms, the NEO-FFI would not predict outcome and tested this in a large sample of inpatients at a psychosomatic clinic. Naturalistic, non-controlled study using patients' data for multiple regression analysis to identify predictors of outcome. Data of 254 inpatients suffering primarily from depressive, anxiety, stress, and somatoform disorders were analysed. Personality was assessed at the beginning of therapy. For psychotherapy outcome, changes in anxiety and depression (Hospital Anxiety and Depression Scale; HADS), overall psychopathology (Symptom Checklist-90-R Global Severity Index [GSI]), and interpersonal problems (Inventory of Interpersonal Problems; IIP) were measured. The treatment resulted in significant decreases on all outcome measures corresponding to moderate to large effect sizes (HADS: d = 1.03; GSI: d = 0.90; IIP: d = 0.38). Consistent with our hypothesis, none of the personality domains predicted outcome when baseline symptoms were controlled for. Personality assessment at baseline does not seem to have an added value in the prediction of inpatient psychotherapy outcome beyond initial symptoms. Clinical implications Personality dimensions overlap with symptomatic distress. Rather than serve as predictors of

  15. Predictive vs. empiric assessment of schistosomiasis: implications for treatment projections in Ghana.

    Directory of Open Access Journals (Sweden)

    Achille Kabore

    Full Text Available BACKGROUND: Mapping the distribution of schistosomiasis is essential to determine where control programs should operate, but because it is impractical to assess infection prevalence in every potentially endemic community, model-based geostatistics (MBG is increasingly being used to predict prevalence and determine intervention strategies. METHODOLOGY/PRINCIPAL FINDINGS: To assess the accuracy of MBG predictions for Schistosoma haematobium infection in Ghana, school surveys were evaluated at 79 sites to yield empiric prevalence values that could be compared with values derived from recently published MBG predictions. Based on these findings schools were categorized according to WHO guidelines so that practical implications of any differences could be determined. Using the mean predicted values alone, 21 of the 25 empirically determined 'high-risk' schools requiring yearly praziquantel would have been undertreated and almost 20% of the remaining schools would have been treated despite empirically-determined absence of infection - translating into 28% of the children in the 79 schools being undertreated and 12% receiving treatment in the absence of any demonstrated need. CONCLUSIONS/SIGNIFICANCE: Using the current predictive map for Ghana as a spatial decision support tool by aggregating prevalence estimates to the district level was clearly not adequate for guiding the national program, but the alternative of assessing each school in potentially endemic areas of Ghana or elsewhere is not at all feasible; modelling must be a tool complementary to empiric assessments. Thus for practical usefulness, predictive risk mapping should not be thought of as a one-time exercise but must, as in the current study, be an iterative process that incorporates empiric testing and model refining to create updated versions that meet the needs of disease control operational managers.

  16. Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation

    Science.gov (United States)

    Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli

    2017-11-01

    The heteroscedasticity treatment in residual error models directly impacts the model calibration and prediction uncertainty estimation. This study compares three methods to deal with the heteroscedasticity, including the explicit linear modeling (LM) method and nonlinear modeling (NL) method using hyperbolic tangent function, as well as the implicit Box-Cox transformation (BC). Then a combined approach (CA) combining the advantages of both LM and BC methods has been proposed. In conjunction with the first order autoregressive model and the skew exponential power (SEP) distribution, four residual error models are generated, namely LM-SEP, NL-SEP, BC-SEP and CA-SEP, and their corresponding likelihood functions are applied to the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin, China. Results show that the LM-SEP yields the poorest streamflow predictions with the widest uncertainty band and unrealistic negative flows. The NL and BC methods can better deal with the heteroscedasticity and hence their corresponding predictive performances are improved, yet the negative flows cannot be avoided. The CA-SEP produces the most accurate predictions with the highest reliability and effectively avoids the negative flows, because the CA approach is capable of addressing the complicated heteroscedasticity over the study basin.

  17. Assessment of Predictive Response Factors to Intragastric Balloon Therapy for the Treatment of Obesity.

    Science.gov (United States)

    Madeira, Eduardo; Madeira, Miguel; Guedes, Erika Paniago; Mafort, Thiago Thomaz; Neto, Leonardo Vieira; de Oliveira Moreira, Rodrigo; de Pinho, Paulo Roberto Alves; Lopes, Agnaldo José; Farias, Maria Lucia Fleiuss

    2016-03-01

    Obesity is a worldwide epidemic that is difficult to control with non-invasive treatments, which usually present poor results. In this context, the intragastric balloon (IGB) is an important tool that presents a mean body weight loss (BWL) estimated at approximately 12%, although individual responses are highly variable. This study assesses whether there are factors that can predict responses to IGB therapy either before or early after placement of the device. A total of 50 obese patients underwent insertion of IGB placed endoscopically, and patients were monitored for 6 months. The evaluated predictive factors involved general characteristics and psychological, social, and dyspeptic aspects, and the preliminary results obtained in the first month after balloon placement. The mean weight loss was 11.5%, and 48% of the participants presented BWL >10%. Among the factors analyzed before IGB placement, only advanced age (P = .04) and higher scores obtained in the social relationships domain of a shorter version of the World Health Organization's Quality of Life questionnaire (P = .02) were significant. Analysis of the factors evaluated after IGB placement revealed that the BWL amounts observed in week 2 (P = .001) and week 4 (P < .001) and the intensity of dyspeptic symptoms in week 2 (P < .001) were positive predictive factors. The assessment of predictive factors may help to manage patients with IGB.

  18. Ranked Conservation Opportunity Areas for Region 7 (ECO_RES.RANKED_OAS)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The RANKED_OAS are all the Conservation Opportunity Areas identified by MoRAP that have subsequently been ranked by patch size, landform representation, and the...

  19. Ranking scientific publications: the effect of nonlinearity.

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru

    2014-10-17

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  20. Ranking scientific publications: the effect of nonlinearity

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

    2014-10-01

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  1. Entity Ranking using Wikipedia as a Pivot

    NARCIS (Netherlands)

    R. Kaptein; P. Serdyukov; A.P. de Vries (Arjen); J. Kamps

    2010-01-01

    htmlabstractIn this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about

  2. Entity ranking using Wikipedia as a pivot

    NARCIS (Netherlands)

    Kaptein, R.; Serdyukov, P.; de Vries, A.; Kamps, J.; Huang, X.J.; Jones, G.; Koudas, N.; Wu, X.; Collins-Thompson, K.

    2010-01-01

    In this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about these entities. Since

  3. Biplots in Reduced-Rank Regression

    NARCIS (Netherlands)

    Braak, ter C.J.F.; Looman, C.W.N.

    1994-01-01

    Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced-rank regression. Reduced-rank regression combines multiple regression and principal

  4. Mining Feedback in Ranking and Recommendation Systems

    Science.gov (United States)

    Zhuang, Ziming

    2009-01-01

    The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

  5. Using centrality to rank web snippets

    NARCIS (Netherlands)

    Jijkoun, V.; de Rijke, M.; Peters, C.; Jijkoun, V.; Mandl, T.; Müller, H.; Oard, D.W.; Peñas, A.; Petras, V.; Santos, D.

    2008-01-01

    We describe our participation in the WebCLEF 2007 task, targeted at snippet retrieval from web data. Our system ranks snippets based on a simple similarity-based centrality, inspired by the web page ranking algorithms. We experimented with retrieval units (sentences and paragraphs) and with the

  6. Generating and ranking of Dyck words

    CERN Document Server

    Kasa, Zoltan

    2010-01-01

    A new algorithm to generate all Dyck words is presented, which is used in ranking and unranking Dyck words. We emphasize the importance of using Dyck words in encoding objects related to Catalan numbers. As a consequence of formulas used in the ranking algorithm we can obtain a recursive formula for the nth Catalan number.

  7. Frontal and limbic activation during inhibitory control predicts treatment response in major depressive disorder.

    Science.gov (United States)

    Langenecker, Scott A; Kennedy, Susan E; Guidotti, Leslie M; Briceno, Emily M; Own, Lawrence S; Hooven, Thomas; Young, Elizabeth A; Akil, Huda; Noll, Douglas C; Zubieta, Jon-Kar

    2007-12-01

    Inhibitory control or regulatory difficulties have been explored in major depressive disorder (MDD) but typically in the context of affectively salient information. Inhibitory control is addressed specifically by using a task devoid of affectively-laden stimuli, to disentangle the effects of altered affect and altered inhibitory processes in MDD. Twenty MDD and 22 control volunteer participants matched by age and gender completed a contextual inhibitory control task, the Parametric Go/No-go (PGNG) task during functional magnetic resonance imaging. The PGNG includes three levels of difficulty, a typical continuous performance task and two progressively more difficult versions including Go/No-go hit and rejection trials. After this test, 15 of 20 MDD patients completed a full 10-week treatment with s-citalopram. There was a significant interaction among response time (control subjects better), hits (control subjects better), and rejections (patients better). The MDD participants had greater activation compared with the control group in frontal and anterior temporal areas during correct rejections (inhibition). Activation during successful inhibitory events in bilateral inferior frontal and left amygdala, insula, and nucleus accumbens and during unsuccessful inhibition (commission errors) in rostral anterior cingulate predicted post-treatment improvement in depression symptoms. The imaging findings suggest that in MDD subjects, greater neural activation in frontal, limbic, and temporal regions during correct rejection of lures is necessary to achieve behavioral performance equivalent to control subjects. Greater activation in similar regions was further predictive of better treatment response in MDD.

  8. Microwave thermal ablation: Effects of tissue properties variations on predictive models for treatment planning.

    Science.gov (United States)

    Lopresto, Vanni; Pinto, Rosanna; Farina, Laura; Cavagnaro, Marta

    2017-08-01

    Microwave thermal ablation (MTA) therapy for cancer treatments relies on the absorption of electromagnetic energy at microwave frequencies to induce a very high and localized temperature increase, which causes an irreversible thermal damage in the target zone. Treatment planning in MTA is based on experimental observations of ablation zones in ex vivo tissue, while predicting the treatment outcomes could be greatly improved by reliable numerical models. In this work, a fully dynamical simulation model is exploited to look at effects of temperature-dependent variations in the dielectric and thermal properties of the targeted tissue on the prediction of the temperature increase and the extension of the thermally coagulated zone. In particular, the influence of measurement uncertainty of tissue parameters on the numerical results is investigated. Numerical data were compared with data from MTA experiments performed on ex vivo bovine liver tissue at 2.45GHz, with a power of 60W applied for 10min. By including in the simulation model an uncertainty budget (CI=95%) of ±25% in the properties of the tissue due to inaccuracy of measurements, numerical results were achieved in the range of experimental data. Obtained results also showed that the specific heat especially influences the extension of the thermally coagulated zone, with an increase of 27% in length and 7% in diameter when a variation of -25% is considered with respect to the value of the reference simulation model. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

  9. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

    Science.gov (United States)

    Benson, M

    2016-03-01

    Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide

  10. Evaluation of candidate biomarkers to predict cancer cell sensitivity or resistance to PARP-1 inhibitor treatment

    DEFF Research Database (Denmark)

    Oplustilova, L.; Wolanin, K.; Bartkova, J.

    2012-01-01

    (ADp-ribose) polymerase-1 (PARP-1), an enzyme critical for repair pathways alternative to HR. While promising, treatment with PARP-1 inhibitors (PARP-1i) faces some hurdles, including (1) acquired resistance, (2) search for other sensitizing, non-BRCA1/2 cancer defects and (3) lack of biomarkers to predict response......Impaired DNA damage response pathways may create vulnerabilities of cancer cells that can be exploited therapeutically. One such selective vulnerability is the sensitivity of BRCA1- or BRCA2-defective tumors (hence defective in DNA repair by homologous recombination, HR) to inhibitors of the poly...... to PARP-1i. Here we addressed these issues using PARP-1i on 20 human cell lines from carcinomas of the breast, prostate, colon, pancreas and ovary. Aberrations of the Mre11-Rad50-Nbs1 (MRN) complex sensitized cancer cells to PARP-1i, while p53 status was less predictive, even in response to PARP-1i...

  11. Voxel-Based Dose Prediction with Multi-Patient Atlas Selection for Automated Radiotherapy Treatment Planning

    CERN Document Server

    McIntosh, Chris

    2016-01-01

    Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography (CT) planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical do...

  12. Comprehensive geophysical prediction and treatment measures of karst caves in deep buried tunnel

    Science.gov (United States)

    Li, S. C.; Zhou, Z. Q.; Ye, Z. H.; Li, L. P.; Zhang, Q. Q.; Xu, Z. H.

    2015-05-01

    While tunneling in karst terrains, engineers may encounter hazardous geotechnical structures such as faults, karst caves and collapse columns which may induce geohazards and seriously endanger the construction safety. Geological processes significantly affect the varieties and characteristics of karst caves, and therefore engineering geological and hydrogeological conditions of Shangjiawan Tunnel were analyzed firstly. In order to accurately predict the geometric characteristics of karst caves and their spatial relationship with the tunnel, the Ground Penetrating Radar (GPR) and Geological Drilling (Geo-D) were applied comprehensively in the present study. The Tunnel Seismic Prediction (TSP) system was also applied to forecast whether any karst cave existed in front of the tunnel face and the detection results generally agree well with the field investigation. Furthermore, the Beam-Slab method was carried out for the treatment of the karst cave which situated under the tunnel floor, while the Backfill method was applied for the karst cave which was exposed during the construction.

  13. University ranking methodologies. An interview with Ben Sowter about the Quacquarelli Symonds World University Ranking

    OpenAIRE

    Alberto Baccini; Antono Banfi; Giuseppe De Nicolao; Paola Galimberti

    2015-01-01

    University rankings represent a controversial issue in the debate about higher education policy. One of the best known university ranking is the Quacquarelli Symonds World University Rankings (QS), published annually since 2004 by Quacquarelli Symonds ltd, a company founded in 1990 and headquartered in London. QS provides a ranking based on a score calculated by weighting six different indicators. The 2015 edition, published in October 2015, introduced major methodological innovations and, as...

  14. The LAILAPS search engine: relevance ranking in life science databases.

    Science.gov (United States)

    Lange, Matthias; Spies, Karl; Bargsten, Joachim; Haberhauer, Gregor; Klapperstück, Matthias; Leps, Michael; Weinel, Christian; Wünschiers, Röbbe; Weissbach, Mandy; Stein, Jens; Scholz, Uwe

    2010-01-15

    Search engines and retrieval systems are popular tools at a life science desktop. The manual inspection of hundreds of database entries, that reflect a life science concept or fact, is a time intensive daily work. Hereby, not the number of query results matters, but the relevance does. In this paper, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. With a set of features, extracted from each database hit in combination with user relevance preferences, a neural network predicts user specific relevance scores. Using expert knowledge as training data for a predefined neural network or using users own relevance training sets, a reliable relevance ranking of database hits has been implemented. In this paper, we present the LAILAPS system, the concepts, benchmarks and use cases. LAILAPS is public available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

  15. Low-Rank Affinity Based Local-Driven Multilabel Propagation

    Directory of Open Access Journals (Sweden)

    Teng Li

    2013-01-01

    Full Text Available This paper presents a novel low-rank affinity based local-driven algorithm to robustly propagate the multilabels from training images to test images. A graph is constructed over the segmented local image regions. The labels for vertices from the training data are derived based on the context among different training images, and the derived vertex labels are propagated to the unlabeled vertices via the graph. The multitask low-rank affinity, which jointly seeks the sparsity-consistent low-rank affinities from multiple feature matrices, is applied to compute the edge weights between graph vertices. The inference process of multitask low-rank affinity is formulated as a constrained nuclear norm and ℓ2,1-norm minimization problem. The optimization is conducted efficiently with the augmented Lagrange multiplier method. Based on the learned local patch labels we can predict the multilabels for the test images. Experiments on multilabel image annotation demonstrate the encouraging results from the proposed framework.

  16. Social rank affects the haematologic profile in red deer hinds.

    Science.gov (United States)

    Ceacero, Francisco; Gaspar-López, Enrique; Landete-Castillejos, Tomás; Gallego, Laureano; García, Andrés J

    2018-01-26

    We studied the effects of social rank on the haematologic profile in a herd of 24 female Iberian red deer hinds. Social rank hierarchy was determined and blood samples were taken and analysed. After adjusting for age and body mass, dominance ranking showed a significant negative effect (ie, lower values in dominant hinds) on white blood cell (WBC) count, haemoglobin and haematocrit. Our results are similar to those reported for stressed individuals due to physical immobilisation, but do not support the predicted enhanced erythropoiesis due to higher levels of androgens. The results for WBC numbers may also reflect that subordinate hinds must allocate a higher amount of resources to immunity as a result of injuries incurred from dominant hinds, while simultaneously facing restricted access to food sources. For red blood cell (RBC) counts, the results may be due to subordinate hinds likely needing increased haematocrit and haemoglobin levels for fast flight responses. Our data show that social rank influences haematologic profile, and thus it should be considered when correctly interpreting blood analyses in social cervid species. © British Veterinary Association (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  17. Low-rank regularization for learning gene expression programs.

    Science.gov (United States)

    Ye, Guibo; Tang, Mengfan; Cai, Jian-Feng; Nie, Qing; Xie, Xiaohui

    2013-01-01

    Learning gene expression programs directly from a set of observations is challenging due to the complexity of gene regulation, high noise of experimental measurements, and insufficient number of experimental measurements. Imposing additional constraints with strong and biologically motivated regularizations is critical in developing reliable and effective algorithms for inferring gene expression programs. Here we propose a new form of regulation that constrains the number of independent connectivity patterns between regulators and targets, motivated by the modular design of gene regulatory programs and the belief that the total number of independent regulatory modules should be small. We formulate a multi-target linear regression framework to incorporate this type of regulation, in which the number of independent connectivity patterns is expressed as the rank of the connectivity matrix between regulators and targets. We then generalize the linear framework to nonlinear cases, and prove that the generalized low-rank regularization model is still convex. Efficient algorithms are derived to solve both the linear and nonlinear low-rank regularized problems. Finally, we test the algorithms on three gene expression datasets, and show that the low-rank regularization improves the accuracy of gene expression prediction in these three datasets.

  18. Dendritic cell vaccination for glioblastoma multiforme: review with focus on predictive factors for treatment response

    Directory of Open Access Journals (Sweden)

    Dejaegher J

    2014-03-01

    Full Text Available Joost Dejaegher,1 Stefaan Van Gool,2 Steven De Vleeschouwer1 1Department of Neurosciences, 2Department of Microbiology and Immunology, KU Leuven, Leuven, Belgium Abstract: Glioblastoma multiforme (GBM is the most common and most aggressive type of primary brain cancer. Since median overall survival with multimodal standard therapy is only 15 months, there is a clear need for additional effective and long-lasting treatments. Dendritic cell (DC vaccination is an experimental immunotherapy being tested in several Phase I and Phase II clinical trials. In these trials, safety and feasibility have been proven, and promising clinical results have been reported. On the other hand, it is becoming clear that not every GBM patient will benefit from this highly personalized treatment. Defining the subgroup of patients likely to respond to DC vaccination will position this option correctly amongst other new GBM treatment modalities, and pave the way to incorporation in standard therapy. This review provides an overview of GBM treatment options and focuses on the currently known prognostic and predictive factors for response to DC vaccination. In this way, it will provide the clinician with the theoretical background to refer patients who might benefit from this treatment. Keywords: immunotherapy, personalized medicine, brain tumor, stratification

  19. Dendritic cell vaccination for glioblastoma multiforme: review with focus on predictive factors for treatment response

    Science.gov (United States)

    Dejaegher, Joost; Van Gool, Stefaan; De Vleeschouwer, Steven

    2014-01-01

    Glioblastoma multiforme (GBM) is the most common and most aggressive type of primary brain cancer. Since median overall survival with multimodal standard therapy is only 15 months, there is a clear need for additional effective and long-lasting treatments. Dendritic cell (DC) vaccination is an experimental immunotherapy being tested in several Phase I and Phase II clinical trials. In these trials, safety and feasibility have been proven, and promising clinical results have been reported. On the other hand, it is becoming clear that not every GBM patient will benefit from this highly personalized treatment. Defining the subgroup of patients likely to respond to DC vaccination will position this option correctly amongst other new GBM treatment modalities, and pave the way to incorporation in standard therapy. This review provides an overview of GBM treatment options and focuses on the currently known prognostic and predictive factors for response to DC vaccination. In this way, it will provide the clinician with the theoretical background to refer patients who might benefit from this treatment. PMID:27471700

  20. Universal emergence of PageRank

    Energy Technology Data Exchange (ETDEWEB)

    Frahm, K M; Georgeot, B; Shepelyansky, D L, E-mail: frahm@irsamc.ups-tlse.fr, E-mail: georgeot@irsamc.ups-tlse.fr, E-mail: dima@irsamc.ups-tlse.fr [Laboratoire de Physique Theorique du CNRS, IRSAMC, Universite de Toulouse, UPS, 31062 Toulouse (France)

    2011-11-18

    The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter {alpha} Element-Of ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when {alpha} {yields} 1. The whole network can be divided into a core part and a group of invariant subspaces. For {alpha} {yields} 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at {alpha} {yields} 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

  1. Comparing classical and quantum PageRanks

    Science.gov (United States)

    Loke, T.; Tang, J. W.; Rodriguez, J.; Small, M.; Wang, J. B.

    2017-01-01

    Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker's probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.

  2. Reliability of journal impact factor rankings

    Science.gov (United States)

    Greenwood, Darren C

    2007-01-01

    Background Journal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises. Methods Based on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators. Results Intervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals. Conclusion Decisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate. PMID:18005435

  3. Reliability of journal impact factor rankings

    Directory of Open Access Journals (Sweden)

    Greenwood Darren C

    2007-11-01

    Full Text Available Abstract Background Journal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises. Methods Based on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators. Results Intervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals. Conclusion Decisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate.

  4. Cointegration rank testing under conditional heteroskedasticity

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, Robert M.

    2010-01-01

    (martingale difference) innovations. We first demonstrate that the limiting null distributions of the rank statistics coincide with those derived by previous authors who assume either independent and identically distributed (i.i.d.) or (strict and covariance) stationary martingale difference innovations. We...... then propose wild bootstrap implementations of the cointegrating rank tests and demonstrate that the associated bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show that the same is also true of the corresponding rank tests based on the i.......i.d. bootstrap of Swensen (2006, Econometrica 74, 1699-1714). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap, it preserves in the resampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence suggests that...

  5. Parkinsonian motor impairment predicts personality domains related to genetic risk and treatment outcomes in schizophrenia.

    Science.gov (United States)

    Molina, Juan L; Calvó, María; Padilla, Eduardo; Balda, Mara; Alemán, Gabriela González; Florenzano, Néstor V; Guerrero, Gonzalo; Kamis, Danielle; Rangeon, Beatriz Molina; Bourdieu, Mercedes; Strejilevich, Sergio A; Conesa, Horacio A; Escobar, Javier I; Zwir, Igor; Cloninger, C Robert; de Erausquin, Gabriel A

    2017-01-01

    Identifying endophenotypes of schizophrenia is of critical importance and has profound implications on clinical practice. Here we propose an innovative approach to clarify the mechanims through which temperament and character deviance relates to risk for schizophrenia and predict long-term treatment outcomes. We recruited 61 antipsychotic naïve subjects with chronic schizophrenia, 99 unaffected relatives, and 68 healthy controls from rural communities in the Central Andes. Diagnosis was ascertained with the Schedules of Clinical Assessment in Neuropsychiatry; parkinsonian motor impairment was measured with the Unified Parkinson's Disease Rating Scale; mesencephalic parenchyma was evaluated with transcranial ultrasound; and personality traits were assessed using the Temperament and Character Inventory. Ten-year outcome data was available for ~40% of the index cases. Patients with schizophrenia had higher harm avoidance and self-transcendence (ST), and lower reward dependence (RD), cooperativeness (CO), and self-directedness (SD). Unaffected relatives had higher ST and lower CO and SD. Parkinsonism reliably predicted RD, CO, and SD after correcting for age and sex. The average duration of untreated psychosis (DUP) was over 5 years. Further, SD was anticorrelated with DUP and antipsychotic dosing at follow-up. Baseline DUP was related to antipsychotic dose-years. Further, 'explosive/borderline', 'methodical/obsessive', and 'disorganized/schizotypal' personality profiles were associated with increased risk of schizophrenia. Parkinsonism predicts core personality features and treatment outcomes in schizophrenia. Our study suggests that RD, CO, and SD are endophenotypes of the disease that may, in part, be mediated by dopaminergic function. Further, SD is an important determinant of treatment course and outcome.

  6. Tumoral cubilin is a predictive marker for treatment of renal cancer patients with sunitinib and sorafenib.

    Science.gov (United States)

    Niinivirta, Marjut; Enblad, Gunilla; Edqvist, Per-Henrik; Pontén, Fredrik; Dragomir, Anca; Ullenhag, Gustav J

    2017-06-01

    Tyrosine kinase inhibitors like sunitinib and sorafenib are commonly used to treat metastatic renal cell cancer patients. Cubilin is a membrane protein expressed in the proximal renal tubule. Cubilin and megalin function together as endocytic receptors mediating uptake of many proteins. There is no established predictive marker for metastatic renal cell cancer patients and the purpose of the present study was to assess if cubilin can predict response to treatment with tyrosine kinase inhibitors. Cubilin protein expression was analyzsed in tumor tissue from a cohort of patients with metastatic renal cell cancer (n = 139) using immunohistochemistry. One hundred and thirty six of the patients were treated with sunitinib or sorafenib in the first- or second-line setting. Thirty of these were censored because of toxicity leading to the termination of treatment and the remaining (n = 106) were selected for the current study. Fifty-three (50%) of the tumors expressed cubilin in the membrane. The median progression-free survival was 8 months in patients with cubilin expressing tumors and 4 months in the cubilin negative group. In addition, the overall survival was better for patients with cubilin positive tumors. We also found that the fraction of cubilin negative patients was significantly higher in the non-responding group (PFS ≤3 months) compared to responding patients (PFS >3 months). We show for the first time that tumoral expression of cubilin is a positive predictive marker for treatment of metastatic renal cell cancer patients with sunitinib and sorafenib.

  7. PageRank and rank-reversal dependence on the damping factor

    Science.gov (United States)

    Son, S.-W.; Christensen, C.; Grassberger, P.; Paczuski, M.

    2012-12-01

    PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d0=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d0.

  8. PageRank and rank-reversal dependence on the damping factor.

    Science.gov (United States)

    Son, S-W; Christensen, C; Grassberger, P; Paczuski, M

    2012-12-01

    PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d_{0}=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d_{0}.

  9. A tilting approach to ranking influence

    KAUST Repository

    Genton, Marc G.

    2014-12-01

    We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

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

    Science.gov (United States)

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

    2012-01-01

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

  11. Analysis of linear dynamic systems of low rank

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2003-01-01

    We present here procedures of how obtain stable solutions to linear dynamic systems can be found. Different types of models are considered. The basic idea is to use the H-principle to develop low rank approximations to solutions. The approximations stop, when the prediction ability of the model...... cannot be improved for the present data. Therefore, the present methods give better prediction results than traditional methods that give exact solutions. The vectors used in the approximations can be used to carry out graphic analysis of the dynamic systems. We show how score vectors can display the low...

  12. Helping alliance and outcome in psychotherapy: what predicts what in routine outpatient treatment?

    Science.gov (United States)

    Puschner, Bernd; Wolf, Markus; Kraft, Susanne

    2008-03-01

    This naturalistic longitudinal study analyzed the reciprocal dependency of the helping alliance and symptom outcome over the course of mid- and long-term outpatient psychotherapy as practiced in routine care in Germany. Patient-rated helping alliance and symptom distress were assessed repeatedly over a 2-year period in a sample of 259 outpatients in psychodynamic, cognitive-behavioral, and psychoanalytic psychotherapy. Hierarchical linear models showed that initial symptom distress negatively predicted subsequent quality of the helping alliance but not vice versa. Only initial symptom distress affected symptom status at the last treatment session. These results raise doubts about the helping alliance being a strong predictor of outcome and indicate that other patient and therapist variables might be more important for treatment success.

  13. Agitation predicts response of depression to botulinum toxin treatment in a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Marc Axel Wollmer

    2014-03-01

    Full Text Available In a randomized, controlled trial (n=30 we showed that botulinum toxin injection to the glabellar region produces a marked improvement in the symptoms of major depression. We hypothesized that the mood-lifting effect was mediated by facial feedback mechanisms. Here we assessed if agitation, which may be associated with increased dynamic psychomotor activity of the facial musculature, can predict response to the treatment. To test this hypothesis we re-analyzed the data of the scales from our previous study on a single item basis and compared the baseline scores in the agitation item (item 9 of the Hamilton Depression Rating Scale (HAM-D between responders (n=9 and participants who did not attain response (n=6 among the recipients of onabotulinumtoxinA (n=15. Results: Responders had significantly higher item 9 scores at baseline (1.56+0.88 vs. 0.33+0.52, t(13=3.04, d=1.7, p=0.01, while no other single item of the HAM-D or the Beck Depression Inventory was associated with treatment response. The agitation score had an overall precision of 78% in predicting response in a receiver operating characteristic (ROC analysis (area under the curve, AUC=0.87. These data provide a link between response to botulinum toxin treatment with a psychomotor manifestation of depression and thereby indirect support of the proposed facial feedback mechanism of action. Moreover, it suggests that patients with agitated depression may particularly benefit from botulinum toxin treatment.

  14. University ranking methodologies. An interview with Ben Sowter about the Quacquarelli Symonds World University Ranking

    Directory of Open Access Journals (Sweden)

    Alberto Baccini

    2015-10-01

    Full Text Available University rankings represent a controversial issue in the debate about higher education policy. One of the best known university ranking is the Quacquarelli Symonds World University Rankings (QS, published annually since 2004 by Quacquarelli Symonds ltd, a company founded in 1990 and headquartered in London. QS provides a ranking based on a score calculated by weighting six different indicators. The 2015 edition, published in October 2015, introduced major methodological innovations and, as a consequence, many universities worldwide underwent major changes of their scores and ranks. Ben Sowter, head of division of intelligence unit of Quacquarelli Symonds, responds to 15 questions about the new QS methodology.

  15. On a common generalization of Shelah's 2-rank, dp-rank, and o-minimal dimension

    OpenAIRE

    Guingona, Vincent; Hill, Cameron Donnay

    2013-01-01

    In this paper, we build a dimension theory related to Shelah's 2-rank, dp-rank, and o-minimal dimension. We call this dimension op-dimension. We exhibit the notion of the n-multi-order property, generalizing the order property, and use this to create op-rank, which generalizes 2-rank. From this we build op-dimension. We show that op-dimension bounds dp-rank, that op-dimension is sub-additive, and op-dimension generalizes o-minimal dimension in o-minimal theories.

  16. Academic rankings: an approach to rank portuguese universities Rankings académicos: un abordaje para clasificar las universidades portuguesas Rankings acadêmicos: uma abordagem ao ranking das universidades portuguesas

    Directory of Open Access Journals (Sweden)

    Pedro Bernardino

    2010-03-01

    Full Text Available The academic rankings are a controversial subject in higher education. However, despite all the criticism, academic rankings are here to stay and more and more different stakeholders use rankings to obtain information about the institutions' performance. The two most well-known rankings, The Times and the Shanghai Jiao Tong University rankings have different methodologies. The Times ranking is based on peer review, whereas the Shanghai ranking has only quantitative indicators and is mainly based on research outputs. In Germany, the CHE ranking uses a different methodology from the traditional rankings, allowing the users to choose criteria and weights. The Portuguese higher education institutions are performing below their European peers, and the Government believes that an academic ranking could improve both performance and competitiveness between institutions. The purpose of this paper is to analyse the advantages and problems of academic rankings and provide guidance to a new Portuguese ranking.Los rankings académicos son un tema muy contradictorio en la enseñanza superior. Todavía, además de todas las críticas los rankings están para quedarse entre nosotros. Y cada vez más, diferentes stakeholders utilizan los rankings para obtener información sobre el desempeño de las instituciones. Dos de los rankings más conocidos, el The Times y el ranking de la universidad de Shangai Jiao Tong tienen métodos distintos. El The Times se basa en la opinión de expertos mientras el ranking de la universidad de Shangai presenta solamente indicadores cuantitativos y mayoritariamente basados en los resultados de actividades de investigación. En Alemania el ranking CHE usa un método distinto permitiendo al utilizador elegir los criterios y su importancia. Las instituciones de enseñanza superior portuguesas tienen un desempeño abajo de las europeas y el gobierno cree que un ranking académico podría contribuir para mejorar su desempeño y

  17. Using behavioral economics to predict opioid use during prescription opioid dependence treatment.

    Science.gov (United States)

    Worley, Matthew J; Shoptaw, Steven J; Bickel, Warren K; Ling, Walter

    2015-03-01

    Research grounded in behavioral economics has previously linked addictive behavior to disrupted decision-making and reward-processing, but these principles have not been examined in prescription opioid addiction, which is currently a major public health problem. This study examined whether pre-treatment drug reinforcement value predicted opioid use during outpatient treatment of prescription opioid addiction. Secondary analyses examined participants with prescription opioid dependence who received 12 weeks of buprenorphine-naloxone and counseling in a multi-site clinical trial (N=353). Baseline measures assessed opioid source and indices of drug reinforcement value, including the total amount and proportion of income spent on drugs. Weekly urine drug screens measured opioid use. Obtaining opioids from doctors was associated with lower pre-treatment drug spending, while obtaining opioids from dealers/patients was associated with greater spending. Controlling for demographics, opioid use history, and opioid source frequency, patients who spent a greater total amount (OR=1.30, peconomic resources to drugs, reflects propensity for continued opioid use during treatment among individuals with prescription opioid addiction. Future studies should examine disrupted decision-making and reward-processing in prescription opioid users more directly and test whether reinforcer pathology can be remediated in this population. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Predicting depression outcome in mental health treatment: a recursive partitioning analysis.

    Science.gov (United States)

    Berman, Margit I; Hegel, Mark T

    2014-01-01

    Recursive partitioning was applied to a longitudinal dataset of outpatient mental health clinic patients to identify empirically factors and interactions among factors that best predicted clinical improvement and deterioration in symptoms of depression across treatment. Sixty-two variables drawn from an initial patient survey and from chart review were included as covariates in the analysis, representing nearly all of the demographic, treatment, symptom, diagnostic, and social history information obtained from patients at their initial evaluations. Trees estimated the probability of participants' having depression at their last assessment, improving to a clinically significant degree during treatment, or developing a new onset of significant depressive symptoms during treatment. Initial pain, the presence of anxiety, and a history of multiple types of abuse were risk factors for poorer outcome, even among patients who did not initially have significant depressive symptoms. By examining multiple-related outcomes, we were able to create a series of overlapping models that revealed important predictors across trees. Limitations of the study included the lack of cross-validation of the trees and the exploratory nature of the analysis.

  19. Factors predicting the outcome following medical treatment of mesial temporal epilepsy with hippocampal sclerosis.

    Science.gov (United States)

    Sànchez, Javier; Centanaro, Mirella; Solís, Juanita; Delgado, Fabrizio; Yépez, Luis

    2014-06-01

    There is a lack of information from South America regarding factors that predict the clinical outcomes of patients treated medically for mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). This study was conducted to determine which of these factors are the most important. This study included 110 South American patients with MTLE-HS treated with antiepileptic drugs. The factors considered included age, gender, age of epilepsy onset, interval between the lesion and the first seizure, central nervous system infection, traumatic brain injury, perinatal asphyxia, febrile convulsion, history of status epilepticus, types of seizures, site of hippocampal sclerosis (HS), extrahippocampal pathology, and electroencephalogram (EEG) abnormalities. The patients were divided into two groups based on the response to treatment: Group I, seizure free for at least two years; and Group II, not seizure free. On the multivariate analysis, the factors associated with a poor prognosis in terms of seizure frequency and control following treatment included the presence of an early onset of seizure, more than 10 seizures per month before treatment, and EEG abnormalities. The recognition of risk factors, such as early onset of seizures, more than 10 seizures per month before treatment, and EEG abnormalities, could lead to the identification of risk groups among patients with MTLE-HS and refractory epilepsy, possibly designating these individuals as candidates for early epilepsy surgery. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  20. Adiabatic quantum algorithm for search engine ranking.

    Science.gov (United States)

    Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A

    2012-06-08

    We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

  1. Adiabatic Quantum Algorithm for Search Engine Ranking

    Science.gov (United States)

    Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A.

    2012-06-01

    We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log⁡(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in “q-sampling” protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

  2. Percutaneous aspiration and irrigation technique for the treatment of pediatric septic hip: effectiveness and predictive parameters.

    Science.gov (United States)

    Weigl, Daniel M; Becker, Tali; Mercado, Eyal; Bar-On, Elhanan

    2016-11-01

    Septic arthritis of the hip has been treated traditionally by surgical drainage. Recent reports have described repeated aspirations as an adequate and safe treatment. The aim of the present study was to assess the success of treatment of septic arthritis of the hip by repeated aspirations and to identify predictive factors for failure. Medical records were retrospectively reviewed for all patients treated by ultrasound-guided aspiration and intravenous antibiotics between 2002 and 2010. The demographic, clinical, laboratory, and outcome data were recorded. Findings were compared between patients who responded to this treatment and those who subsequently required surgery. A total of 42 patients fulfilled the inclusion criteria. Of the total 33 responded to repeated aspirations and nine required surgical drainage. The mean age of patients requiring surgery was 8.3 years compared with 2.6 years for those responding to aspirations. Age older than 10 years was associated with a 57% rate of failed conservative treatment compared with 14% for age younger than 10 years. There was no significant difference between the groups in any of the other parameters measured. Follow-up of the operated group after an average of 7.44 years showed no unfavorable results. In children with septic arthritis of the hip, hip decompression may be achieved with repeated aspirations and lavage combined with antibiotics, sparing patients the risks of anesthesia and surgery. Age older than 10 years at admission may serve as the cutoff for initial conservative treatment. The postponement of surgery did not cause any long-term morbidity. Level III; patients compared on the basis of outcome of conservative treatment of septic hip arthritis.

  3. Prediction factors for failure to seek treatment following traumatic dental injuries to primary teeth

    Directory of Open Access Journals (Sweden)

    Ramon Targino Firmino

    2014-06-01

    Full Text Available The objective of this study was to evaluate prediction factors for failure to seek treatment following a traumatic dental injury (TDI to primary teeth among preschool children in the city of Campina Grande, Brazil. A cross-sectional study was carried out involving 277 children 3 to 5 years of age, with TDI, enrolled in public and private preschools. Parents filled out a form addressing demographic data and whether or not they had sought treatment. Clinical examinations were performed by three dentists who had undergone a calibration exercise (Kappa: 0.85 to 0.90 for the evaluation of TDI. Bivariate and multivariate Poisson regression models were constructed (α = 5%. Enamel fracture was the most prevalent type of TDI (48.7% and the upper central incisors were the most affected teeth (88.4%. The frequency of seeking dental treatment was low (9.7%. The following variables were associated with failure to seek treatment following TDI: a household income greater than one minimum wage (PR = 1.170; 95%CI 1.018-1.341, parents/caregivers’ perception of a child’s oral health as poor (PR = 1.100; 95%CI 1.026-1.176, and the non-perception of TDI by parents/caregivers (PR = 1.250; 95%CI 1.142-1.360. In the present study, the frequency of seeking treatment following TDI was low, and parents/caregivers with a higher income, a poor perception of their child’s oral health and a lack of awareness regarding the trauma were more likely to fail to seek treatment following TDI to primary teeth.

  4. Maintenance treatment with azathioprine in ulcerative colitis: outcome and predictive factors after drug withdrawal.

    Science.gov (United States)

    Cassinotti, Andrea; Actis, Giovanni C; Duca, Piergiorgio; Massari, Alessandro; Colombo, Elisabetta; Gai, Elisa; Annese, Vito; D'Albasio, Giuseppe; Manes, Gianpiero; Travis, Simon; Porro, Gabriele Bianchi; Ardizzone, Sandro

    2009-11-01

    Whether the duration of maintenance treatment with azathioprine (AZA) affects the outcome of ulcerative colitis (UC) is unclear. We investigated clinical outcomes and any predictive factors after withdrawal of AZA in UC. In this multicenter observational retrospective study, 127 Italian UC patients, who were in steroid-free remission at the time of withdrawal of AZA, were followed-up for a median of 55 months or until relapse. The frequency of clinical relapse or colectomy after AZA withdrawal was analyzed according to demographic, clinical, and endoscopic variables. After drug withdrawal, a third of the patients relapsed within 12 months, half within 2 years and two-thirds within 5 years. After multivariable analysis, predictors of relapse after drug withdrawal were lack of sustained remission during AZA maintenance (hazard ratio, HR 2.350, confidence interval, CI 95% 1.434-3.852; P=0.001), extensive colitis (HR 1.793, CI 95% 1.064-3.023, P=0.028 vs. left-sided colitis; HR 2.024, CI 95% 1.103-3.717, P=0.023 vs. distal colitis), and treatment duration, with short treatments (3-6 months) more disadvantaged than >48-month treatments (HR 2.783, CI 95% 1.267-6.114, P=0.008). Concomitant aminosalicylates were the only predictors of sustained remission during AZA therapy (P=0.009). The overall colectomy rate was 10%. Predictors of colectomy were drug-related toxicity as the cause of AZA withdrawal (P=0.041), no post-AZA drug therapy (P=0.031), and treatment duration (P<0.0005). Discontinuation of AZA while UC is in remission is associated with a high relapse rate. Disease extent, lack of sustained remission during AZA, and discontinuation due to toxicity could stratify relapse risk. Concomitant aminosalicylates were advantageous. Prospective randomized controlled trials are needed to confirm whether treatment duration is inversely associated with outcome.

  5. HIV-1 DNA predicts disease progression and post-treatment virological control

    Science.gov (United States)

    Williams, James P; Hurst, Jacob; Stöhr, Wolfgang; Robinson, Nicola; Brown, Helen; Fisher, Martin; Kinloch, Sabine; Cooper, David; Schechter, Mauro; Tambussi, Giuseppe; Fidler, Sarah; Carrington, Mary; Babiker, Abdel; Weber, Jonathan

    2014-01-01

    In HIV-1 infection, a population of latently infected cells facilitates viral persistence despite antiretroviral therapy (ART). With the aim of identifying individuals in whom ART might induce a period of viraemic control on stopping therapy, we hypothesised that quantification of the pool of latently infected cells in primary HIV-1 infection (PHI) would predict clinical progression and viral replication following ART. We measured HIV-1 DNA in a highly characterised randomised population of individuals with PHI. We explored associations between HIV-1 DNA and immunological and virological markers of clinical progression, including viral rebound in those interrupting therapy. In multivariable analyses, HIV-1 DNA was more predictive of disease progression than plasma viral load and, at treatment interruption, predicted time to plasma virus rebound. HIV-1 DNA may help identify individuals who could safely interrupt ART in future HIV-1 eradication trials. Clinical trial registration: ISRCTN76742797 and EudraCT2004-000446-20 DOI: http://dx.doi.org/10.7554/eLife.03821.001 PMID:25217531

  6. Tinea capitis: predictive value of symptoms and time to cure with griseofulvin treatment.

    Science.gov (United States)

    Lorch Dauk, Kelly C; Comrov, Elana; Blumer, Jeffrey L; O'Riordan, Mary Ann; Furman, Lydia M

    2010-03-01

    To describe (a) the predictive value of symptoms for diagnosis of tinea capitis and (b) the rate and timing of cure with high-dose griseofulvin treatment. This prospective open-label study enrolled children aged 1 to 12 years with clinical tinea capitis. Participants with a positive dermatophyte culture received oral griseofulvin (20-25 mg/kg/day) and topical selenium sulfide shampoo for 6 weeks. Main outcome measures. The rate of symptoms of tinea capitis, and rates of mycologic and clinical cure. The positive predictive values of any 1, 2, 3, or 4 symptoms for a positive culture were 88%, 82%, 78%, and 77%, respectively. The observed rates of mycologic, clinical, and complete cure were 89%, 66%, and 49%, respectively. conclusion: In a high-risk population it is reasonable to diagnose tinea capitis using one or more cardinal symptoms. Oral griseofulvin at 20 to 25 mg/ kg/day with adjunctive shampooing for 6 weeks is moderately successful as treatment.

  7. Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

    Science.gov (United States)

    Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

    2017-10-11

    Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

  8. Narrow-diameter implants: are they a predictable treatment option? A literature review.

    Science.gov (United States)

    Sierra-Sánchez, José-Luis; Martínez-González, Amparo; García-Sala Bonmatí, Fernando; Mañes-Ferrer, José-Félix; Brotons-Oliver, Alejandro

    2014-01-01

    To evaluate the predictability of narrow-diameter implants as a treatment option in routine clinical practice. A literature review was performed of studies reporting clinical results obtained with these implants. Survival rates, peri-implant bone loss and related complications were evaluated. The working hypothesis was that narrow-diameter implants offer clinical results similar to those obtained with implants of greater diameter. A Medline-PubMed search covering the period between 2002 and 2012 was carried out. Studies published in English and with a follow-up period of at least 12 months were considered for inclusion. A manual search was also conducted in different journals with an important impact factor. results: Twenty-one studies meeting the screening criteria were included in the literature review. A total of 2980 narrow-diameter implants placed in 1607 patients were analyzed. The results obtained from the literature indicate that narrow-diameter implants are a predictable treatment option, since they afford clinical results comparable to those obtained with implants of greater diameter.

  9. Citric Acid Metabolism in Resistant Hypertension: Underlying Mechanisms and Metabolic Prediction of Treatment Response.

    Science.gov (United States)

    Martin-Lorenzo, Marta; Martinez, Paula J; Baldan-Martin, Montserrat; Ruiz-Hurtado, Gema; Prado, Jose Carlos; Segura, Julian; de la Cuesta, Fernando; Barderas, Maria G; Vivanco, Fernando; Ruilope, Luis Miguel; Alvarez-Llamas, Gloria

    2017-11-01

    Resistant hypertension (RH) affects 9% to 12% of hypertensive adults. Prolonged exposure to suboptimal blood pressure control results in end-organ damage and cardiovascular risk. Spironolactone is the most effective drug for treatment, but not all patients respond and side effects are not negligible. Little is known on the mechanisms responsible for RH. We aimed to identify metabolic alterations in urine. In addition, a potential capacity of metabolites to predict response to spironolactone was investigated. Urine was collected from 29 patients with RH and from a group of 13 subjects with pseudo-RH. For patients, samples were collected before and after spironolactone administration and were classified in responders (n=19) and nonresponders (n=10). Nuclear magnetic resonance was applied to identify altered metabolites and pathways. Metabolites were confirmed by liquid chromatography-mass spectrometry. Citric acid cycle was the pathway most significantly altered (Pcitric acid cycle and deregulation of reactive oxygen species homeostasis control continue its activation after hypertension was developed. A metabolic panel showing alteration before spironolactone treatment and predicting future response of patients is shown. These molecular indicators will contribute optimizing the rate of control of RH patients with spironolactone. © 2017 American Heart Association, Inc.

  10. The potential use of expression profiling: implications for predicting treatment response in rheumatoid arthritis.

    Science.gov (United States)

    Smith, Samantha Louise; Plant, Darren; Eyre, Stephen; Barton, Anne

    2013-07-01

    Whole genome expression profiling, or transcriptomics, is a high throughput technology with the potential for major impacts in both clinical settings and drug discovery and diagnostics. In particular, there is much interest in this technique as a mechanism for predicting treatment response. Gene expression profiling entails the quantitative measurement of messenger RNA levels for thousands of genes simultaneously with the inherent possibility of identifying biomarkers of response to a particular therapy or by singling out those at risk of serious adverse events. This technology should contribute to the era of stratified medicine, in which patient specific populations are matched to potentially beneficial drugs via clinical tests. Indeed, in the oncology field, gene expression testing is already recommended to allow rational use of therapies to treat breast cancer. However, there are still many issues surrounding the use of the various testing platforms available and the statistical analysis associated with the interpretation of results generated. This review will discuss the implications this promising technology has in predicting treatment response and outline the various advantages and pitfalls associated with its use.

  11. Stathmin protein level, a potential predictive marker for taxane treatment response in endometrial cancer.

    Directory of Open Access Journals (Sweden)

    Henrica M J Werner

    Full Text Available Stathmin is a prognostic marker in many cancers, including endometrial cancer. Preclinical studies, predominantly in breast cancer, have suggested that stathmin may additionally be a predictive marker for response to paclitaxel. We first evaluated the response to paclitaxel in endometrial cancer cell lines before and after stathmin knock-down. Subsequently we investigated the clinical response to paclitaxel containing chemotherapy in metastatic endometrial cancer in relation to stathmin protein level in tumors. Stathmin level was also determined in metastatic lesions, analyzing changes in biomarker status on disease progression. Knock-down of stathmin improved sensitivity to paclitaxel in endometrial carcinoma cell lines with both naturally higher and lower sensitivity to paclitaxel. In clinical samples, high stathmin level was demonstrated to be associated with poor response to paclitaxel containing chemotherapy and to reduced disease specific survival only in patients treated with such combination. Stathmin level increased significantly from primary to metastatic lesions. This study suggests, supported by both preclinical and clinical data, that stathmin could be a predictive biomarker for response to paclitaxel treatment in endometrial cancer. Re-assessment of stathmin level in metastatic lesions prior to treatment start may be relevant. Also, validation in a randomized clinical trial will be important.

  12. Augmenting the Deliberative Method for Ranking Risks.

    Science.gov (United States)

    Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

    2016-01-01

    The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

  13. Global DNA methylation is altered by neoadjuvant chemoradiotherapy in rectal cancer and may predict response to treatment - A pilot study.

    LENUS (Irish Health Repository)

    Tsang, J S

    2014-07-28

    In rectal cancer, not all tumours display a response to neoadjuvant treatment. An accurate predictor of response does not exist to guide patient-specific treatment. DNA methylation is a distinctive molecular pathway in colorectal carcinogenesis. Whether DNA methylation is altered by neoadjuvant treatment and a potential response predictor is unknown. We aimed to determine whether DNA methylation is altered by neoadjuvant chemoradiotherapy (CRT) and to determine its role in predicting response to treatment.

  14. Point scoring system to rank traffic calming projects

    Directory of Open Access Journals (Sweden)

    Farzana Rahman

    2016-08-01

    Full Text Available The installation of calming measures on a road network is systematically planned way in general to reduce driving speeds, but also reduces the volume of through traffic on local and residential streets. When the demands of traffic calming exceed city resources, there is a need to prioritize or rank them. Asian countries, like Japan, Korea, Bangladesh and etc., do not have a prioritization system to apply in such cases. The objective of this research is to develop a point ranking system to prioritize traffic calming projects. Firstly paired comparison method was employed to obtain residents' opinions about the streets severity and needs of traffic calming treatment. A binary logistic regression model was developed to identify the factors of selecting streets for traffic calming. This model also explored the weight of variables during developing the point ranking system. The weights used in the point ranking system include vehicle speed, pedestrian generation, sidewalk condition and hourly vehicle volume per width (m of street. Results suggest that the severity of street largely depends on the absence of sidewalks, which has a weight of 45%, and high hourly vehicle volume of traffic per width (m of street, which has a weight of 38%. These outcomes are significant to develop the state of traffic safety in Japan and other Asian countries.

  15. Serum microRNA expression patterns that predict early treatment failure in prostate cancer patients

    Science.gov (United States)

    Singh, Prashant K.; Preus, Leah; Hu, Qiang; Yan, Li; Long, Mark D.; Morrison, Carl D.; Nesline, Mary; Johnson, Candace S.; Koochekpour, Shahriar; Kohli, Manish; Liu, Song; Trump, Donald L.

    2014-01-01

    We aimed to identify microRNA (miRNA) expression patterns in the serum of prostate cancer (CaP) patients that predict the risk of early treatment failure following radical prostatectomy (RP). Microarray and Q-RT-PCR analyses identified 43 miRNAs as differentiating disease stages within 14 prostate cell lines and reflectedpublically available patient data. 34 of these miRNA were detectable in the serum of CaP patients. Association with time to biochemical progression was examined in a cohort of CaP patients following RP. A greater than two-fold increase in hazard of biochemical progression associated with altered expression of miR-103, miR-125b and miR-222 (p <.0008) in the serum of CaP patients. Prediction models based on penalized regression analyses showed that the levels of the miRNAs and PSA together were better at detecting false positives than models without miRNAs, for similar level of sensitivity. Analyses of publically available data revealed significant and reciprocal relationships between changes in CpG methylation and miRNA expression patterns suggesting a role for CpG methylation to regulate miRNA. Exploratory validation supported roles for miR-222 and miR-125b to predict progression risk in CaP. The current study established that expression patterns of serum-detectable miRNAs taken at the time of RP are prognostic for men who are at risk of experiencing subsequent early biochemical progression. These non-invasive approaches could be used to augment treatment decisions. PMID:24583788

  16. MRI evaluation of anterior knee pain: predicting response to nonoperative treatment

    Energy Technology Data Exchange (ETDEWEB)

    Wittstein, Jocelyn R.; Garrett, William E. [Duke University Medical Center, Division of Orthopaedic Surgery, Durham, NC (United States); O' Brien, Seth D. [Brooke Army Medical Center, Department of Radiology, San Antonio, TX (United States); Vinson, Emily N. [Duke University Medical Center, Department of Radiology, Durham, NC (United States)

    2009-09-15

    Tibial tubercle lateral deviation and patellofemoral chondromalacia are associated with anterior knee pain (AKP). We hypothesized that increased tibial tubercle lateral deviation and patellofemoral chondromalacia on magnetic resonance imaging correlates with the presence of AKP and with failure of nonoperative management. In this retrospective comparative study, a blinded musculoskeletal radiologist measured tibial tubercle lateral deviation relative to the trochlear groove in 15 controls, 15 physical therapy responders with AKP, and 15 physical therapy nonresponders with AKP. Patellar and trochlear cartilage was assessed for signal abnormality, irregularity, and defects. The mean tibial tubercle lateral deviation in controls, physical therapy responders, and physical therapy nonresponders were 9.32 {+-} 0.68, 13.01 {+-} 0.82, and 16.07 {+-} 1.16 mm, respectively (data are mean {+-} standard deviation). The correlation coefficients for tubercle deviation, chondromalacia patellae, and trochlear chondromalacia were 0.51 (P < 0.01), 0.44 (P < 0.01), and 0.28 (P < 0.05), respectively. On analysis of variance, tubercle deviation and chondromalacia patellae contributed significantly to prediction of AKP and response to physical therapy. The presence of chondromalacia patellae and a tubercle deviation greater than 14.6 mm is 100% specific and 67% sensitive with a positive predictive value of 100% and negative predictive value of 75% for failure of nonoperative management. Subjects with AKP have more laterally positioned tibial tubercles and are more likely to have patellar chondromalacia. Patients with AKP, chondromalacia patellae, and a tubercle deviation greater than 14.6 mm are unlikely to respond to nonoperative treatment. Knowledge of tibial tubercle lateralization and presence of chondromalacia patellae may assist clinicians in determining patient prognosis and selecting treatment options. (orig.)

  17. Is electromyography a predictive test of patient response to biofeedback in the treatment of fecal incontinence?

    Science.gov (United States)

    Lacima, Gloria; Pera, Miguel; González-Argenté, Xavier; Torrents, Abiguei; Valls-Solé, Josep; Espuña-Pons, Montserrat

    2016-03-01

    Biofeedback is effective in more than 70% of patients with fecal incontinence. However, reliable predictors of successful treatment have not been identified. The aim was to identify clinical variables and diagnostic tests, particularly electromyography, that could predict a successful outcome. We included 135 consecutive women with fecal incontinence treated with biofeedback. Clinical evaluation, manometry, ultrasonography, electromyography, and pudendal nerve terminal motor latency were performed before therapy. Treatment outcome was assessed using a symptoms diary, Wexner incontinence score and the patient's subjective perception. According to the symptoms diaries, 106 (78.5%) women had a good clinical result and 29 (21.5%) had a poor result. There were no differences in age, severity and type of fecal incontinence. Maximum resting pressure (39.3 ± 19.1 mmHg vs. 33.7 ± 20.2 mmHg; P = 0.156) and maximum squeeze pressure (91.8 ± 33.2 mmHg vs. 79.8 ± 31.2 mmHg; P = 0.127) were higher in patients having good clinical outcome although the difference was not significant. There were no differences in the presence of sphincter defects or abnormalities in electromyographic recordings. Logistic regression analysis found no independent predictive factor for good clinical outcome. Biofeedback is effective in more than 75% of patients with fecal incontinence. Clinical characteristics of patients and results of baseline tests have no predictive value of response to therapy. Specifically, we found no association between severity of electromyographic deficit and clinical response. © 2015 Wiley Periodicals, Inc.

  18. Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm.

    Science.gov (United States)

    Ting, Sie Chun; Ismail, A R; Malek, M A

    2013-11-15

    This study aims at developing a novel effluent removal management tool for septic sludge treatment plants (SSTP) using a clonal selection algorithm (CSA). The proposed CSA articulates the idea of utilizing an artificial immune system (AIS) to identify the behaviour of the SSTP, that is, using a sequence batch reactor (SBR) technology for treatment processes. The novelty of this study is the development of a predictive SSTP model for effluent discharge adopting the human immune system. Septic sludge from the individual septic tanks and package plants will be desuldged and treated in SSTP before discharging the wastewater into a waterway. The Borneo Island of Sarawak is selected as the case study. Currently, there are only two SSTPs in Sarawak, namely the Matang SSTP and the Sibu SSTP, and they are both using SBR technology. Monthly effluent discharges from 2007 to 2011 in the Matang SSTP are used in this study. Cross-validation is performed using data from the Sibu SSTP from April 2011 to July 2012. Both chemical oxygen demand (COD) and total suspended solids (TSS) in the effluent were analysed in this study. The model was validated and tested before forecasting the future effluent performance. The CSA-based SSTP model was simulated using MATLAB 7.10. The root mean square error (RMSE), mean absolute percentage error (MAPE), and correction coefficient (R) were used as performance indexes. In this study, it was found that the proposed prediction model was successful up to 84 months for the COD and 109 months for the TSS. In conclusion, the proposed CSA-based SSTP prediction model is indeed beneficial as an engineering tool to forecast the long-run performance of the SSTP and in turn, prevents infringement of future environmental balance in other towns in Sarawak. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers.

    Directory of Open Access Journals (Sweden)

    Elena Pereira

    Full Text Available High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools.Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival.Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential

  20. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers.

    Science.gov (United States)

    Pereira, Elena; Camacho-Vanegas, Olga; Anand, Sanya; Sebra, Robert; Catalina Camacho, Sandra; Garnar-Wortzel, Leopold; Nair, Navya; Moshier, Erin; Wooten, Melissa; Uzilov, Andrew; Chen, Rong; Prasad-Hayes, Monica; Zakashansky, Konstantin; Beddoe, Ann Marie; Schadt, Eric; Dottino, Peter; Martignetti, John A

    2015-01-01

    High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools. Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival. Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection

  1. Robust and predictive fuzzy key performance indicators for condition-based treatment of squats in railway infrastructures

    NARCIS (Netherlands)

    Jamshidi, A.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Li, Z.

    2017-01-01

    This paper presents a condition-based treatment methodology for a type of rail surface defect called squat. The proposed methodology is based on a set of robust and predictive fuzzy key performance indicators. A fuzzy Takagi-Sugeno interval model is used to predict squat evolution for different

  2. Accuracy of Dolphin visual treatment objective (VTO) prediction software on class III patients treated with maxillary advancement and mandibular setback.

    Science.gov (United States)

    Peterman, Robert J; Jiang, Shuying; Johe, Rene; Mukherjee, Padma M

    2016-12-01

    Dolphin® visual treatment objective (VTO) prediction software is routinely utilized by orthodontists during the treatment planning of orthognathic cases to help predict post-surgical soft tissue changes. Although surgical soft tissue prediction is considered to be a vital tool, its accuracy is not well understood in tow-jaw surgical procedures. The objective of this study was to quantify the accuracy of Dolphin Imaging's VTO soft tissue prediction software on class III patients treated with maxillary advancement and mandibular setback and to validate the efficacy of the software in such complex cases. This retrospective study analyzed the records of 14 patients treated with comprehensive orthodontics in conjunction with two-jaw orthognathic surgery. Pre- and post-treatment radiographs were traced and superimposed to determine the actual skeletal movements achieved in surgery. This information was then used to simulate surgery in the software and generate a final soft tissue patient profile prediction. Prediction images were then compared to the actual post-treatment profile photos to determine differences. Dolphin Imaging's software was determined to be accurate within an error range of +/- 2 mm in the X-axis at most landmarks. The lower lip predictions were most inaccurate. Clinically, the observed error suggests that the VTO may be used for demonstration and communication with a patient or consulting practitioner. However, Dolphin should not be useful for precise treatment planning of surgical movements. This program should be used with caution to prevent unrealistic patient expectations and dissatisfaction.

  3. Statistical monitoring and dynamic simulation of a wastewater treatment plant: A combined approach to achieve model predictive control.

    Science.gov (United States)

    Wang, Xiaodong; Ratnaweera, Harsha; Holm, Johan Abdullah; Olsbu, Vibeke

    2017-05-15

    The on-line monitoring of Chemical oxygen demand (COD) and total phosphorus (TP) restrains wastewater treatment plants to achieve better control of aeration and chemical dosing. In this study, we applied principal components analysis (PCA) to find out significant variables for COD and TP prediction. Multiple regression method applied the variables suggested by PCA to predict influent COD and TP. Moreover, a model of full-scale wastewater treatment plant with moving bed bioreactor (MBBR) and ballasted separation process was developed to simulate the performance of wastewater treatment. The predicted COD and TP data by multiple regression served as model input for dynamic simulation. Besides, the wastewater characteristic of the wastewater treatment plant and MBBR model parameters were given for model calibration. As a result, R2 of predicted COD and TP versus measured data are 81.6% and 77.2%, respectively. The model output in terms of sludge production and effluent COD based on predicted input data fitted measured data well, which provides possibility to enabled model predictive control of aeration and coagulant dosing in practice. This study provide a feasible and economical approach to overcome monitoring and modelling restrictions that limits model predictive control of wastewater treatment plant. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. The predictive value of trauma-related coping self-efficacy for posttraumatic stress symptoms : Differences between treatment seeking and non-treatment seeking victims

    NARCIS (Netherlands)

    Bosmans, Mark; van der Knaap, Leontien; van der Velden, Peter

    2015-01-01

    Objective: To assess and compare the (independent) predictive value of trauma-related coping selfefficacy (CSE) for posttraumatic stress symptoms (PTSS) among a treatment sample and a comparison group of nontreatment seeking victims. Method: Both the treatment (N 54) and comparison group (N 144)

  5. Nowcasting Mobile Games Ranking Using Web Search Query Data

    Directory of Open Access Journals (Sweden)

    Yoones A. Sekhavat

    2016-01-01

    Full Text Available In recent years, the Internet has become embedded into the purchasing decision of consumers. The purpose of this paper is to study whether the Internet behavior of users correlates with their actual behavior in computer games market. Rather than proposing the most accurate model for computer game sales, we aim to investigate to what extent web search query data can be exploited to nowcast (contraction of “now” and “forecasting” referring to techniques used to make short-term forecasts (predict the present status of the ranking of mobile games in the world. Google search query data is used for this purpose, since this data can provide a real-time view on the topics of interest. Various statistical techniques are used to show the effectiveness of using web search query data to nowcast mobile games ranking.

  6. Predicting the electric field distribution in the brain for the treatment of glioblastoma.

    Science.gov (United States)

    Miranda, Pedro C; Mekonnen, Abeye; Salvador, Ricardo; Basser, Peter J

    2014-08-07

    The use of alternating electric fields has been recently proposed for the treatment of recurrent glioblastoma. In order to predict the electric field distribution in the brain during the application of such tumor treating fields (TTF), we constructed a realistic head model from MRI data and placed transducer arrays on the scalp to mimic an FDA-approved medical device. Values for the tissue dielectric properties were taken from the literature; values for the device parameters were obtained from the manufacturer. The finite element method was used to calculate the electric field distribution in the brain. We also included a 'virtual lesion' in the model to simulate the presence of an idealized tumor. The calculated electric field in the brain varied mostly between 0.5 and 2.0 V cm( - 1) and exceeded 1.0 V cm( - 1) in 60% of the total brain volume. Regions of local field enhancement occurred near interfaces between tissues with different conductivities wherever the electric field was perpendicular to those interfaces. These increases were strongest near the ventricles but were also present outside the tumor's necrotic core and in some parts of the gray matter-white matter interface. The electric field values predicted in this model brain are in reasonably good agreement with those that have been shown to reduce cancer cell proliferation in vitro. The electric field distribution is highly non-uniform and depends on tissue geometry and dielectric properties. This could explain some of the variability in treatment outcomes. The proposed modeling framework could be used to better understand the physical basis of TTF efficacy through retrospective analysis and to improve TTF treatment planning.

  7. 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...

  8. Predicting the drying properties of sludge based on hydrothermal treatment under subcritical conditions.

    Science.gov (United States)

    Mäkelä, Mikko; Fraikin, Laurent; Léonard, Angélique; Benavente, Verónica; Fullana, Andrés

    2016-03-15

    The effects of hydrothermal treatment on the drying properties of sludge were determined. Sludge was hydrothermally treated at 180-260 °C for 0.5-5 h using NaOH and HCl as additives to influence reaction conditions. Untreated sludge and attained hydrochar samples were then dried under identical conditions with a laboratory microdryer and an X-ray microtomograph was used to follow changes in sample dimensions. The effective moisture diffusivities of sludge and hydrochar samples were determined and the effect of process conditions on respective mean diffusivities evaluated using multiple linear regression. Based on the results the drying time of untreated sludge decreased from approximately 80 min to 37-59 min for sludge hydrochar. Drying of untreated sludge was governed by the falling rate period where drying flux decreased continuously as a function of sludge moisture content due to heat and mass transfer limitations and sample shrinkage. Hydrothermal treatment increased the drying flux of sludge hydrochar and decreased the effect of internal heat and mass transfer limitations and sample shrinkage especially at higher treatment temperatures. The determined effective moisture diffusivities of sludge and hydrochar increased as a function of decreasing moisture content and the mean diffusivity of untreated sludge (8.56·10(-9) m(2) s(-1)) and sludge hydrochar (12.7-27.5·10(-9) m(2) s(-1)) were found statistically different. The attained regression model indicated that treatment temperature governed the mean diffusivity of hydrochar, as the effects of NaOH and HCl were statistically insignificant. The attained results enabled prediction of sludge drying properties through mean moisture diffusivity based on hydrothermal treatment conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Block models and personalized PageRank

    National Research Council Canada - National Science Library

    Kloumann, Isabel M; Ugander, Johan; Kleinberg, Jon

    2017-01-01

    ...? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in the space of "landing probabilities" of a random walk...

  10. Who's bigger? where historical figures really rank

    CERN Document Server

    Skiena, Steven

    2014-01-01

    Is Hitler bigger than Napoleon? Washington bigger than Lincoln? Picasso bigger than Einstein? Quantitative analysts are rapidly finding homes in social and cultural domains, from finance to politics. What about history? In this fascinating book, Steve Skiena and Charles Ward bring quantitative analysis to bear on ranking and comparing historical reputations. They evaluate each person by aggregating the traces of millions of opinions, just as Google ranks webpages. The book includes a technical discussion for readers interested in the details of the methods, but no mathematical or computational background is necessary to understand the rankings or conclusions. Along the way, the authors present the rankings of more than one thousand of history's most significant people in science, politics, entertainment, and all areas of human endeavor. Anyone interested in history or biography can see where their favorite figures place in the grand scheme of things.

  11. Ranking Forestry Investments With Parametric Linear Programming

    Science.gov (United States)

    Paul A. Murphy

    1976-01-01

    Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

  12. Superfund Hazard Ranking System Training Course

    Science.gov (United States)

    The Hazard Ranking System (HRS) training course is a four and ½ day, intermediate-level course designed for personnel who are required to compile, draft, and review preliminary assessments (PAs), site inspections (SIs), and HRS documentation records/packag

  13. Psychiatric comorbidity and aspects of cognitive coping negatively predict outcome in cognitive behavioral treatment of psychophysiological insomnia.

    Science.gov (United States)

    van de Laar, Merijn; Pevernagie, Dirk; van Mierlo, Petra; Overeem, Sebastiaan

    2015-01-01

    Cognitive behavioral treatment is the gold standard treatment for insomnia, although a substantial group does not respond. We examined possible predictors for treatment outcome in psychophysiological insomniacs, with a focus on the presence of clearly defined psychiatric comorbidity. This was a longitudinal uncontrolled case series study comprising 60 patients with chronic psychophysiological insomnia consecutively referred to a tertiary sleep medicine center, to receive cognitive behavioral treatment for insomnia (CBT-I). Remission of insomnia was defined as a posttreatment Insomnia Severity Index score below 8. As an alternative outcome, we used a clinically relevant decrease on the Insomnia Severity Index (drop of > 7 points). Personality, coping, and social support questionnaires were assessed before the start of the treatment and were compared between treatment responders and nonresponders. To examine whether these variables were predictive for negative treatment outcome, logistic regression analyses were applied. Treatment nonresponders had a significantly higher prevalence of psychiatric comorbidity. Logistic regression analyses showed that the presence of psychiatric comorbidity was strongly predictive for negative treatment outcome (odds ratios: 20.6 and 10.3 for the 2 outcome definitions). Additionally, higher scores on the cognitive coping strategy called "refocus on planning" were associated with worse CBT-I outcome. Current psychiatric comorbidity is strongly predictive for negative treatment outcome. The presence of a psychiatric disorder must therefore be one of the leading arguments in the choice of treatment modalities that are being proposed to patients with insomnia.

  14. Predicting client attendance at further treatment following drug and alcohol detoxification: Theory of Planned Behaviour and Implementation Intentions.

    Science.gov (United States)

    Kelly, Peter J; Leung, Joanne; Deane, Frank P; Lyons, Geoffrey C B

    2016-11-01

    Despite clinical recommendations that further treatment is critical for successful recovery following drug and alcohol detoxification, a large proportion of clients fail to attend treatment after detoxification. In this study, individual factors and constructs based on motivational and volitional models of health behaviour were examined as predictors of post-detoxification treatment attendance. The sample consisted of 220 substance-dependent individuals participating in short-term detoxification programs provided by The Australian Salvation Army. The Theory of Planned Behaviour and Implementation Intentions were used to predict attendance at subsequent treatment. Follow-up data were collected for 177 participants (81%), with 104 (80%) of those participants reporting that they had either attended further formal treatment (e.g. residential rehabilitation programs, outpatient counselling) or mutual support groups in the 2 weeks after leaving the detoxification program. Logistic regression examined the predictors of further treatment attendance. The full model accounted for 21% of the variance in treatment attendance, with attitude and Implementation Intentions contributing significantly to the prediction. Findings from the present study would suggest that assisting clients to develop a specific treatment plan, as well as helping clients to build positive perceptions about subsequent treatment, will promote greater attendance at further treatment following detoxification. [Kelly PJ, Leung J, Deane FP, Lyons GCB. Predicting client attendance at further treatment following drug and alcohol detoxification: Theory of Planned Behaviour and Implementation Intentions. Drug Alcohol Rev 2016;35:678-685]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

  15. The Predictive Role of Procalcitonin On the Treatment of Intra-Abdominal Infections

    Science.gov (United States)

    Mahmutaj, Dafina; Krasniqi, Shaip; Braha, Bedri; Limani, Dalip; Neziri, Burim

    2017-01-01

    AIM: This study aims to evaluate the algorithm of procalcitonin (PCT) and its role on the duration of antibiotics prescription for intra-abdominal infections. MATERIALS AND METHODS: This study is a prospective controlled study that is conducted in groups of 50 hospitalised patients and 50 controlled group patients. RESULTS: The results indicated that the average duration of antibiotic delivery to the PCT group was -10.6 days (SD ± 6.6 days), while in the control group -13.2 days (SD ± 4.2 days). These data showed a significant difference in the duration of antibiotic therapy and the monitoring role of PCTs in the prediction success of antibiotic treatment. The antibiotic delivery was longer in the septic shock 17 (SD ± 11.7) that corresponds to high PCT values of 67.8 (SD ± 50.9). Recurrence of the infection after the cessation of antibiotics occurred in 2 cases (4%) in the standard group, while it occurred in 3 cases (6%) in the control group. CONCLUSION: The treatment of the intra-abdominal infections based on the PCT algorithm shortens the duration of antibiotic treatment and does not pose a risk for the recurrence of the infection. PMID:29362617

  16. Prediction of post-treatment trismus in head and neck cancer patients.

    Science.gov (United States)

    Lee, R; Slevin, N; Musgrove, B; Swindell, R; Molassiotis, A

    2012-06-01

    Our aim was to establish the incidence of trismus over time, together with risk factors (including quality of life (QoL)) for the prediction of trismus after treatment in patients with cancer of the head and neck. It was a longitudinal study of 152 patients accepted for primary operation who attended the head and neck cancer clinic of a tertiary referral cancer centre in the United Kingdom. A total of 87 patients was studied prospectively. Our results showed that 41/87 (47%) of patients presented with trismus, 57/80 (71%) had postoperative trismus, and 41/52 (79%) had trismus 6 months after operation or radiotherapy (trismus defined as a maximum mouth opening of ≤ 35 mm). Men and those who drank a lot of alcohol were less likely to have trismus after treatment. QoL variables showed that pain, eating, chewing, taste, saliva, social functioning, social contact, and dry mouth were significantly more impaired in the trismus group than among those without trismus. Postoperative differences in QoL between the two groups highlighted problems with social function and role-playing, fatigue, activity, recreation, and overall reduction in QoL. Women, and those who do not drink alcohol, are at particularly high risk of developing trismus, and, to prevent it and treat it, patients may benefit from multidisciplinary management at an early stage during treatment. Copyright © 2011 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

  17. The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

    Directory of Open Access Journals (Sweden)

    Bradford A. Moffat

    2006-04-01

    Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

  18. Block models and personalized PageRank.

    Science.gov (United States)

    Kloumann, Isabel M; Ugander, Johan; Kleinberg, Jon

    2017-01-03

    Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods through the "seed set expansion problem": given a subset [Formula: see text] of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in the space of "landing probabilities" of a random walk rooted at the seed set, ranking nodes according to weighted sums of landing probabilities of different length walks. Both schemes, however, lack an a priori relationship to the seed set objective. In this work, we develop a principled framework for evaluating ranking methods by studying seed set expansion applied to the stochastic block model. We derive the optimal gradient for separating the landing probabilities of two classes in a stochastic block model and find, surprisingly, that under reasonable assumptions the gradient is asymptotically equivalent to personalized PageRank for a specific choice of the PageRank parameter [Formula: see text] that depends on the block model parameters. This connection provides a formal motivation for the success of personalized PageRank in seed set expansion and node ranking generally. We use this connection to propose more advanced techniques incorporating higher moments of landing probabilities; our advanced methods exhibit greatly improved performance, despite being simple linear classification rules, and are even competitive with belief propagation.

  19. Rank rigidity for CAT(0) cube complexes

    OpenAIRE

    Caprace, Pierre-Emmanuel; Sageev, Michah

    2010-01-01

    We prove that any group acting essentially without a fixed point at infinity on an irreducible finite-dimensional CAT(0) cube complex contains a rank one isometry. This implies that the Rank Rigidity Conjecture holds for CAT(0) cube complexes. We derive a number of other consequences for CAT(0) cube complexes, including a purely geometric proof of the Tits Alternative, an existence result for regular elements in (possibly non-uniform) lattices acting on cube complexes, and a characterization ...

  20. NUCLEAR POWER PLANTS SAFETY IMPROVEMENT PROJECTS RANKING

    OpenAIRE

    Григорян, Анна Сергеевна; Тигран Георгиевич ГРИГОРЯН; Квасневский, Евгений Анатольевич

    2013-01-01

    The ranking nuclear power plants safety improvement projects is the most important task for ensuring the efficiency of NPP project management office work. Total amount of projects in NPP portfolio may reach more than 400. Features of the nuclear power plants safety improvement projects ranking in NPP portfolio determine the choice of the decision verbal analysis as a method of decision-making, as it allows to quickly compare the number of alternatives that are not available at the time of con...

  1. Ranking Music Data by Relevance and Importance

    DEFF Research Database (Denmark)

    Ruxanda, Maria Magdalena; Nanopoulos, Alexandros; Jensen, Christian Søndergaard

    2008-01-01

    Due to the rapidly increasing availability of audio files on the Web, it is relevant to augment search engines with advanced audio search functionality. In this context, the ranking of the retrieved music is an important issue. This paper proposes a music ranking method capable of flexibly fusing...... the relevance and importance of music. The proposed method may support users with diverse needs when searching for music....

  2. Treatment of 817 patients with spontaneous supratentorial intracerebral hemorrhage: characteristics, predictive factors and outcome

    Directory of Open Access Journals (Sweden)

    Homajoun Maslehaty

    2012-05-01

    significant factors for worse outcome in the conservative group. The results of our study show that ICH remains a multifarious disease and challenges neurosurgeons repeatedly. Selection of the treatment modality and prediction for neurofunctional outcome underlies various parameters. Treatment recommendations of ICH remain an unsolved issue. The consideration of the GCS grade at admission is the most important predictive factor. Old age is not an absolute contraindication for surgery, but cumulative multi-morbidity, especially cerebrovascular and cardiovascular diseases and oral anticoagulant therapy should be regarded critically in view of surgical treatment.

  3. Rank distributions: A panoramic macroscopic outlook

    Science.gov (United States)

    Eliazar, Iddo I.; Cohen, Morrel H.

    2014-01-01

    This paper presents a panoramic macroscopic outlook of rank distributions. We establish a general framework for the analysis of rank distributions, which classifies them into five macroscopic "socioeconomic" states: monarchy, oligarchy-feudalism, criticality, socialism-capitalism, and communism. Oligarchy-feudalism is shown to be characterized by discrete macroscopic rank distributions, and socialism-capitalism is shown to be characterized by continuous macroscopic size distributions. Criticality is a transition state between oligarchy-feudalism and socialism-capitalism, which can manifest allometric scaling with multifractal spectra. Monarchy and communism are extreme forms of oligarchy-feudalism and socialism-capitalism, respectively, in which the intrinsic randomness vanishes. The general framework is applied to three different models of rank distributions—top-down, bottom-up, and global—and unveils each model's macroscopic universality and versatility. The global model yields a macroscopic classification of the generalized Zipf law, an omnipresent form of rank distributions observed across the sciences. An amalgamation of the three models establishes a universal rank-distribution explanation for the macroscopic emergence of a prevalent class of continuous size distributions, ones governed by unimodal densities with both Pareto and inverse-Pareto power-law tails.

  4. Hierarchical Rank Aggregation with Applications to Nanotoxicology.

    Science.gov (United States)

    Patel, Trina; Telesca, Donatello; Rallo, Robert; George, Saji; Xia, Tian; Nel, André E

    2013-06-01

    The development of high throughput screening (HTS) assays in the field of nanotoxicology provide new opportunities for the hazard assessment and ranking of engineered nanomaterials (ENMs). It is often necessary to rank lists of materials based on multiple risk assessment parameters, often aggregated across several measures of toxicity and possibly spanning an array of experimental platforms. Bayesian models coupled with the optimization of loss functions have been shown to provide an effective framework for conducting inference on ranks. In this article we present various loss-function-based ranking approaches for comparing ENM within experiments and toxicity parameters. Additionally, we propose a framework for the aggregation of ranks across different sources of evidence while allowing for differential weighting of this evidence based on its reliability and importance in risk ranking. We apply these methods to high throughput toxicity data on two human cell-lines, exposed to eight different nanomaterials, and measured in relation to four cytotoxicity outcomes. This article has supplementary material online.

  5. Predicting Dropout from a Residential Programme for Adolescent Sexual Abusers Using Pre-Treatment Variables and Implications for Recidivism

    Science.gov (United States)

    Edwards, Rachel; Beech, Anthony; Bishopp, Daz; Erikson, Matt; Friendship, Caroline; Charlesworth, Lucy

    2005-01-01

    This study addresses the prediction that dropout from a UK specialized residential treatment program for adolescent sexual abusers can be determined from pre-treatment variables. Participants were 49 adolescents aged 12-16 years, who had sexually abused children, peers/adults or both. Of the variables examined, 25 showed a significant association…

  6. Distinctive Facial Cues Predict Leadership Rank and Selection.

    Science.gov (United States)

    Re, Daniel E; Rule, Nicholas

    2017-09-01

    Facial appearance correlates with leadership, both in terms of who is chosen (leader selection) and how they do (leader success). Leadership theories suggest that exceptional individuals acquire positions as leaders. Exceptional traits can differ between domains, however, and so the qualities valued in leaders in one occupation may not match those valued among leaders in another. To test this, we compared the relationship between facial appearance and leadership across two domains: law firms and mafia families. Perceptions of power correlated with leadership among law executives whereas social skill correlated with leadership in organized crime. Critically, these traits were distinctive within their respective groups. Furthermore, an experimental test showed that the relative frequency of facial traits in a group can render them either an asset or liability. Perceived leadership ability is therefore enhanced by characteristics that appear unique among individuals who satisfy the basic criteria for their group.

  7. Dominance rank and boldness predict social attraction in great tits

    NARCIS (Netherlands)

    Snijders, Lysanne; Naguib, Marc; Oers, van Kees

    2017-01-01

    Social relationships can have important fitness consequences, and how well an individual is socially connected often correlates with other behavioral traits. Whether such correlations are caused by underlying individual differences in social attraction usually remains unclear, because to identify

  8. Greater hunger and less restraint predict weight loss success with phentermine treatment.

    Science.gov (United States)

    Thomas, Elizabeth A; Mcnair, Bryan; Bechtell, Jamie L; Ferland, Annie; Cornier, Marc-Andre; Eckel, Robert H

    2016-01-01

    Phentermine is thought to cause weight loss through a reduction in hunger. It was hypothesized that higher hunger ratings would predict greater weight loss with phentermine. This is an observational pilot study in which all subjects were treated with phentermine for 8 weeks and appetite and eating behaviors were measured at baseline and week 8. Outcomes were compared in subjects with ≥5% vs. hunger (P = 0.017), desire to eat (P =0.003), and prospective food consumption (0.006) and lower baseline cognitive restraint (P = 0.01). In addition, higher baseline home prospective food consumption (P = 0.002) and lower baseline cognitive restraint (P hunger and less restraint are more likely to achieve significant weight loss with phentermine. This information can be used clinically to determine who might benefit most from phentermine treatment. © 2015 The Obesity Society.

  9. Impact of Child Maltreatment on Attachment and Social Rank Systems: Introducing an Integrated Theory.

    Science.gov (United States)

    Sloman, Leon; Taylor, Peter

    2016-04-01

    Child maltreatment is a prevalent societal problem that has been linked to a wide range of social, psychological, and emotional difficulties. Maltreatment impacts on two putative evolved psychobiological systems in particular, the attachment system and the social rank system. The maltreatment may disrupt the child's ability to form trusting and reassuring relationships and also creates a power imbalance where the child may feel powerless and ashamed. The aim of the current article is to outline an evolutionary theory for understanding the impact of child maltreatment, focusing on the interaction between the attachment and the social rank system. We provide a narrative review of the relevant literature relating to child maltreatment and these two theories. This research highlights how, in instances of maltreatment, these ordinarily adaptive systems may become maladaptive and contribute to psychopathology. We identify a number of novel hypotheses that can be drawn from this theory, providing a guide for future research. We finally explore how this theory provides a guide for the treatment of victims of child maltreatment. In conclusion, the integrated theory provides a framework for understanding and predicting the consequences of maltreatment, but further research is required to test several hypotheses made by this theory. © The Author(s) 2015.

  10. ARWU vs. Alternative ARWU Ranking: What are the Consequences for Lower Ranked Universities?

    Directory of Open Access Journals (Sweden)

    Milica Maričić

    2017-05-01

    Full Text Available The ARWU ranking has been a source of academic debate since its development in 2003, but the same does not account for the Alternative ARWU ranking. Namely, the Alternative ARWU ranking attempts to reduce the influence of the prestigious indicators Alumni and Award which are based on the number of received Nobel Prizes and Fields Medals by alumni or university staff. However, the consequences of the reduction of the two indicators have not been scrutinized in detail. Therefore, we propose a statistical approach to the comparison of the two rankings and an in-depth analysis of the Alternative ARWU groups. The obtained results, which are based on the official data, can provide new insights into the nature of the Alternative ARWU ranking. The presented approach might initiate further research on the Alternative ARWU ranking and on the impact of university ranking’s list length. JEL Classification: C10, C38, I23

  11. Predictive factors for loco regional recurrence and distant metastasis following primary surgical treatment of cutaneous melanoma

    Directory of Open Access Journals (Sweden)

    Vijayalakshmi Deshmane

    2014-01-01

    Full Text Available Background: Cutaneous melanoma (CM has a high propensity for regional and systemic spread. This is one of the largest series of CM reported from India. Aims: To predict factors for loco regional recurrence (LRR and distant metastasis in patients with CM primarily treated with surgery. Study Design: Retrospective analysis of patient database at a tertiary care cancer center with evaluation of factors for LRR and distant metastasis for CM. Materials and Methods: Data from 68 patients treated for CM between January 2006 and December 2010 were reviewed. Data recorded included age, sex, symptoms, investigations, treatment given, histopathology, recurrence and follow-up. Patient factors, tumor factors, pathologic variables, and adjuvant treatment were investigated as predictors′ of LRR and distant metastasis. Results: Mean age of patients was 54 years. Melanoma was more common in males (44. Tumor thickness > 4 mm was found in 43 patients. Lymph node involvement was found in 43 patients. Adjuvant radiotherapy was given in seven patients. At mean follow-up of 16.5 months, LRR was seen in 34 patients and distant metastasis in 28 patients. LRR and distant metastasis were more commonly found in females, age > 40 years, Clark′s level IV and V, Breslow′s depth > 4 mm, patients with lymph node involvement and extra-capsular spread. Conclusion: The age, sex, site, thickness of lesion, involvement of lymph node, and extra-capsular spread were important factors in predicting LRR and distant metastasis. Distant metastasis was also more commonly found in patients with LRR.

  12. Molecular biomarkers predictive of sertraline treatment response in young children with fragile X syndrome.

    Science.gov (United States)

    AlOlaby, Reem Rafik; Sweha, Stefan R; Silva, Marisol; Durbin-Johnson, Blythe; Yrigollen, Carolyn M; Pretto, Dalyir; Hagerman, Randi J; Tassone, Flora

    2017-06-01

    Several neurotransmitters involved in brain development are altered in fragile X syndrome (FXS), the most common monogenic cause of autism spectrum disorder (ASD). Serotonin plays a vital role in synaptogenesis and postnatal brain development. Deficits in serotonin synthesis and abnormal neurogenesis were shown in young children with autism, suggesting that treating within the first years of life with a selective serotonin reuptake inhibitor might be the most effective time. In this study we aimed to identify molecular biomarkers involved in the serotonergic pathway that could predict the response to sertraline treatment in young children with FXS. Genotypes were determined for several genes involved in serotonergic pathway in 51 children with FXS, ages 24-72months. Correlations between genotypes and deviations from baseline in primary and secondary outcome measures were modeled using linear regression models. A significant association was observed between a BDNF polymorphism and improvements for several clinical measures, including the Clinical Global Impression scale (P=0.008) and the cognitive T score (P=0.017) in those treated with sertraline compared to those in the placebo group. Additionally, polymorphisms in the MAOA, Cytochrome P450 2C19 and 2D6, and in the 5-HTTLPR gene showed a significant correlation with some of the secondary measures included in this study. This study shows that polymorphisms of genes involved in the serotonergic pathway could play a potential role in predicting response to sertraline treatment in young children with FXS. Larger studies are warranted to confirm these initial findings. Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  13. Partial wave spectroscopic microscopy can predict prostate cancer progression and mitigate over-treatment (Conference Presentation)

    Science.gov (United States)

    Zhang, Di; Graff, Taylor; Crawford, Susan; Subramanian, Hariharan; Thompson, Sebastian; Derbas, Justin R.; Lyengar, Radha; Roy, Hemant K.; Brendler, Charles B.; Backman, Vadim

    2016-02-01

    Prostate Cancer (PC) is the second leading cause of cancer deaths in American men. While prostate specific antigen (PSA) test has been widely used for screening PC, >60% of the PSA detected cancers are indolent, leading to unnecessary clinical interventions. An alternative approach, active surveillance (AS), also suffer from high expense, discomfort and complications associated with repeat biopsies (every 1-3 years), limiting its acceptance. Hence, a technique that can differentiate indolent from aggressive PC would attenuate the harms from over-treatment. Combining microscopy with spectroscopy, our group has developed partial wave spectroscopic (PWS) microscopy, which can quantify intracellular nanoscale organizations (e.g. chromatin structures) that are not accessible by conventional microscopy. PWS microscopy has previously been shown to predict the risk of cancer in seven different organs (N ~ 800 patients). Herein we use PWS measurement of label-free histologically-normal prostatic epithelium to distinguish indolent from aggressive PC and predict PC risk. Our results from 38 men with low-grade PC indicated that there is a significant increase in progressors compared to non-progressors (p=0.002, effect size=110%, AUC=0.80, sensitivity=88% and specificity=72%), while the baseline clinical characteristics were not significantly different. We further improved the diagnostic power by performing nuclei-specific measurements using an automated system that separates in real-time the cell nuclei from the remaining prostate epithelium. In the long term, we envision that the PWS based prognostication can be coupled with AS without any change to the current procedure to mitigate the harms caused by over-treatment.

  14. External validation of the ability of the DRAGON score to predict outcome after thrombolysis treatment.

    Science.gov (United States)

    Ovesen, C; Christensen, A; Nielsen, J K; Christensen, H

    2013-11-01

    Easy-to-perform and valid assessment scales for the effect of thrombolysis are essential in hyperacute stroke settings. Because of this we performed an external validation of the DRAGON scale proposed by Strbian et al. in a Danish cohort. All patients treated with intravenous recombinant plasminogen activator between 2009 and 2011 were included. Upon admission all patients underwent physical and neurological examination using the National Institutes of Health Stroke Scale along with non-contrast CT scans and CT angiography. Patients were followed up through the Outpatient Clinic and their modified Rankin Scale (mRS) was assessed after 3 months. Three hundred and three patients were included in the analysis. The DRAGON scale proved to have a good discriminative ability for predicting highly unfavourable outcome (mRS 5-6) (area under the curve-receiver operating characteristic [AUC-ROC]: 0.89; 95% confidence interval [CI] 0.81-0.96; pDRAGON scale provided good discriminative capability (AUC-ROC: 0.89; 95% CI 0.78-1.0; p=0.003) for highly unfavourable outcome. We confirmed the validity of the DRAGON scale in predicting outcome after thrombolysis treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Prediction analysis of effluent removal in a septic sludge treatment plant: a biomimetics engineering approach.

    Science.gov (United States)

    Chun, Ting Sie; Malek, M A; Ismail, Amelia Ritahani

    2014-09-20

    Effluent discharge from septic tanks is affecting the environment in developing countries. The most challenging issue facing these countries is the cost of inadequate sanitation, which includes significant economic, social, and environmental burdens. Although most sanitation facilities are evaluated based on their immediate costs and benefits, their long-term performance should also be investigated. In this study, effluent quality-namely, the biological oxygen demand (BOD), chemical oxygen demand (COD), and total suspended solid (TSS)-was assessed using a biomimetics engineering approach. A novel immune network algorithm (INA) approach was applied to a septic sludge treatment plant (SSTP) for effluent-removal predictive modelling. The Matang SSTP in the city of Kuching, Sarawak, on the island of Borneo, was selected as a case study. Monthly effluent discharges from 2007 to 2011 were used for training, validating, and testing purposes using MATLAB 7.10. The results showed that the BOD effluent-discharge prediction was less than 50% of the specified standard after the 97(th) month of operation. The COD and TSS effluent removals were simulated at the 85(th) and the 121(st) months, respectively. The study proved that the proposed INA-based SSTP model could be used to achieve an effective SSTP assessment and management technique.

  16. Predictive value of self-reported and observer-rated defense style in depression treatment.

    Science.gov (United States)

    Van Henricus, L; Dekker, Jack; Peen, Jaap; Abraham, Robert E; Schoevers, Robert

    2009-01-01

    This study explored the predictive value of observer-rated and self-reported defensive functioning on the outcome of psychotherapy for the treatment of depression. Defense styles were measured according to the Developmental Profile (DP) and the Defense Style Questionnaire (DSQ) in 81 moderately severely depressed patients. All patients were treated with Short-term Psychodynamic Supportive Psychotherapy (SPSP). At baseline, women appeared to have a more mature level of overall defensive functioning. A lower level of defensive function was found in patients with recurrent depressions. We also found a rather modest relationship between self-reported and observer-rated defense. Remitted patients had a more mature overall defensive functioning on the DP and the DSQ. In particular, patients with a symbiotic defense style (giving up, apathetic withdrawal) were at risk for poor outcome. This exploratory study provides further evidence of the relevance of defense styles for depression. It suggests a differential predictive value of separate defense levels, which may help to tailor psychotherapeutic strategies.

  17. Personality Pathology Predicts Outcomes in a Treatment-Seeking Sample with Bipolar I Disorder

    Directory of Open Access Journals (Sweden)

    Susan J. Wenze

    2014-01-01

    Full Text Available We conducted a secondary analysis of data from a clinical trial to explore the relationship between degree of personality disorder (PD pathology (i.e., number of subthreshold and threshold PD symptoms and mood and functioning outcomes in Bipolar I Disorder (BD-I. Ninety-two participants completed baseline mood and functioning assessments and then underwent 4 months of treatment for an index manic, mixed, or depressed phase acute episode. Additional assessments occurred over a 28-month follow-up period. PD pathology did not predict psychosocial functioning or manic symptoms at 4 or 28 months. However, it did predict depressive symptoms at both timepoints, as well as percent time symptomatic. Clusters A and C pathology were most strongly associated with depression. Our findings fit with the literature highlighting the negative repercussions of PD pathology on a range of outcomes in mood disorders. This study builds upon previous research, which has largely focused on major depression and which has primarily taken a categorical approach to examining PD pathology in BD.

  18. PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB.

    Science.gov (United States)

    Jahandideh, Samad; Sharifi, Fatemeh; Jaroszewski, Lukasz; Godzik, Adam

    2015-01-01

    One of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research. To meet these demands we developed PROPER - a package for visual evaluation of ranking classifiers for biological big data mining studies in the MATLAB environment. PROPER is an efficient tool for optimization and comparison of ranking classifiers, providing over 20 different two- and three-dimensional performance curves.

  19. Rapidity-Rank Structure of $p\\overline{p}$ Pairs in Hadronic $Z^{0}$ Decays

    CERN Document Server

    Abreu, P.; Adye, T.; Adzic, P.; Azhinenko, I.; Albrecht, Z.; Alderweireld, T.; Alekseev, G.D.; Alemany, R.; Allmendinger, T.; Allport, P.P.; Almehed, S.; Amaldi, U.; Amapane, N.; Amato, S.; Anassontzis, E.G.; Andersson, P.; Andreazza, A.; Andringa, S.; Antilogus, P.; Apel, W.D.; Arnoud, Y.; Asman, B.; Augustin, J.E.; Augustinus, A.; Baillon, P.; Bambade, P.; Barao, F.; Barbiellini, G.; Barbier, R.; Bardin, D.Yu.; Barker, G.J.; Baroncelli, A.; Battaglia, M.; Baubillier, M.; Becks, K.H.; Begalli, M.; Behrmann, A.; Beilliere, P.; Belokopytov, Yu.; Benekos, N.C.; Benvenuti, A.C.; Berat, C.; Berggren, M.; Bertrand, D.; Besancon, M.; Bigi, M.; Bilenky, Mikhail S.; Bizouard, M.A.; Bloch, D.; Blom, H.M.; Bonesini, M.; Boonekamp, M.; Booth, P.S.L.; Borgland, A.W.; Borisov, G.; Bosio, C.; Botner, O.; Boudinov, E.; Bouquet, B.; Bourdarios, C.; Bowcock, T.J.V.; Boyko, I.; Bozovic, I.; Bozzo, M.; Bracko, M.; Branchini, P.; Brenner, R.A.; Bruckman, P.; Brunet, J.M.; Bugge, L.; Buran, T.; Buschbeck, B.; Buschmann, P.; Cabrera, S.; Caccia, M.; Calvi, M.; Camporesi, T.; Canale, V.; Carena, F.; Carroll, L.; Caso, C.; Castillo Gimenez, M.V.; Cattai, A.; Cavallo, F.R.; Chabaud, V.; Charpentier, P.; Checchia, P.; Chelkov, G.A.; Chierici, R.; Shlyapnikov, P.; Chochula, P.; Chorowicz, V.; Chudoba, J.; Cieslik, K.; Collins, P.; Contri, R.; Cortina, E.; Cosme, G.; Cossutti, F.; Crawley, H.B.; Crennell, D.; Crepe-Renaudin, Sabine; Crosetti, G.; Cuevas Maestro, J.; Czellar, S.; Davenport, M.; Da Silva, W.; Della Ricca, G.; Delpierre, P.; Demaria, N.; De Angelis, A.; De Boer, W.; De Clercq, C.; De Lotto, B.; De Min, A.; De Paula, L.; Dijkstra, H.; Di Ciaccio, L.; Dolbeau, J.; Doroba, K.; Dracos, M.; Drees, J.; Dris, M.; Duperrin, A.; Durand, J.D.; Eigen, G.; Ekelof, T.; Ekspong, G.; Ellert, M.; Elsing, M.; Engel, J.P.; Espirito Santo, M.C.; Fanourakis, G.; Fassouliotis, D.; Fayot, J.; Feindt, M.; Ferrer, A.; Ferrer-Ribas, E.; Ferro, F.; Fichet, S.; Firestone, A.; Flagmeyer, U.; Foeth, H.; Fokitis, E.; Fontanelli, F.; Franek, B.; Frodesen, A.G.; Fruhwirth, R.; Fulda-Quenzer, F.; Fuster, J.; Galloni, A.; Gamba, D.; Gamblin, S.; Gandelman, M.; Garcia, C.; Gaspar, C.; Gaspar, M.; Gasparini, U.; Gavillet, P.; Gazis, Evangelos; Gele, D.; Gerdyukov, L.; Ghodbane, N.; Gil Botella, Ines; Glege, F.; Gokieli, R.; Golob, B.; Gomez-Ceballos, G.; Goncalves, P.; Gonzalez Caballero, I.; Gopal, G.; Gorn, L.; Gracco, V.; Grahl, J.; Graziani, E.; Gris, P.; Grosdidier, G.; Grzelak, K.; Guy, J.; Haag, C.; Hahn, F.; Hahn, S.; Haider, S.; Hallgren, A.; Hamacher, K.; Hansen, J.; Harris, F.J.; Hedberg, V.; Heising, S.; Hernandez, J.J.; Herquet, P.; Herr, H.; Hessing, T.L.; Heuser, J.M.; Higon, E.; Holmgren, S.O.; Holt, P.J.; Hoorelbeke, S.; Houlden, M.; Hrubec, J.; Huber, M.; Huet, K.; Hughes, G.J.; Hultqvist, K.; Jackson, John Neil; Jacobsson, R.; Jalocha, P.; Janik, R.; Jarlskog, C.; Jarlskog, G.; Jarry, P.; Jean-Marie, B.; Jeans, D.; Johansson, Erik Karl; Jonsson, P.; Joram, C.; Juillot, P.; Jungermann, L.; Kapusta, Frederic; Karafasoulis, K.; Katsanevas, S.; Katsoufis, E.C.; Keranen, R.; Kernel, G.; Kersevan, B.P.; Khokhlov, Yu.A.; Khomenko, B.A.; Khovansky, N.N.; Kiiskinen, A.; King, B.; Kinvig, A.; Kjaer, N.J.; Klapp, O.; Klein, Hansjorg; Kluit, P.; Kokkinias, P.; Kostyukhin, V.; Kourkoumelis, C.; Kuznetsov, O.; Krammer, M.; Kriznic, E.; Krumshtein, Z.; Kubinec, P.; Kurowska, J.; Kurvinen, K.; Lamsa, J.W.; Lane, D.W.; Lapin, V.; Laugier, J.P.; Lauhakangas, R.; Leder, G.; Ledroit, Fabienne; Lefebure, V.; Leinonen, L.; Leisos, A.; Leitner, R.; Lemonne, J.; Lenzen, G.; Lepeltier, V.; Lesiak, T.; Lethuillier, M.; Libby, J.; Liebig, W.; Liko, D.; Lipniacka, A.; Lippi, I.; Lorstad, B.; Loken, J.G.; Lopes, J.H.; Lopez, J.M.; Lopez-Fernandez, R.; Loukas, D.; Lutz, P.; Lyons, L.; MacNaughton, J.; Mahon, J.R.; Maio, A.; Malek, A.; Malmgren, T.G.M.; Maltezos, S.; Malychev, V.; Mandl, F.; Marco, J.; Marco, R.; Marechal, B.; Margoni, M.; Marin, J.C.; Mariotti, C.; Markou, A.; Martinez-Rivero, C.; Martinez-Vidal, F.; Marti i Garcia, S.; Masik, J.; Mastroyiannopoulos, N.; Matorras, F.; Matteuzzi, C.; Matthiae, G.; Mazzucato, F.; Mazzucato, M.; McCubbin, M.; McKay, R.; McNulty, R.; McPherson, G.; Meroni, C.; Meyer, W.T.; Myagkov, A.; Migliore, E.; Mirabito, L.; Mitaroff, W.A.; Mjornmark, U.; Moa, T.; Moch, M.; Moller, Rasmus; Monig, Klaus; Monge, M.R.; Moraes, D.; Moreau, X.; Morettini, P.; Morton, G.; Muller, U.; Munich, K.; Mulders, M.; Mulet-Marquis, C.; Muresan, R.; Murray, W.J.; Muryn, B.; Myatt, G.; Myklebust, T.; Naraghi, F.; Nassiakou, M.; Navarria, F.L.; Navas, Sergio; Nawrocki, K.; Negri, P.; Neufeld, N.; Nicolaidou, R.; Nielsen, B.S.; Niezurawski, P.; Nikolenko, M.; Nomokonov, V.; Nygren, A.; Obraztsov, V.; Olshevsky, A.G.; Onofre, A.; Orava, R.; Orazi, G.; Osterberg, K.; Ouraou, A.; Paganoni, M.; Paiano, S.; Pain, R.; Paiva, R.; Palacios, J.; Palka, H.; Papadopoulou, T.D.; Papageorgiou, K.; Pape, L.; Parkes, C.; Parodi, F.; Parzefall, U.; Passeri, A.; Passon, O.; Pavel, T.; Pegoraro, M.; Peralta, L.; Pernicka, M.; Perrotta, A.; Petridou, C.; Petrolini, A.; Phillips, H.T.; Pierre, F.; Pimenta, M.; Piotto, E.; Podobnik, T.; Pol, M.E.; Polok, G.; Poropat, P.; Pozdnyakov, V.; Privitera, P.; Pukhaeva, N.; Pullia, A.; Radojicic, D.; Ragazzi, S.; Rahmani, H.; Rames, J.; Ratoff, P.N.; Read, Alexander L.; Rebecchi, P.; Redaelli, Nicola Giuseppe; Regler, M.; Rehn, J.; Reid, D.; Reinhardt, R.; Renton, P.B.; Resvanis, L.K.; Richard, F.; Ridky, J.; Rinaudo, G.; Ripp-Baudot, Isabelle; Rohne, O.; Romero, A.; Ronchese, P.; Rosenberg, E.I.; Rosinsky, P.; Roudeau, P.; Rovelli, T.; Royon, C.; Ruhlmann-Kleider, V.; Ruiz, A.; Saarikko, H.; Sacquin, Y.; Sadovsky, A.; Sajot, G.; Salt, J.; Sampsonidis, D.; Sannino, M.; Schwemling, P.; Schwering, B.; Schwickerath, U.; Scuri, Fabrizio; Seager, P.; Sedykh, Yu.; Segar, A.M.; Seibert, N.; Sekulin, R.; Shellard, R.C.; Siebel, M.; Simard, L.; Simonetto, F.; Sisakian, A.N.; Smadja, G.; Smirnov, N.; Smirnova, O.; Smith, G.R.; Sokolov, A.; Sopczak, A.; Sosnowski, R.; Spassoff, T.; Spiriti, E.; Squarcia, S.; Stanescu, C.; Stanic, S.; Stanitzki, M.; Stevenson, K.; Stocchi, A.; Strauss, J.; Strub, R.; Stugu, B.; Szczekowski, M.; Szeptycka, M.; Tabarelli, T.; Taffard, A.; Tegenfeldt, F.; Terranova, F.; Thomas, J.; Timmermans, Jan; Tinti, N.; Tkachev, L.G.; Tobin, M.; Todorova, S.; Tomaradze, A.; Tome, B.; Tonazzo, A.; Tortora, L.; Tortosa, P.; Transtromer, G.; Treille, D.; Tristram, G.; Trochimczuk, M.; Troncon, C.; Turluer, M.L.; Tyapkin, I.A.; Tzamarias, S.; Ullaland, O.; Uvarov, V.; Valenti, G.; Vallazza, E.; Van Dam, Piet; Van den Boeck, W.; Van Eldik, J.; Van Lysebetten, A.; Van Remortel, N.; Van Vulpen, I.; Vegni, G.; Ventura, L.; Venus, W.; Verbeure, F.; Verdier, P.; Verlato, M.; Vertogradov, L.S.; Verzi, V.; Vilanova, D.; Vitale, L.; Vlasov, E.; Vodopianov, A.S.; Voulgaris, G.; Vrba, V.; Wahlen, H.; Walck, C.; Washbrook, A.J.; Weiser, C.; Wicke, D.; Wickens, J.H.; Wilkinson, G.R.; Winter, M.; Witek, M.; Wolf, G.; Yi, J.; Yushchenko, O.; Zalewska, A.; Zalewski, P.; Zavrtanik, D.; Zevgolatakos, E.; Zimine, N.I.; Zinchenko, A.; Zoller, P.; Zucchelli, G.C.; Zumerle, G.

    2000-01-01

    The rapidity-rank structure of \\ppb pairs is used to analyze the mechanism of baryon production in hadronic \\zz decay. The relative occurrence of the rapidity-ordered configuration \\pmpb, where $M$ is a meson, and that of \\ppb adjacent pairs is compared. The data are found to be consistent with predictions from a mechanism producing adjacent-rank \\ppb pairs, without requiring `string-ordered' \\pmpb configurations. An upper limit of 15\\% at 90\\% confidence is determined for the \\pmpb contribution.

  20. An alternative methodology for the prediction of adherence to anti HIV treatment

    Directory of Open Access Journals (Sweden)

    Denholm-Price James CW

    2009-06-01

    important feature of treatment prediction tools provided for practitioners to aid daily practice. In addition, distinct characteristics of biological markers routinely used to assess the state of the disease may be identified in the adherent and non-adherent groups. This latter approach would directly help clinicians to differentiate between non-responding and non-adherent patients.

  1. Efficient Top-k Search for PageRank

    National Research Council Canada - National Science Library

    Fujiwara, Yasuhiro; Nakatsuji, Makoto; Shiokawa, Hiroaki; Mishima, Takeshi; Onizuka, Makoto

    2015-01-01

      In AI communities, many applications utilize PageRank. To obtain high PageRank score nodes, the original approach iteratively computes the PageRank score of each node until convergence from the whole graph...

  2. Network-based survival analysis reveals subnetwork signatures for predicting outcomes of ovarian cancer treatment.

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    Full Text Available Cox regression is commonly used to predict the outcome by the time to an event of interest and in addition, identify relevant features for survival analysis in cancer genomics. Due to the high-dimensionality of high-throughput genomic data, existing Cox models trained on any particular dataset usually generalize poorly to other independent datasets. In this paper, we propose a network-based Cox regression model called Net-Cox and applied Net-Cox for a large-scale survival analysis across multiple ovarian cancer datasets. Net-Cox integrates gene network information into the Cox's proportional hazard model to explore the co-expression or functional relation among high-dimensional gene expression features in the gene network. Net-Cox was applied to analyze three independent gene expression datasets including the TCGA ovarian cancer dataset and two other public ovarian cancer datasets. Net-Cox with the network information from gene co-expression or functional relations identified highly consistent signature genes across the three datasets, and because of the better generalization across the datasets, Net-Cox also consistently improved the accuracy of survival prediction over the Cox models regularized by L(2 or L(1. This study focused on analyzing the death and recurrence outcomes in the treatment of ovarian carcinoma to identify signature genes that can more reliably predict the events. The signature genes comprise dense protein-protein interaction subnetworks, enriched by extracellular matrix receptors and modulators or by nuclear signaling components downstream of extracellular signal-regulated kinases. In the laboratory validation of the signature genes, a tumor array experiment by protein staining on an independent patient cohort from Mayo Clinic showed that the protein expression of the signature gene FBN1 is a biomarker significantly associated with the early recurrence after 12 months of the treatment in the ovarian cancer patients who are

  3. PageRank as a method to rank biomedical literature by importance.

    Science.gov (United States)

    Yates, Elliot J; Dixon, Louise C

    2015-01-01

    Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

  4. RANK/RANK-Ligand/OPG: Ein neuer Therapieansatz in der Osteoporosebehandlung

    Directory of Open Access Journals (Sweden)

    Preisinger E

    2007-01-01

    Full Text Available Die Erforschung der Kopplungsmechanismen zur Osteoklastogenese, Knochenresorption und Remodellierung eröffnete neue mögliche Therapieansätze in der Behandlung der Osteoporose. Eine Schlüsselrolle beim Knochenabbau spielt der RANK- ("receptor activator of nuclear factor (NF- κB"- Ligand (RANKL. Durch die Bindung von RANKL an den Rezeptor RANK wird die Knochenresorption eingeleitet. OPG (Osteoprotegerin sowie der für den klinischen Gebrauch entwickelte humane monoklonale Antikörper (IgG2 Denosumab blockieren die Bindung von RANK-Ligand an RANK und verhindern den Knochenabbau.

  5. Treatment success in neck pain: The added predictive value of psychosocial variables in addition to clinical variables.

    Science.gov (United States)

    Groeneweg, Ruud; Haanstra, Tsjitske; Bolman, Catherine A W; Oostendorp, Rob A B; van Tulder, Maurits W; Ostelo, Raymond W J G

    2017-01-01

    Identification of psychosocial variables may influence treatment outcome. The objective of this study was to prospectively examine whether psychosocial variables, in addition to clinical variables (pain, functioning, general health, previous neck pain, comorbidity), are predictive factors for treatment outcome (i.e. global perceived effect, functioning and pain) in patients with sub-acute and chronic non-specific neck pain undergoing physical therapy or manual therapy. Psychosocial factors included treatment outcome expectancy and treatment credibility, health locus of control, and fear avoidance beliefs. This study reports a secondary analysis of a primary care-based pragmatic randomized controlled trial. Potential predictors were measured at baseline and outcomes, in 181 patients, at 7 weeks and 26 weeks. Hierarchical logistic regression models showed that treatment outcome expectancy predicted outcome success, in addition to clinical and demographic variables. Expectancy explained additional variance, ranging from 6% (pain) to 17% (functioning) at 7 weeks, and 8% (pain) to 16% (functioning) at 26 weeks. Locus of control and fear avoidance beliefs did not add significantly to predicting outcome. Based on the results of this study we conclude that outcome expectancy, in patients with non-specific sub-acute and chronic neck pain, has additional predictive value for treatment success above and beyond clinical and demographic variables. Psychological processes, health perceptions and how these factors relate to clinical variables may be important for treatment decision making regarding therapeutic options for individual patients. Copyright © 2016 Scandinavian Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  6. Prediction of Treatment Response to Donepezil using Automated Hippocampal Subfields Volumes Segmentation in Patients with Mild Alzheimer's Disease.

    Science.gov (United States)

    Um, Yoo Hyun; Kim, Tae-Won; Jeong, Jong-Hyun; Seo, Ho-Jun; Han, Jin-Hee; Hong, Seung-Chul; Lee, Chang-Uk; Lim, Hyun Kook

    2017-09-01

    Previous studies reported some relationships between donepezil treatment and hippocampus in Alzheimer's disease (AD). However, due to methodological limitations, their close relationships remain unclear. The aim of this study is to predict treatment response to donepezil by utilizing the automated segmentation of hippocampal subfields volumes (ASHS) in AD. Sixty four AD patients were prescribed with donepezil and were followed up for 24 weeks. Cognitive function was measured to assess whether there was a response from the donepezil treatment. ASHS was implemented on non-responder (NR) and responder (TR) groups, and receiver operator characteristic (ROC) analysis was conducted to evaluate the sensitivity, specificity, and accuracy of hippocampal subfields in predicting response to donepezil. The left total hippocampus and the CA1 area of the NR were significantly smaller than those of the TR group. The ROC curve analysis showed the left CA1 volumes showed highest area under curve (AUC) of 0.85 with a sensitivity of 88.0%, a specificity of 74.0% in predicting treatment response to donepezil treatment. We expect that hippocampal subfields volume measurements that predict treatment responses to current AD drugs will enable more evidence-based, individualized prescription of medications that will lead to more favorable treatment outcomes.

  7. Risk Factors Predicting Colorectal Cancer Recurrence Following Initial Treatment: A 5-year Cohort Study

    Science.gov (United States)

    Zare-Bandamiri, Mohammad; Fararouei, Mohammad; Zohourinia, Shadi; Daneshi, Nima; Dianatinasab, Mostafa

    2017-09-27

    Purpose: Recurrence is one of the most important factors influencing survival of colorectal cancer patients. Subjects and Methods: In this cohort study, clinical and demographic characteristics of 561 patients with colorectal cancer were collected from 2010 to 2015. Medical records and telephone interviews were used to define the patient’s clinical status including the date of any recurrence during the study period. The multivariate Cox model was used as the main strategy for analyzing data. Results: Some 239 (42.6%) patients experienced cancer recurrence during the 5-year follow-up period. Those with an older age at diagnosis had a higher risk of cancer recurrence than their younger counterparts [Hazard Ratio (HR) >70 y /<50 y= 1.65, P=0.01]. Rectal cancer had a greater risk of disease recurrence compared with other tumor sites [HR colon/ rectum=1.53, P=0.02]. Stage 3 cancer had a higher risk than stage 1 cancer [HR stage 3/ stage 1=4.30, P<0.001], and positive lympho-vascular invasion was also a risk factor [HR yes/ no=2.03, P<0.001]. Finally, tumor size , number of dissected lymph nodes, proportion of positive lymph nodes, perineural invasion and type of treatment did not significantly predict recurrence. Conclusion: Access to enhanced medical services including cancer diagnosis at an early stage and optimal treatment is needed to improve the survival and quality of life of CRC patients. Creative Commons Attribution License

  8. Paving the way for predictive diagnostics and personalized treatment of invasive aspergillosis

    Directory of Open Access Journals (Sweden)

    Ana eOliveira-Coelho

    2015-05-01

    Full Text Available Invasive aspergillosis (IA is a life-threatening fungal disease commonly diagnosed among individuals with immunological deficits, namely hematological patients undergoing chemotherapy or allogeneic hematopoietic stem cell transplantation. Vaccines are not available, and despite the improved diagnosis and antifungal therapy, the treatment of IA is associated with a poor outcome. Importantly, the risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and microbiological exposure. Recent insights into antifungal immunity have further highlighted the complexity of host-fungus interactions and the multiple pathogen-sensing systems activated to control infection. How to decode this information into clinical practice remains however a challenging issue in medical mycology. Here, we address recent advances in our understanding of the host-fungus interaction and discuss the application of this knowledge in potential strategies with the aim of moving towards personalized diagnostics and treatment (theragnostics in immunocompromised patients. Ultimately, the integration of individual traits into a clinically applicable process to predict the risk and progression of disease, and the efficacy of antifungal prophylaxis and therapy, holds the promise of a pioneering innovation benefiting patients at risk of IA.

  9. Online working alliance predicts treatment outcome for posttraumatic stress symptoms in Arab war-traumatized patients.

    Science.gov (United States)

    Wagner, Birgit; Brand, Janine; Schulz, Wassima; Knaevelsrud, Christine

    2012-07-01

    Previous studies have shown that Internet-based interventions for posttraumatic stress disorder are feasible. However, little is known about how therapeutic process factors impact online interventions in war and conflict regions. This study aims to assess the quality of the working alliance at midtreatment and posttreatment and its relationship with therapy outcome in an Internet-based cognitive-behavioral intervention for Arabic-speaking traumatized patients. A trial was conducted from January 2009 to August 2011 with patients recruited specifically in Iraq. Fifty-five participants with posttraumatic stress symptoms completed the Working Alliance Inventory (WAI) after at least session 4. Participants' mean age was 27.7 years (SD = 6.9); 78% of participants were females. Participants received two weekly 45-min Internet-based cognitive-behavioral interventions over a 5-week period. The main outcome measures were the Posttraumatic Diagnostic Scale (PDS) and the WAI. High ratings of the therapeutic alliance were obtained early in treatment, and results remained stable from sessions 4 to 10, indicating that it was possible to establish a positive and stable online therapeutic relationship. The working alliance at both assessment points predicted treatment outcome for posttraumatic stress symptoms. Despite the instability of the settings and patients' ongoing exposure to human right violations through war and dictatorships, it was possible to establish a stable online therapeutic relationship. © 2012 Wiley Periodicals, Inc.

  10. Ranking competitors using degree-neutralized random walks.

    Science.gov (United States)

    Shin, Seungkyu; Ahnert, Sebastian E; Park, Juyong

    2014-01-01

    Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win-loss differential method in sparse networks.

  11. Ranking competitors using degree-neutralized random walks.

    Directory of Open Access Journals (Sweden)

    Seungkyu Shin

    Full Text Available Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win-loss differential method in sparse networks.

  12. Ranking Fuzzy Numbers and Its Application to Products Attributes Preferences

    OpenAIRE

    Abdullah, Lazim; Fauzee, Nor Nashrah Ahmad

    2011-01-01

    Ranking is one of the widely used methods in fuzzy decision making environment. The recent ranking fuzzy numbers proposed by Wang and Li is claimed to be the improved version in ranking. However, the method was never been simplified and tested in real life application. This paper presents a four-step computation of ranking fuzzy numbers and its application in ranking attributes of selected chocolate products. The four steps algorithm was formulated to rank fuzzy numbers and followed by a tes...

  13. Fc-gamma receptor polymorphisms as predictive and prognostic factors in patients receiving oncolytic adenovirus treatment

    Science.gov (United States)

    2013-01-01

    Background Oncolytic viruses have shown potential as cancer therapeutics, but not all patients seem to benefit from therapy. Polymorphisms in Fc gamma receptors (FcgRs) lead to altered binding affinity of IgG between the receptor allotypes and therefore contribute to differences in immune defense mechanisms. Associations have been identified between FcgR polymorphisms and responsiveness to different immunotherapies. Taken together with the increasing understanding that immunological factors might determine the efficacy of oncolytic virotherapy we studied whether FcgR polymorphisms would have prognostic and/or predictive significance in the context of oncolytic adenovirus treatments. Methods 235 patients with advanced solid tumors were genotyped for two FcgR polymorphisms, FcgRIIa-H131R (rs1801274) and FcgRIIIa-V158F (rs396991), using TaqMan based qPCR. The genotypes were correlated with patient survival and tumor imaging data. Results In patients treated with oncolytic adenoviruses, overall survival was significantly shorter if the patient had an FcgRIIIa-VV/ FcgRIIa-HR (VVHR) genotype combination (P = 0,032). In contrast, patients with FFHR and FFRR genotypes had significantly longer overall survival (P = 0,004 and P = 0,006, respectively) if they were treated with GM-CSF-armed adenovirus in comparison to other viruses. Treatment of these patients with unarmed virus correlated with shorter survival (P treatment with other viruses (P = 0,047). Conclusions Our data are compatible with the hypothesis that individual differences in effector cell functions, such as NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC) and tumor antigen presentation by APCs caused by polymorphisms in FcgRs could play role in the effectiveness of oncolytic virotherapies. If confirmed in larger populations, FcgR polymorphisms could have potential as prognostic and predictive biomarkers for oncolytic adenovirus therapies to enable better selection of patients

  14. Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data.

    Science.gov (United States)

    Munsell, Brent C; Wee, Chong-Yaw; Keller, Simon S; Weber, Bernd; Elger, Christian; da Silva, Laura Angelica Tomaz; Nesland, Travis; Styner, Martin; Shen, Dinggang; Bonilha, Leonardo

    2015-09-01

    The objective of this study is to evaluate machine learning algorithms aimed at predicting surgical treatment outcomes in groups of patients with temporal lobe epilepsy (TLE) using only the structural brain connectome. Specifically, the brain connectome is reconstructed using white matter fiber tracts from presurgical diffusion tensor imaging. To achieve our objective, a two-stage connectome-based prediction framework is developed that gradually selects a small number of abnormal network connections that contribute to the surgical treatment outcome, and in each stage a linear kernel operation is used to further improve the accuracy of the learned classifier. Using a 10-fold cross validation strategy, the first stage in the connectome-based framework is able to separate patients with TLE from normal controls with 80% accuracy, and second stage in the connectome-based framework is able to correctly predict the surgical treatment outcome of patients with TLE with 70% accuracy. Compared to existing state-of-the-art methods that use VBM data, the proposed two-stage connectome-based prediction framework is a suitable alternative with comparable prediction performance. Our results additionally show that machine learning algorithms that exclusively use structural connectome data can predict treatment outcomes in epilepsy with similar accuracy compared with "expert-based" clinical decision. In summary, using the unprecedented information provided in the brain connectome, machine learning algorithms may uncover pathological changes in brain network organization and improve outcome forecasting in the context of epilepsy. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. A two-stage predictive model to simultaneous control of trihalomethanes in water treatment plants and distribution systems: adaptability to treatment processes.

    Science.gov (United States)

    Domínguez-Tello, Antonio; Arias-Borrego, Ana; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2017-10-01

    The trihalomethanes (TTHMs) and others disinfection by-products (DBPs) are formed in drinking water by the reaction of chlorine with organic precursors contained in the source water, in two consecutive and linked stages, that starts at the treatment plant and continues in second stage along the distribution system (DS) by reaction of residual chlorine with organic precursors not removed. Following this approach, this study aimed at developing a two-stage empirical model for predicting the formation of TTHMs in the water treatment plant and subsequently their evolution along the water distribution system (WDS). The aim of the two-stage model was to improve the predictive capability for a wide range of scenarios of water treatments and distribution systems. The two-stage model was developed using multiple regression analysis from a database (January 2007 to July 2012) using three different treatment processes (conventional and advanced) in the water supply system of Aljaraque area (southwest of Spain). Then, the new model was validated using a recent database from the same water supply system (January 2011 to May 2015). The validation results indicated no significant difference in the predictive and observed values of TTHM (R 2 0.874, analytical variance model was applied to three different supply systems with different treatment processes and different characteristics. Acceptable predictions were obtained in the three distribution systems studied, proving the adaptability of the new model to the boundary conditions. Finally the predictive capability of the new model was compared with 17 other models selected from the literature, showing satisfactory results prediction and excellent adaptability to treatment processes.

  16. Predictive Clinical Parameters and Glycemic Efficacy of Vildagliptin Treatment in Korean Subjects with Type 2 Diabetes

    Directory of Open Access Journals (Sweden)

    Jin-Sun Chang

    2013-02-01

    Full Text Available BackgroundThe aims of this study are to investigate the glycemic efficacy and predictive parameters of vildagliptin therapy in Korean subjects with type 2 diabetes.MethodsIn this retrospective study, we retrieved data for subjects who were on twice-daily 50 mg vildagliptin for at least 6 months, and classified the subjects into five treatment groups. In three of the groups, we added vildagliptin to their existing medication regimen; in the other two groups, we replaced one of their existing medications with vildagliptin. We then analyzed the changes in glucose parameters and clinical characteristics.ResultsUltimately, 327 subjects were analyzed in this study. Vildagliptin significantly improved hemoglobin A1c (HbA1c levels over 6 months. The changes in HbA1c levels (ΔHbA1c at month 6 were -2.24% (P=0.000, -0.77% (P=0.000, -0.80% (P=0.001, -0.61% (P=0.000, and -0.34% (P=0.025 for groups 1, 2, 3, 4, and 5, respectively, with significance. We also found significant decrements in fasting plasma glucose levels in groups 1, 2, 3, and 4 (P<0.05. Of the variables, initial HbA1c levels (P=0.032 and history of sulfonylurea use (P=0.026 were independently associated with responsiveness to vildagliptin treatment.ConclusionVildagliptin was effective when it was used in subjects with poor glycemic control. It controlled fasting plasma glucose levels as well as sulfonylurea treatment in Korean type 2 diabetic subjects.

  17. Neural activation during processing of aversive faces predicts treatment outcome in alcoholism.

    Science.gov (United States)

    Charlet, Katrin; Schlagenhauf, Florian; Richter, Anne; Naundorf, Karina; Dornhof, Lina; Weinfurtner, Christopher E J; König, Friederike; Walaszek, Bernadeta; Schubert, Florian; Müller, Christian A; Gutwinski, Stefan; Seissinger, Annette; Schmitz, Lioba; Walter, Henrik; Beck, Anne; Gallinat, Jürgen; Kiefer, Falk; Heinz, Andreas

    2014-05-01

    Neuropsychological studies reported decoding deficits of emotional facial expressions in alcohol-dependent patients, and imaging studies revealed reduced prefrontal and limbic activation during emotional face processing. However, it remains unclear whether this reduced neural activation is mediated by alcohol-associated volume reductions and whether it interacts with treatment outcome. We combined analyses of neural activation during an aversive face-cue-comparison task and local gray matter volumes (GM) using Biological Parametric Mapping in 33 detoxified alcohol-dependent patients and 33 matched healthy controls. Alcoholics displayed reduced activation toward aversive faces-neutral shapes in bilateral fusiform gyrus [FG; Brodmann areas (BA) 18/19], right middle frontal gyrus (BA46/47), right inferior parietal gyrus (BA7) and left cerebellum compared with controls, which were explained by GM differences (except for cerebellum). Enhanced functional activation in patients versus controls was found in left rostral anterior cingulate cortex (ACC) and medial frontal gyrus (BA10/11), even after GM reduction control. Increased ACC activation correlated significantly with less (previous) lifetime alcohol intake [Lifetime Drinking History (LDH)], longer abstinence and less subsequent binge drinking in patients. High LDH appear to impair treatment outcome via its neurotoxicity on ACC integrity. Thus, high activation of the rostral ACC elicited by affective faces appears to be a resilience factor predicting better treatment outcome. Although no group differences were found, increased FG activation correlated with patients' higher LDH. Because high LDH correlated with worse task performance for facial stimuli in patients, elevated activation in the fusiform 'face' area may reflect inefficient compensatory activation. Therapeutic interventions (e.g. emotion evaluation training) may enable patients to cope with social stress and to decrease relapses after detoxification.

  18. Predicting response to physiotherapy treatment for musculoskeletal shoulder pain: protocol for a longitudinal cohort study

    Science.gov (United States)

    2013-01-01

    Background Shoulder pain affects all ages, with a lifetime prevalence of one in three. The most effective treatment is not known. Physiotherapy is often recommended as the first choice of treatment. At present, it is not possible to identify, from the initial physiotherapy assessment, which factors predict the outcome of physiotherapy for patients with shoulder pain. The primary objective of this study is to identify which patient characteristics and baseline measures, typically assessed at the first physiotherapy appointment, are related to the functional outcome of shoulder pain 6 weeks and 6 months after starting physiotherapy treatment. Methods/Design Participants with musculoskeletal shoulder pain of any duration will be recruited from participating physiotherapy departments. For this longitudinal cohort study, the participants care pathway, including physiotherapy treatment will be therapist determined. Potential prognostic variables will be collected from participants during their first physiotherapy appointment and will include demographic details, lifestyle, psychosocial factors, shoulder symptoms, general health, clinical examination, activity limitations and participation restrictions. Outcome measures (Shoulder Pain and Disability Index, Quick Disability of the Arm, Shoulder and Hand, and Global Impression of Change) will be collected by postal self-report questionnaires 6 weeks and 6 months after commencing physiotherapy. Details of attendance and treatment will be collected by the treating physiotherapist. Participants will be asked to complete an exercise dairy. An initial exploratory analysis will assess the relationship between potential prognostic factors at baseline and outcome using univariate statistical tests. Those factors significant at the 5% level will be further considered as prognostic factors using a general linear model. It is estimated that 780 subjects will provide more than 90% power to detect an effect size of less than 0

  19. Social class rank, essentialism, and punitive judgment.

    Science.gov (United States)

    Kraus, Michael W; Keltner, Dacher

    2013-08-01

    Recent evidence suggests that perceptions of social class rank influence a variety of social cognitive tendencies, from patterns of causal attribution to moral judgment. In the present studies we tested the hypotheses that upper-class rank individuals would be more likely to endorse essentialist lay theories of social class categories (i.e., that social class is founded in genetically based, biological differences) than would lower-class rank individuals and that these beliefs would decrease support for restorative justice--which seeks to rehabilitate offenders, rather than punish unlawful action. Across studies, higher social class rank was associated with increased essentialism of social class categories (Studies 1, 2, and 4) and decreased support for restorative justice (Study 4). Moreover, manipulated essentialist beliefs decreased preferences for restorative justice (Study 3), and the association between social class rank and class-based essentialist theories was explained by the tendency to endorse beliefs in a just world (Study 2). Implications for how class-based essentialist beliefs potentially constrain social opportunity and mobility are discussed.

  20. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  1. Global network centrality of university rankings

    Science.gov (United States)

    Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

    2017-10-01

    Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

  2. A Review of Outcomes of Seven World University Ranking Systems

    National Research Council Canada - National Science Library

    Mahmood Khosrowjerdi; Neda Zeraatkar

    2012-01-01

    There are many national and international ranking systems rank the universities and higher education institutions of the world, nationally or internationally, based on the same or different criteria...

  3. Prediction of lip response to orthodontic treatment using a multivariable regression model

    Directory of Open Access Journals (Sweden)

    Amin Shirvani

    2016-01-01

    Conclusion: Within the limitation of this study, multiple regression technique was slightly more accurate than the ratio of mean prediction (Viewbox4.0 software and appears to be useful in the prediction of soft tissue changes. As the variability of the predicted individual outcome seems to be relatively high, caution should be taken in predicting hard and soft tissue positional changes.

  4. What Predicts Patients' Willingness to Undergo Online Treatment and Pay for Online Treatment? Results from a Web-Based Survey to Investigate the Changing Patient-Physician Relationship.

    Science.gov (United States)

    Roettl, Johanna; Bidmon, Sonja; Terlutter, Ralf

    2016-02-04

    Substantial research has focused on patients' health information-seeking behavior on the Internet, but little is known about the variables that may predict patients' willingness to undergo online treatment and willingness to pay additionally for online treatment. This study analyzed sociodemographic variables, psychosocial variables, and variables of Internet usage to predict willingness to undergo online treatment and willingness to pay additionally for online treatment offered by the general practitioner (GP). An online survey of 1006 randomly selected German patients was conducted. The sample was drawn from an e-panel maintained by GfK HealthCare. Missing values were imputed; 958 usable questionnaires were analyzed. Variables with multi-item measurement were factor analyzed. Willingness to undergo online treatment and willingness to pay additionally for online treatment offered by the GP were predicted using 2 multiple regression models. Exploratory factor analyses revealed that the disposition of patients' personality to engage in information-searching behavior on the Internet was unidimensional. Exploratory factor analysis with the variables measuring the motives for Internet usage led to 2 separate factors: perceived usefulness (PU) of the Internet for health-related information searching and social motives for information searching on the Internet. Sociodemographic variables did not serve as significant predictors for willingness to undergo online treatment offered by the GP, whereas PU (B=.092, P=.08), willingness to communicate with the GP more often in the future (B=.495, Ponline communication with the GP (B=.198, Ponline treatment, but it was predicted by health-related information-seeking personality (B=.127, P=.07), PU (B=-.098, P=.09), willingness to undergo online treatment (B=.391, Ponline communication with the GP (B=.192, P=.001), highest education level (B=.178, Ponline more often in the future (B=.076, P=.03). Age, gender, and trust in the GP

  5. What Predicts Patients’ Willingness to Undergo Online Treatment and Pay for Online Treatment? Results from a Web-Based Survey to Investigate the Changing Patient-Physician Relationship

    Science.gov (United States)

    Bidmon, Sonja; Terlutter, Ralf

    2016-01-01

    Background Substantial research has focused on patients’ health information–seeking behavior on the Internet, but little is known about the variables that may predict patients’ willingness to undergo online treatment and willingness to pay additionally for online treatment. Objective This study analyzed sociodemographic variables, psychosocial variables, and variables of Internet usage to predict willingness to undergo online treatment and willingness to pay additionally for online treatment offered by the general practitioner (GP). Methods An online survey of 1006 randomly selected German patients was conducted. The sample was drawn from an e-panel maintained by GfK HealthCare. Missing values were imputed; 958 usable questionnaires were analyzed. Variables with multi-item measurement were factor analyzed. Willingness to undergo online treatment and willingness to pay additionally for online treatment offered by the GP were predicted using 2 multiple regression models. Results Exploratory factor analyses revealed that the disposition of patients’ personality to engage in information-searching behavior on the Internet was unidimensional. Exploratory factor analysis with the variables measuring the motives for Internet usage led to 2 separate factors: perceived usefulness (PU) of the Internet for health-related information searching and social motives for information searching on the Internet. Sociodemographic variables did not serve as significant predictors for willingness to undergo online treatment offered by the GP, whereas PU (B=.092, P=.08), willingness to communicate with the GP more often in the future (B=.495, Ponline communication with the GP (B=.198, Ponline treatment, but it was predicted by health-related information–seeking personality (B=.127, P=.07), PU (B=–.098, P=.09), willingness to undergo online treatment (B=.391, Ponline communication with the GP (B=.192, P=.001), highest education level (B=.178, Ponline more often in the future (B

  6. Do drug treatment variables predict cognitive performance in multidrug-treated opioid-dependent patients? A regression analysis study

    Directory of Open Access Journals (Sweden)

    Rapeli Pekka

    2012-11-01

    Full Text Available Abstract Background Cognitive deficits and multiple psychoactive drug regimens are both common in patients treated for opioid-dependence. Therefore, we examined whether the cognitive performance of patients in opioid-substitution treatment (OST is associated with their drug treatment variables. Methods Opioid-dependent patients (N = 104 who were treated either with buprenorphine or methadone (n = 52 in both groups were given attention, working memory, verbal, and visual memory tests after they had been a minimum of six months in treatment. Group-wise results were analysed by analysis of variance. Predictors of cognitive performance were examined by hierarchical regression analysis. Results Buprenorphine-treated patients performed statistically significantly better in a simple reaction time test than methadone-treated ones. No other significant differences between groups in cognitive performance were found. In each OST drug group, approximately 10% of the attention performance could be predicted by drug treatment variables. Use of benzodiazepine medication predicted about 10% of performance variance in working memory. Treatment with more than one other psychoactive drug (than opioid or BZD and frequent substance abuse during the past month predicted about 20% of verbal memory performance. Conclusions Although this study does not prove a causal relationship between multiple prescription drug use and poor cognitive functioning, the results are relevant for psychosocial recovery, vocational rehabilitation, and psychological treatment of OST patients. Especially for patients with BZD treatment, other treatment options should be actively sought.

  7. Predictive Factors for Subjective Improvement in Lumbar Spinal Stenosis Patients with Nonsurgical Treatment: A 3-Year Prospective Cohort Study.

    Directory of Open Access Journals (Sweden)

    Ko Matsudaira

    Full Text Available To assess the predictive factors for subjective improvement with nonsurgical treatment in consecutive patients with lumbar spinal stenosis (LSS.Patients with LSS were enrolled from 17 medical centres in Japan. We followed up 274 patients (151 men; mean age, 71 ± 7.4 years for 3 years. A multivariable logistic regression model was used to assess the predictive factors for subjective symptom improvement with nonsurgical treatment.In 30% of patients, conservative treatment led to a subjective improvement in the symptoms; in 70% of patients, the symptoms remained unchanged, worsened, or required surgical treatment. The multivariable analysis of predictive factors for subjective improvement with nonsurgical treatment showed that the absence of cauda equina symptoms (only radicular symptoms had an odds ratio (OR of 3.31 (95% confidence interval [CI]: 1.50-7.31; absence of degenerative spondylolisthesis/scoliosis had an OR of 2.53 (95% CI: 1.13-5.65; <1-year duration of illness had an OR of 3.81 (95% CI: 1.46-9.98; and hypertension had an OR of 2.09 (95% CI: 0.92-4.78.The predictive factors for subjective symptom improvement with nonsurgical treatment in LSS patients were the presence of only radicular symptoms, absence of degenerative spondylolisthesis/scoliosis, and an illness duration of <1 year.

  8. Resolution of ranking hierarchies in directed networks

    Science.gov (United States)

    Barucca, Paolo; Lillo, Fabrizio

    2018-01-01

    Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

  9. Low Rank Approximation Algorithms, Implementation, Applications

    CERN Document Server

    Markovsky, Ivan

    2012-01-01

    Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory. Applications described include: system and control theory: approximate realization, model reduction, output error, and errors-in-variables identification; signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modeling, and array processing; machine learning: multidimensional scaling and recommender system; computer vision: algebraic curve fitting and fundamental matrix estimation; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; ...

  10. Adaptive distributional extensions to DFR ranking

    DEFF Research Database (Denmark)

    Petersen, Casper; Simonsen, Jakob Grue; Järvelin, Kalervo

    2016-01-01

    Divergence From Randomness (DFR) ranking models assume that informative terms are distributed in a corpus differently than non-informative terms. Different statistical models (e.g. Poisson, geometric) are used to model the distribution of non-informative terms, producing different DFR models....... An informative term is then detected by measuring the divergence of its distribution from the distribution of non-informative terms. However, there is little empirical evidence that the distributions of non-informative terms used in DFR actually fit current datasets. Practically this risks providing a poor...... separation between informative and non-informative terms, thus compromising the discriminative power of the ranking model. We present a novel extension to DFR, which first detects the best-fitting distribution of non-informative terms in a collection, and then adapts the ranking computation to this best...

  11. Sign rank versus Vapnik-Chervonenkis dimension

    Science.gov (United States)

    Alon, N.; Moran, Sh; Yehudayoff, A.

    2017-12-01

    This work studies the maximum possible sign rank of sign (N × N)-matrices with a given Vapnik-Chervonenkis dimension d. For d=1, this maximum is three. For d=2, this maximum is \\widetilde{\\Theta}(N1/2). For d >2, similar but slightly less accurate statements hold. The lower bounds improve on previous ones by Ben-David et al., and the upper bounds are novel. The lower bounds are obtained by probabilistic constructions, using a theorem of Warren in real algebraic topology. The upper bounds are obtained using a result of Welzl about spanning trees with low stabbing number, and using the moment curve. The upper bound technique is also used to: (i) provide estimates on the number of classes of a given Vapnik-Chervonenkis dimension, and the number of maximum classes of a given Vapnik-Chervonenkis dimension--answering a question of Frankl from 1989, and (ii) design an efficient algorithm that provides an O(N/log(N)) multiplicative approximation for the sign rank. We also observe a general connection between sign rank and spectral gaps which is based on Forster's argument. Consider the adjacency (N × N)-matrix of a Δ-regular graph with a second eigenvalue of absolute value λ and Δ ≤ N/2. We show that the sign rank of the signed version of this matrix is at least Δ/λ. We use this connection to prove the existence of a maximum class C\\subseteq\\{+/- 1\\}^N with Vapnik-Chervonenkis dimension 2 and sign rank \\widetilde{\\Theta}(N1/2). This answers a question of Ben-David et al. regarding the sign rank of large Vapnik-Chervonenkis classes. We also describe limitations of this approach, in the spirit of the Alon-Boppana theorem. We further describe connections to communication complexity, geometry, learning theory, and combinatorics. Bibliography: 69 titles.

  12. Anterior Cruciate Ligament Tear: Reliability of MR Imaging to Predict Stability after Conservative Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Hye Won; Ahn, Jin Hwan; Ahn, Joong Mo; Yoon, Young Cheol; Hong, Hyun Pyo; Yoo, So Young; Kim, Seon Woo [Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

    2007-06-15

    The aim of this study is to evaluate the reliability of MR imaging to predict the stability of the torn anterior cruciate ligament (ACL) after complete recovery of the ligament's continuity. Twenty patients with 20 knee injuries (13 males and 7 females; age range, 20 54) were enrolled in the study. The inclusion criteria were a positive history of acute trauma, diagnosis of the ACL tear by both the physical examination and the MR imaging at the initial presentation, conservative treatment, complete recovery of the continuity of the ligament on the follow up (FU) MR images and availability of the KT-2000 measurements. Two radiologists, who worked in consensus, graded the MR findings with using a 3-point system for the signal intensity, sharpness, straightness and the thickness of the healed ligament. The insufficiency of ACL was categorized into three groups according to the KT-2000 measurements. The statistic correlations between the grades of the MR findings and the degrees of ACL insufficiency were analyzed using the Cochran-Mantel-Haenszel test (p < 0.05). The p-values for each category of the MR findings according to the different groups of the KT-2000 measurements were 0.9180 for the MR signal intensity, 1.0000 for sharpness, 0.5038 for straightness and 0.2950 for thickness of the ACL. The MR findings were not significantly different between the different KT-2000 groups. MR imaging itself is not a reliable examination to predict stability of the ACL rupture outcome, even when the MR images show an intact appearance of the ACL.

  13. Importance of early weight changes to predict long-term weight gain during psychotropic drug treatment.

    Science.gov (United States)

    Vandenberghe, Frederik; Gholam-Rezaee, Mehdi; Saigí-Morgui, Núria; Delacrétaz, Aurélie; Choong, Eva; Solida-Tozzi, Alessandra; Kolly, Stéphane; Thonney, Jacques; Gallo, Sylfa Fassassi; Hedjal, Ahmed; Ambresin, Anne-Emmanuelle; von Gunten, Armin; Conus, Philippe; Eap, Chin B

    2015-11-01

    Psychotropic drugs can induce substantial weight gain, particularly during the first 6 months of treatment. The authors aimed to determine the potential predictive power of an early weight gain after the introduction of weight gain-inducing psychotropic drugs on long-term weight gain. Data were obtained from a 1-year longitudinal study ongoing since 2007 including 351 psychiatric (ICD-10) patients, with metabolic parameters monitored (baseline and/or 1, 3, 6, 9, 12 months) and with compliance ascertained. International Diabetes Federation and World Health Organization definitions were used to define metabolic syndrome and obesity, respectively. Prevalences of metabolic syndrome and obesity were 22% and 17%, respectively, at baseline and 32% and 24% after 1 year. Receiver operating characteristic analyses indicated that an early weight gain > 5% after a period of 1 month is the best predictor for important long-term weight gain (≥ 15% after 3 months: sensitivity, 67%; specificity, 88%; ≥ 20% after 12 months: sensitivity, 47%; specificity, 89%). This analysis identified most patients (97% for 3 months, 93% for 12 months) who had weight gain ≤ 5% after 1 month as continuing to have a moderate weight gain after 3 and 12 months. Its predictive power was confirmed by fitting a longitudinal multivariate model (difference between groups in 1 year of 6.4% weight increase as compared to baseline, P = .0001). Following prescription of weight gain-inducing psychotropic drugs, a 5% threshold for weight gain after 1 month should raise clinician concerns about weight-controlling strategies. © Copyright 2015 Physicians Postgraduate Press, Inc.

  14. Pulling Rank: A Plan to Help Students with College Choice in an Age of Rankings

    Science.gov (United States)

    Thacker, Lloyd

    2008-01-01

    Colleges and universities are "ranksteering"--driving under the influence of popular college rankings systems like "U.S. News and World Report's" Best Colleges. This article examines the criticisms of college rankings and describes how a group of education leaders is honing a plan to end the tyranny of the ratings game and better help students and…

  15. When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

    KAUST Repository

    Wang, Jim Jing-Yan

    2017-06-28

    Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

  16. Stroke Treatments

    Science.gov (United States)

    ... Month Infographic Stroke Hero F.A.S.T. Quiz Stroke Treatment Stroke used to rank fourth in leading causes of ... type of treatment depends on the type of stroke. Ischemic stroke happens when a clot blocks a ...

  17. Accuracy of Dolphin visual treatment objective (VTO prediction software on class III patients treated with maxillary advancement and mandibular setback

    Directory of Open Access Journals (Sweden)

    Robert J. Peterman

    2016-06-01

    Full Text Available Abstract Background Dolphin® visual treatment objective (VTO prediction software is routinely utilized by orthodontists during the treatment planning of orthognathic cases to help predict post-surgical soft tissue changes. Although surgical soft tissue prediction is considered to be a vital tool, its accuracy is not well understood in tow-jaw surgical procedures. The objective of this study was to quantify the accuracy of Dolphin Imaging’s VTO soft tissue prediction software on class III patients treated with maxillary advancement and mandibular setback and to validate the efficacy of the software in such complex cases. Methods This retrospective study analyzed the records of 14 patients treated with comprehensive orthodontics in conjunction with two-jaw orthognathic surgery. Pre- and post-treatment radiographs were traced and superimposed to determine the actual skeletal movements achieved in surgery. This information was then used to simulate surgery in the software and generate a final soft tissue patient profile prediction. Prediction images were then compared to the actual post-treatment profile photos to determine differences. Results Dolphin Imaging’s software was determined to be accurate within an error range of +/− 2 mm in the X-axis at most landmarks. The lower lip predictions were most inaccurate. Conclusions Clinically, the observed error suggests that the VTO may be used for demonstration and communication with a patient or consulting practitioner. However, Dolphin should not be useful for precise treatment planning of surgical movements. This program should be used with caution to prevent unrealistic patient expectations and dissatisfaction.

  18. Ranking Entities in Networks via Lefschetz Duality

    DEFF Research Database (Denmark)

    Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Poulsen, Bjarne

    2014-01-01

    In the theory of communication it is essential that agents are able to exchange information. This fact is closely related to the study of connected spaces in topology. A communication network may be modelled as a topological space such that agents can communicate if and only if they belong...... then be ranked according to how essential their positions are in the network by considering the effect of their respective absences. Defining a ranking of a network which takes the individual position of each entity into account has the purpose of assigning different roles to the entities, e.g. agents...

  19. Compressed Sensing with Rank Deficient Dictionaries

    DEFF Research Database (Denmark)

    Hansen, Thomas Lundgaard; Johansen, Daniel Højrup; Jørgensen, Peter Bjørn

    2012-01-01

    In compressed sensing it is generally assumed that the dictionary matrix constitutes a (possibly overcomplete) basis of the signal space. In this paper we consider dictionaries that do not span the signal space, i.e. rank deficient dictionaries. We show that in this case the signal-to-noise ratio...... (SNR) in the compressed samples can be increased by selecting the rows of the measurement matrix from the column space of the dictionary. As an example application of compressed sensing with a rank deficient dictionary, we present a case study of compressed sensing applied to the Coarse Acquisition (C...

  20. Predicting response to physiotherapy treatment for musculoskeletal shoulder pain: a systematic review

    Science.gov (United States)

    2013-01-01

    Background People suffering from musculoskeletal shoulder pain are frequently referred to physiotherapy. Physiotherapy generally involves a multimodal approach to management that may include; exercise, manual therapy and techniques to reduce pain. At present it is not possible to predict which patients will respond positively to physiotherapy treatment. The purpose of this systematic review was to identify which prognostic factors are associated with the outcome of physiotherapy in the management of musculoskeletal shoulder pain. Methods A comprehensive search was undertaken of Ovid Medline, EMBASE, CINAHL and AMED (from inception to January 2013). Prospective studies of participants with shoulder pain receiving physiotherapy which investigated the association between baseline prognostic factors and change in pain and function over time were included. Study selection, data extraction and appraisal of study quality were undertaken by two independent assessors. Quality criteria were selected from previously published guidelines to form a checklist of 24 items. The study protocol was prospectively registered onto the International Prospective Register of Systematic Reviews. Results A total of 5023 titles were retrieved and screened for eligibility, 154 articles were assessed as full text and 16 met the inclusion criteria: 11 cohort studies, 3 randomised controlled trials and 2 controlled trials. Results were presented for the 9 studies meeting 13 or more of the 24 quality criteria. Clinical and statistical heterogeneity resulted in qualitative synthesis rather than meta-analysis. Three studies demonstrated that high functional disability at baseline was associated with poor functional outcome (p ≤ 0.05). Four studies demonstrated a significant association (p ≤ 0.05) between longer duration of shoulder pain and poorer outcome. Three studies, demonstrated a significant association (p ≤ 0.05) between increasing age and poorer function; three studies

  1. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

    Directory of Open Access Journals (Sweden)

    LI Lan-yin

    2017-04-01

    Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank,which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes,topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs,and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

  2. Network information improves cancer outcome prediction.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

    2014-07-01

    Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  3. Predicting substance-abuse treatment providers' communication with clients about medication assisted treatment: a test of the theories of reasoned action and planned behavior.

    Science.gov (United States)

    Roberto, Anthony J; Shafer, Michael S; Marmo, Jennifer

    2014-01-01

    The purpose of this investigation is to determine if the theory of reasoned action (TRA) and theory of planned behavior (TPB) can retrospectively predict whether substance-abuse treatment providers encourage their clients to use medicated-assisted treatment (MAT) as part of their treatment plan. Two-hundred and ten substance-abuse treatment providers completed a survey measuring attitudes, subjective norms, perceived behavioral control, intentions, and behavior. Results indicate that substance-abuse treatment providers have very positive attitudes, neutral subjective norms, somewhat positive perceived behavioral control, somewhat positive intentions toward recommending MAT as part of their clients' treatment plan, and were somewhat likely to engage in the actual behavior. Further, the data fit both the TRA and TPB, but with the TPB model having better fit and predictive power for this target audience and behavior. The theoretical and practical implications for the developing messages for substance-abuse treatment providers and other health-care professionals who provide treatment to patients with substance use disorders are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Childhood trauma predicts antidepressant response in adults with major depression: data from the randomized international study to predict optimized treatment for depression

    Science.gov (United States)

    Williams, L M; Debattista, C; Duchemin, A-M; Schatzberg, A F; Nemeroff, C B

    2016-01-01

    Few reliable predictors indicate which depressed individuals respond to antidepressants. Several studies suggest that a history of early-life trauma predicts poorer response to antidepressant therapy but results are variable and limited in adults. The major goal of the present study was to evaluate the role of early-life trauma in predicting acute response outcomes to antidepressants in a large sample of well-characterized patients with major depressive disorder (MDD). The international Study to Predict Optimized Treatment for Depression (iSPOT-D) is a randomized clinical trial with enrollment from December 2008 to January 2012 at eight academic and nine private clinical settings in five countries. Patients (n=1008) meeting DSM-IV criteria for MDD and 336 matched healthy controls comprised the study sample. Six participants withdrew due to serious adverse events. Randomization was to 8 weeks of treatment with escitalopram, sertraline or venlafaxine with dosage adjusted by the participant's treating clinician per routine clinical practice. Exposure to 18 types of traumatic events before the age of 18 was assessed using the Early-Life Stress Questionnaire. Impact of early-life stressors—overall trauma ‘load' and specific type of abuse—on treatment outcomes measures: response: (⩾50% improvement on the 17-item Hamilton Rating Scale for Depression, HRSD17 or on the 16-item Quick Inventory of Depressive Symptomatology—Self-Rated, QIDS_SR16) and remission (score ⩽7 on the HRSD17 and ⩽5 on the QIDS_SR16). Trauma prevalence in MDD was compared with controls. Depressed participants were significantly more likely to report early-life stress than controls; 62.5% of MDD participants reported more than two traumatic events compared with 28.4% of controls. The higher rate of early-life trauma was most apparent for experiences of interpersonal violation (emotional, sexual and physical abuses). Abuse and notably abuse occurring at ⩽7 years of age predicted poorer

  5. Predictive Model and Methodology for Heat Treatment Distortion Final Report CRADA No. TC-298-92

    Energy Technology Data Exchange (ETDEWEB)

    Nikkel, D. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McCabe, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-10-16

    This project was a multi-lab, multi-partner CRADA involving LLNL, Los Alamos National Laboratory, Sandia National Laboratories, Oak Ridge National Laboratory, Martin Marietta Energy Systems and the industrial partner, The National Center of Manufacturing Sciences (NCMS). A number of member companies of NCMS participated including General Motors Corporation, Ford Motor Company, The Torrington Company, Gear Research, the Illinois Institute of Technology Research Institute, and Deformation Control Technology •. LLNL was the lead laboratory for metrology technology used for validation of the computational tool/methodology. LLNL was also the lead laboratory for the development of the software user interface , for the computational tool. This report focuses on the participation of LLNL and NCMS. The purpose of the project was to develop a computational tool/methodology that engineers would use to predict the effects of heat treatment on the _size and shape of industrial parts made of quench hardenable alloys. Initially, the target application of the tool was gears for automotive power trains.

  6. Predictive validity of addiction treatment clinicians’ post-training contingency management skills for subsequent clinical outcomes

    Science.gov (United States)

    Hartzler, Bryan; Beadnell, Blair; Donovan, Dennis

    2015-01-01

    In the context of a contingency management (CM) implementation/effectiveness hybrid trial, the post-training implementation domains of direct-care clinicians (N=19) were examined in relation to a targeted clinical outcome of subsequently CM-exposed clients. Clinicians’ CM skillfulness, a behavioral measure of their capability to skillfully deliver the intended CM intervention, was found to be a robust and specific predictor of their subsequent client outcomes. Analyses also revealed CM skillfulness to: 1) fully mediate an association between a general therapeutic effectiveness and client outcome, 2) partially mediate an association of in-training exposure to CM and client outcome, and 3) be comprised of six component clinical practice behaviors that each contributed meaningfully to this behavior fidelity index. Study findings offer preliminary evidence of the predictive validity of post-training CM skillfulness for subsequent client outcomes, and inform suggestions for the design and delivery of skills-focused CM training curricula for the addiction treatment workforce. PMID:26733276

  7. Predictive Validity of Addiction Treatment Clinicians' Post-Training Contingency Management Skills for Subsequent Clinical Outcomes.

    Science.gov (United States)

    Hartzler, Bryan; Beadnell, Blair; Donovan, Dennis

    2017-01-01

    In the context of a contingency management (CM) implementation/effectiveness hybrid trial, the post-training implementation domains of direct-care clinicians (N=19) were examined in relation to a targeted clinical outcome of subsequently CM-exposed clients. Clinicians' CM skillfulness, a behavioral measure of their capability to skillfully deliver the intended CM intervention, was found to be a robust and specific predictor of their subsequent client outcomes. Analyses also revealed CM skillfulness to: (1) fully mediate an association between a general therapeutic effectiveness and client outcome, (2) partially mediate an association of in-training exposure to CM and client outcome, and (3) be composed of six component clinical practice behaviors that each contributed meaningfully to this behavior fidelity index. Study findings offer preliminary evidence of the predictive validity of post-training CM skillfulness for subsequent client outcomes, and inform suggestions for the design and delivery of skills-focused CM training curricula for the addiction treatment workforce. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Plant-specific correlations to predict the total VOC emissions from wastewater treatment plants

    Science.gov (United States)

    Oskouie, Ali K.; Lordi, David T.; Granato, Thomas C.; Kollias, Louis

    Simple linear correlations between the lumped parameter of raw wastewater flow rate, mixed liquor suspended solids (MLSS), and concentration of three volatile organic compounds (VOCs), chloroform, dichloromethane and toluene in the liquid and gas phases, Q×MLSS(C/ER), and T, wastewater temperature, were found for three large wastewater treatment plants operated by the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) using their monthly data for year 2000. These linear relationships were verified for these three dominant VOCs using the data from years 1987 to 1992, 1998, and 1999 for the three MWRDGC plants. The results of this theoretical study showed that linear functions could reasonably fit to the actual data, and the specific VOC compounds' emission rate could be predicted upon having information on ambient temperature, MLSS, and VOC concentration in the liquid phase at the influent to the specific plant without having to use the Bay Area Sewage Toxics Emission (BASTE) fate model as a future emission estimator once the baseline correlation was determined.

  9. Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats

    Science.gov (United States)

    Farhidzadeh, Hamidreza; Chaudhury, Baishali; Zhou, Mu; Goldgof, Dmitry B.; Hall, Lawrence O.; Gatenby, Robert A.; Gillies, Robert J.; Raghavan, Meera

    2015-03-01

    Soft tissue sarcomas are malignant tumors which develop from tissues like fat, muscle, nerves, fibrous tissue or blood vessels. They are challenging to physicians because of their relative infrequency and diverse outcomes, which have hindered development of new therapeutic agents. Additionally, assessing imaging response of these tumors to therapy is also difficult because of their heterogeneous appearance on magnetic resonance imaging (MRI). In this paper, we assessed standard of care MRI sequences performed before and after treatment using 36 patients with soft tissue sarcoma. Tumor tissue was identified by manually drawing a mask on contrast enhanced images. The Otsu segmentation method was applied to segment tumor tissue into low and high signal intensity regions on both T1 post-contrast and T2 without contrast images. This resulted in four distinctive subregions or "habitats." The features used to predict metastatic tumors and necrosis included the ratio of habitat size to whole tumor size and components of 2D intensity histograms. Individual cases were correctly classified as metastatic or non-metastatic disease with 80.55% accuracy and for necrosis ≥ 90 or necrosis <90 with 75.75% accuracy by using meta-classifiers which contained feature selectors and classifiers.

  10. Fully Automated Treatment Planning for Head and Neck Radiotherapy using a Voxel-Based Dose Prediction and Dose Mimicking Method

    CERN Document Server

    McIntosh, Chris; McNiven, Andrea; Jaffray, David A; Purdie, Thomas G

    2016-01-01

    Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present an atlas-based approach which learns a dose prediction model for each patient (atlas) in a training database, and then learns to match novel patients to the most relevant atlases. The method creates a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces any requirement for specifying dose-volume objectives for conveying the goals of treatment planning. A probabilistic dose distribution is inferred from the most relevant atlases, and is scalarized using a conditional random field to determine the most likely spatial distribution of dose to yield a specific dose prior (histogram) for relevant regions of interest. Voxel-based dose mimicking then converts the predicted dose distribution to a deliverable treatment plan dose distribution. In this study, we ...

  11. SOUTH AFRICAN ARMY RANKS AND INSIGNIA

    African Journals Online (AJOL)

    major, cap- tain, lieutenant;. Other Ranks : Warrant officer, staff sergeant, sergeant, corporal, lance-cor- poral, private.' We apparently had no need for second lieuten- ants at that time, and they were introduced only .... Army warrant officers can also hold the cmmon serv- ice posts of Sergeant-Major of Special Forces.

  12. Kinesiology Faculty Citations across Academic Rank

    Science.gov (United States)

    Knudson, Duane

    2015-01-01

    Citations to research reports are used as a measure for the influence of a scholar's research line when seeking promotion, grants, and awards. The current study documented the distributions of citations to kinesiology scholars of various academic ranks. Google Scholar Citations was searched for user profiles using five research interest areas…

  13. Biomechanics Scholar Citations across Academic Ranks

    Directory of Open Access Journals (Sweden)

    Knudson Duane

    2015-11-01

    Full Text Available Study aim: citations to the publications of a scholar have been used as a measure of the quality or influence of their research record. A world-wide descriptive study of the citations to the publications of biomechanics scholars of various academic ranks was conducted.

  14. Ranking Workplace Competencies: Student and Graduate Perceptions.

    Science.gov (United States)

    Rainsbury, Elizabeth; Hodges, Dave; Burchell, Noel; Lay, Mark

    2002-01-01

    New Zealand business students and graduates made similar rankings of the five most important workplace competencies: computer literacy, customer service orientation, teamwork and cooperation, self-confidence, and willingness to learn. Graduates placed greater importance on most of the 24 competencies, resulting in a statistically significant…

  15. Subject Gateway Sites and Search Engine Ranking.

    Science.gov (United States)

    Thelwall, Mike

    2002-01-01

    Discusses subject gateway sites and commercial search engines for the Web and presents an explanation of Google's PageRank algorithm. The principle question addressed is the conditions under which a gateway site will increase the likelihood that a target page is found in search engines. (LRW)

  16. Ranking related entities: components and analyses

    NARCIS (Netherlands)

    Bron, M.; Balog, K.; de Rijke, M.

    2010-01-01

    Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components;

  17. Low-rank coal oil agglomeration

    Science.gov (United States)

    Knudson, C.L.; Timpe, R.C.

    1991-07-16

    A low-rank coal oil agglomeration process is described. High mineral content, a high ash content subbituminous coals are effectively agglomerated with a bridging oil which is partially water soluble and capable of entering the pore structure, and is usually coal-derived.

  18. An evaluation and critique of current rankings

    NARCIS (Netherlands)

    Federkeil, Gero; Westerheijden, Donald F.; van Vught, Franciscus A.; Ziegele, Frank

    2012-01-01

    This chapter raises the question of whether university league tables deliver relevant information to one of their key target groups – students. It examines the inherent biases and weaknesses in the methodologies of the major rankings and argues that the concentration on a single indicator of

  19. World University Ranking Methodologies: Stability and Variability

    Science.gov (United States)

    Fidler, Brian; Parsons, Christine

    2008-01-01

    There has been a steady growth in the number of national university league tables over the last 25 years. By contrast, "World University Rankings" are a more recent development and have received little serious academic scrutiny in peer-reviewed publications. Few researchers have evaluated the sources of data and the statistical…

  20. Alternative Class Ranks Using Z-Scores

    Science.gov (United States)

    Brown, Philip H.; Van Niel, Nicholas

    2012-01-01

    Grades at US colleges and universities have increased precipitously over the last 50 years, suggesting that their signalling power has become attenuated. Moreover, average grades have risen disproportionately in some departments, implying that weak students in departments with high grades may obtain better class ranks than strong students in…

  1. Statistical inference of Minimum Rank Factor Analysis

    NARCIS (Netherlands)

    Shapiro, A; Ten Berge, JMF

    For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the unexplained common variance with that number of factors is minimized, subject to the constraint that both the diagonal matrix of unique variances and the

  2. City Life: Rankings (Livability) versus Perceptions (Satisfaction)

    Science.gov (United States)

    Okulicz-Kozaryn, Adam

    2013-01-01

    I investigate the relationship between the popular Mercer city ranking (livability) and survey data (satisfactions). Livability aims to capture "objective" quality of life such as infrastructure. Survey items capture "subjective" quality of life such as satisfaction with city. The relationship between objective measures of quality of life and…

  3. Matrices with high completely positive semidefinite rank

    NARCIS (Netherlands)

    de Laat, David; Gribling, Sander; Laurent, Monique

    2017-01-01

    A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by (Hermitian) positive semidefinite matrices of any size d. The smallest such d is called the (complex) completely positive semidefinite rank of M , and it is an open question whether there exists an

  4. Ranking health between countries in international comparisons

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    2014-01-01

    Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions...

  5. Comparing survival curves using rank tests

    NARCIS (Netherlands)

    Albers, Willem/Wim

    1990-01-01

    Survival times of patients can be compared using rank tests in various experimental setups, including the two-sample case and the case of paired data. Attention is focussed on two frequently occurring complications in medical applications: censoring and tail alternatives. A review is given of the

  6. Smooth rank one perturbations of selfadjoint operators

    NARCIS (Netherlands)

    Hassi, Seppo; Snoo, H.S.V. de; Willemsma, A.D.I.

    Let A be a selfadjoint operator in a Hilbert space aleph with inner product [.,.]. The rank one perturbations of A have the form A+tau [.,omega]omega, tau epsilon R, for some element omega epsilon aleph. In this paper we consider smooth perturbations, i.e. we consider omega epsilon dom \\A\\(k/2) for

  7. Primate Innovation: Sex, Age and Social Rank

    NARCIS (Netherlands)

    Reader, S.M.; Laland, K.N.

    2001-01-01

    Analysis of an exhaustive survey of primate behavior collated from the published literature revealed significant variation in rates of innovation among individuals of different sex, age and social rank. We searched approximately 1,000 articles in four primatology journals, together with other

  8. An algorithm for ranking assignments using reoptimization

    DEFF Research Database (Denmark)

    Pedersen, Christian Roed; Nielsen, Lars Relund; Andersen, Kim Allan

    2008-01-01

    We consider the problem of ranking assignments according to cost in the classical linear assignment problem. An algorithm partitioning the set of possible assignments, as suggested by Murty, is presented where, for each partition, the optimal assignment is calculated using a new reoptimization...... technique. Computational results for the new algorithm are presented...

  9. Ouderdom, omvang en citatiescores: rankings nader bekeken

    NARCIS (Netherlands)

    van Rooij, Jules

    2017-01-01

    By comparing the Top-300 lists of four global university rankings (ARWU, THE, QS, Leiden), three hypotheses are tested: 1) position correlates with size in the ARWU more than in the THE and QS; 2) given their strong dependency on reputation scores, position will be correlated more with a

  10. Returns to Tenure: Time or Rank?

    DEFF Research Database (Denmark)

    Buhai, Ioan Sebastian

    -specific investment, efficiency-wages or adverse-selection models. However, rent extracting arguments as suggested by the theory of internal labor markets, indicate that the relative position of the worker in the seniority hierarchy of the firm, her 'seniority rank', may also explain part of the observed returns...

  11. Probabilistic relation between In-Degree and PageRank

    NARCIS (Netherlands)

    Litvak, Nelli; Scheinhardt, Willem R.W.; Volkovich, Y.

    2008-01-01

    This paper presents a novel stochastic model that explains the relation between power laws of In-Degree and PageRank. PageRank is a popularity measure designed by Google to rank Web pages. We model the relation between PageRank and In-Degree through a stochastic equation, which is inspired by the

  12. The effect of new links on Google PageRank

    NARCIS (Netherlands)

    Avrachenkov, Konstatin; Litvak, Nelli

    2004-01-01

    PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer and thus it reflects the popularity of a Web page. We study the effect of newly created links on Google PageRank. We discuss to

  13. World University Rankings: Take with a Large Pinch of Salt

    Science.gov (United States)

    Cheng, Soh Kay

    2011-01-01

    Equating the unequal is misleading, and this happens consistently in comparing rankings from different university ranking systems, as the NUT saga shows. This article illustrates the problem by analyzing the 2011 rankings of the top 100 universities in the AWUR, QSWUR and THEWUR ranking results. It also discusses the reasons why the rankings…

  14. Generalized Reduced Rank Tests using the Singular Value Decomposition

    NARCIS (Netherlands)

    Kleibergen, F.R.; Paap, R.

    2006-01-01

    We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson [Annals of Mathematical Statistics (1951), 22, 327-351] sensitivity to the

  15. Some upper and lower bounds on PSD-rank

    NARCIS (Netherlands)

    T. J. Lee (Troy); Z. Wei (Zhaohui); R. M. de Wolf (Ronald)

    2014-01-01

    textabstractPositive semidefinite rank (PSD-rank) is a relatively new quantity with applications to combinatorial optimization and communication complexity. We first study several basic properties of PSD-rank, and then develop new techniques for showing lower bounds on the PSD-rank. All of these

  16. Some upper and lower bounds on PSD-rank

    NARCIS (Netherlands)

    Lee, T.; Wei, Z.; de Wolf, R.

    Positive semidefinite rank (PSD-rank) is a relatively new complexity measure on matrices, with applications to combinatorial optimization and communication complexity. We first study several basic properties of PSD-rank, and then develop new techniques for showing lower bounds on the PSD-rank. All

  17. Predicting Treatment Outcomes from Prefrontal Cortex Activation for Self-Harming Patients with Borderline Personality Disorder: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Anthony Charles Ruocco

    2016-05-01

    Full Text Available Self-harm is a potentially lethal symptom of borderline personality disorder (BPD that often improves with dialectical behavior therapy (DBT. While DBT is effective for reducing self-harm in many patients with BPD, a small but significant number of patients either does not improve in treatment or ends treatment prematurely. Accordingly, it is crucial to identify factors that may prospectively predict which patients are most likely to benefit from and remain in treatment. In the present preliminary study, twenty-nine actively self-harming patients with BPD completed brain-imaging procedures probing activation of the prefrontal cortex during impulse control prior to beginning DBT and after seven months of treatment. Patients that reduced their frequency of self-harm the most over treatment displayed lower levels of neural activation in the bilateral dorsolateral prefrontal cortex prior to beginning treatment, and they showed the greatest increases in activity within this region after seven months of treatment. Prior to starting DBT, treatment non-completers demonstrated greater activation than treatment-completers in the medial prefrontal cortex and right inferior frontal gyrus. Reductions in self-harm over the treatment period were associated with increases in activity in right dorsolateral prefrontal cortex even after accounting for improvements in depression, mania, and BPD symptom severity. These findings suggest that pre-treatment patterns of activation in the prefrontal cortex underlying impulse control may be prospectively associated with improvements in self-harm and treatment attrition for patients with BPD treated with DBT.

  18. Predicting Treatment Outcomes from Prefrontal Cortex Activation for Self-Harming Patients with Borderline Personality Disorder: A Preliminary Study

    Science.gov (United States)

    Ruocco, Anthony C.; Rodrigo, Achala H.; McMain, Shelley F.; Page-Gould, Elizabeth; Ayaz, Hasan; Links, Paul S.

    2016-01-01

    Self-harm is a potentially lethal symptom of borderline personality disorder (BPD) that often improves with dialectical behavior therapy (DBT). While DBT is effective for reducing self-harm in many patients with BPD, a small but significant number of patients either does not improve in treatment or ends treatment prematurely. Accordingly, it is crucial to identify factors that may prospectively predict which patients are most likely to benefit from and remain in treatment. In the present preliminary study, 29 actively self-harming patients with BPD completed brain-imaging procedures probing activation of the prefrontal cortex (PFC) during impulse control prior to beginning DBT and after 7 months of treatment. Patients that reduced their frequency of self-harm the most over treatment displayed lower levels of neural activation in the bilateral dorsolateral prefrontal cortex (DLPFC) prior to beginning treatment, and they showed the greatest increases in activity within this region after 7 months of treatment. Prior to starting DBT, treatment non-completers demonstrated greater activation than treatment-completers in the medial PFC and right inferior frontal gyrus. Reductions in self-harm over the treatment period were associated with increases in activity in right DLPFC even after accounting for improvements in depression, mania, and BPD symptom severity. These findings suggest that pre-treatment patterns of activation in the PFC underlying impulse control may be prospectively associated with improvements in self-harm and treatment attrition for patients with BPD treated with DBT. PMID:27242484

  19. Biology of RANK, RANKL, and osteoprotegerin

    Science.gov (United States)

    Boyce, Brendan F; Xing, Lianping

    2007-01-01

    The discovery of the receptor activator of nuclear factor-κB ligand (RANKL)/RANK/osteoprotegerin (OPG) system and its role in the regulation of bone resorption exemplifies how both serendipity and a logic-based approach can identify factors that regulate cell function. Before this discovery in the mid to late 1990s, it had long been recognized that osteoclast formation was regulated by factors expressed by osteoblast/stromal cells, but it had not been anticipated that members of the tumor necrosis factor superfamily of ligands and receptors would be involved or that the factors involved would have extensive functions beyond bone remodeling. RANKL/RANK signaling regulates the formation of multinucleated osteoclasts from their precursors as well as their activation and survival in normal bone remodeling and in a variety of pathologic conditions. OPG protects the skeleton from excessive bone resorption by binding to RANKL and preventing it from binding to its receptor, RANK. Thus, RANKL/OPG ratio is an important determinant of bone mass and skeletal integrity. Genetic studies in mice indicate that RANKL/RANK signaling is also required for lymph node formation and mammary gland lactational hyperplasia, and that OPG also protects arteries from medial calcification. Thus, these tumor necrosis factor superfamily members have important functions outside bone. Although our understanding of the mechanisms whereby they regulate osteoclast formation has advanced rapidly during the past 10 years, many questions remain about their roles in health and disease. Here we review our current understanding of the role of the RANKL/RANK/OPG system in bone and other tissues. PMID:17634140

  20. VaRank: a simple and powerful tool for ranking genetic variants

    Directory of Open Access Journals (Sweden)

    Véronique Geoffroy

    2015-03-01

    Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

  1. Optimization of continuous ranked probability score using PSO

    Directory of Open Access Journals (Sweden)

    Seyedeh Atefeh Mohammadi

    2015-07-01

    Full Text Available Weather forecast has been a major concern in various industries such as agriculture, aviation, maritime, tourism, transportation, etc. A good weather prediction may reduce natural disasters and unexpected events. This paper presents an empirical investigation to predict weather temperature using continuous ranked probability score (CRPS. The mean and standard deviation of normal density function are linear combination of the components of ensemble system. The resulted optimization model has been solved using particle swarm optimization (PSO and the results are compared with Broyden–Fletcher–Goldfarb–Shanno (BFGS method. The preliminary results indicate that the proposed PSO provides better results in terms of root-mean-square deviation criteria than the alternative BFGS method.

  2. Predictors of remission in depression to individual and combined treatments (PReDICT: study protocol for a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Dunlop Boadie W

    2012-07-01

    -week course of treatment, during which they receive a combination of CBT and antidepressant medication. Predictors of the primary outcome, remission, will be identified for overall and treatment-specific effects, and a statistical model incorporating multiple predictors will be developed to predict outcomes. Discussion The PReDICT study’s evaluation of biological, psychological, and clinical factors that may differentially impact treatment outcomes represents a sizeable step toward developing personalized treatments for MDD. Identified predictors should help guide the selection of initial treatments, and identify those patients most vulnerable to recurrence, who thus warrant maintenance or combination treatments to achieve and maintain wellness. Trial registration Clinicaltrials.gov Identifier: NCT00360399. Registered 02 AUG 2006. First patient randomized 09 FEB 2007.

  3. Ranked Conservation Opportunity Areas for Region 7 (ECO_RES.RANKED_OAS)

    Science.gov (United States)

    The RANKED_OAS are all the Conservation Opportunity Areas identified by MoRAP that have subsequently been ranked by patch size, landform representation, and the targeted land cover class (highest rank for conservation management = 1 [LFRANK_NOR]). The OAs designate areas with potential for forest or grassland conservation because they are areas of natural or semi-natural land cover that are at least 75 meters away from roads and away from patch edges. The OAs were modeled by creating distance grids using the National Land Cover Database and the Census Bureau's TIGER roads files.

  4. UNIVERSITY RANKINGS BY COST OF LIVING ADJUSTED FACULTY COMPENSATION

    OpenAIRE

    Terrance Jalbert; Mercedes Jalbert; Karla Hayashi

    2010-01-01

    In this paper we rank 574 universities based on compensation paid to their faculty. The analysis examines universities both on a raw basis and on a cost of living adjusted basis. Rankings based on salary data and benefit data are presented. In addition rankings based on total compensation are presented. Separate rankings are provided for universities offering different degrees. The results indicate that rankings of universities based on raw and cost of living adjusted data are markedly differ...

  5. A novel method predicting clinical response using only background clinical data in RA patients before treatment with infliximab.

    Science.gov (United States)

    Miyoshi, Fumihiko; Honne, Kyoko; Minota, Seiji; Okada, Masato; Ogawa, Noriyoshi; Mimura, Toshihide

    2016-11-01

    The aim of the present study was to generate a novel method for predicting the clinical response to infliximab (IFX), using a machine-learning algorithm with only clinical data obtained before the treatment in rheumatoid arthritis (RA) patients. We obtained 32 variables out of the clinical data on the patients from two independent hospitals. Next, we selected both clinical parameters and machine-learning algorithms and decided the candidates of prediction method. These candidates were verified by clinical variables on different patients from two other hospitals. Finally, we decided the prediction method to achieve the highest score. The combination of multilayer perceptron algorithm (neural network) and nine clinical parameters shows the best accuracy performance. This method could predict the good or moderate response to IFX with 92% accuracy. The sensitivity of this method was 96.7%, while the specificity was 75%. We have developed a novel method for predicting the clinical response using only background clinical data in RA patients before treatment with IFX. Our method for predicting the response to IFX in RA patients may have advantages over the other previous methods in several points including easy usability, cost-effectiveness and accuracy.

  6. Prediction model for adult height of small for gestational age children at the start of growth hormone treatment

    NARCIS (Netherlands)

    M.A.J. de Ridder (Maria); Th. Stijnen (Theo); A.C.S. Hokken-Koelega (Anita)

    2008-01-01

    textabstractContext: GH treatment is approved for short children born small for gestational age (SGA). The optimal dose is not yet established. Objective: Our objective was to develop a model for prediction of height at the onset of puberty and of adult height (AH). Design and Setting: Two GH

  7. Prediction model for adult height of small for gestational age children at the start of growth hormone treatment

    NARCIS (Netherlands)

    de Ridder, Maria A. J.; Stijnen, Theo; Hokken-Koelega, Anita C. S.

    Context: GH treatment is approved for short children born small for gestational age (SGA). The optimal dose is not yet established. Objective: Our objective was to develop a model for prediction of height at the onset of puberty and of adult height (AH). Design and Setting: Two GH studies were

  8. A predictive model of suitability for minimally invasive parathyroid surgery in the treatment of primary hyperparathyroidism [corrected].

    LENUS (Irish Health Repository)

    Kavanagh, Dara O

    2012-05-01

    Improved preoperative localizing studies have facilitated minimally invasive approaches in the treatment of primary hyperparathyroidism (PHPT). Success depends on the ability to reliably select patients who have PHPT due to single-gland disease. We propose a model encompassing preoperative clinical, biochemical, and imaging studies to predict a patient\\'s suitability for minimally invasive surgery.

  9. FDG-PET after two cycles of chemotherapy predicts treatment failure and progression-free survival in Hodgkin lymphoma

    DEFF Research Database (Denmark)

    Hutchings, Martin; Loft, Annika; Hansen, Mads

    2005-01-01

    Risk-adapted lymphoma treatment requires early and accurate assessment of prognosis. This investigation prospectively assessed the value of positron emission tomography with 2-[18F]fluoro-2-deoxy-D-glucose (FDG-PET) after two cycles of chemotherapy for prediction of progression-free survival (PFS...

  10. An Analysis of Document Category Prediction Responses to Classifier Model Parameter Treatment Permutations within the Software Design Patterns Subject Domain

    Science.gov (United States)

    Pankau, Brian L.

    2009-01-01

    This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

  11. GeneRank: using search engine technology for the analysis of microarray experiments.

    Science.gov (United States)

    Morrison, Julie L; Breitling, Rainer; Higham, Desmond J; Gilbert, David R

    2005-09-21

    Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  12. GeneRank: Using search engine technology for the analysis of microarray experiments

    Directory of Open Access Journals (Sweden)

    Breitling Rainer

    2005-09-01

    Full Text Available Abstract Background Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method – based on the PageRank algorithm employed by the popular search engine Google – that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. Results GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Conclusion Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  13. What factors predict individual subjects' re-learning of words during anomia treatment?

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    William Hayward

    2014-04-01

    Full Text Available A growing number of studies are addressing methodological approaches to treating anomia in persons with aphasia. What is missing from these studies are validated procedures for determining which words have the greatest potential for recovery. The current study evaluates the usefulness of several word-specific variables and one subject-specific measure in predicting success in re-learning problematic words. Methods: Two participants, YPR and ODH, presented with fluent aphasia and marked anomia. YPR’s Aphasia Quotient on the Western Aphasia Battery was 58.8; ODH’s AQ was 79.5. Stimuli were 96 pictures chosen individually for each participant from among those that they named incorrectly on multiple baselines. Subsequently, participants were presented with each picture and asked to indicate whether they could name it covertly, or “in their head.” Each subject completed a biweekly anomia treatment for these pictures. We performed separate statistical analyses for each subject. Dependent variables included whether each word was learned during treatment (Acquisition and the number of sessions required to learn each word (#Sessions. We used logistic regression models to evaluate the association of (self-reported covert naming success with Acquisition, and linear regression models to assess the relationship between (self-reported covert naming success and #Sessions. Starting with the predictors of covert naming accuracy, number of syllables (#syllables, number of phonemes (#phonemes, and frequency, we used backwards elimination methods to select the final regression models. Results: By the end of 25 treatment sessions, YPR had learned 90.2% (37/41 of the covertly correct words but only 70.4% (38/54 of the covertly incorrect words. In the unadjusted analysis, covert naming was significantly associated with Acquisition, OR=3.89, 95% CI: (1.19, 12.74, p=0.025. The result remained significant after adjustment for #phonemes (the only other predictor

  14. Prehospital evaluation and economic analysis of different coronary syndrome treatment strategies - PREDICT - Rationale, Development and Implementation

    Science.gov (United States)

    2011-01-01

    Background A standard of prehospital care for patients presenting with ST-segment elevation myocardial infarction (STEMI) includes prehospital 12-lead and advance Emergency Department notification or prehospital bypass to percutaneous coronary intervention centres. Implementation of either care strategies is variable across communities and neither may exist in some communities. The main objective is to compare prehospital care strategies for time to treatment and survival outcomes as well as cost effectiveness. Methods/Design PREDICT is a multicentre, prospective population-based cohort study of all chest pain patients 18 years or older presenting within 30 mins to 6 hours of symptom onset and treated with nitroglycerin, transported by paramedics in a number of different urban and rural regions in Ontario. The primary objective of this study is to compare the proportion of study subjects who receive reperfusion within the target door-to-reperfusion times in subjects obtained after four prehospital strategies: 12-lead ECG and advance emergency department (ED) notification or 3-lead ECG monitoring and alert to dispatch prior to hospital arrival; either with or without the opportunity to bypass to a PCI centre. Discussion We anticipate four challenges to successful study implementation and have developed strategies for each: 1) diversity in the interpretation of the ethical and privacy issues across 47 research ethics boards/commiittees covering 71 hospitals, 2) remote oversight of data guardian abstraction, 3) timeliness of implementation, and 4) potential interference in the study by concurrent technological advances. Research ethics approvals from academic centres were obtained initially and submitted to non academic centre applications. Data guardians were trained by a single investigator and data entry is informed by a detailed data dictionary including variable definitions and abstraction instrucations and subjected to error and logic checks. Quality oversight

  15. Prehospital evaluation and economic analysis of different coronary syndrome treatment strategies - PREDICT - Rationale, Development and Implementation

    Directory of Open Access Journals (Sweden)

    Craig Alan

    2011-03-01

    Full Text Available Abstract Background A standard of prehospital care for patients presenting with ST-segment elevation myocardial infarction (STEMI includes prehospital 12-lead and advance Emergency Department notification or prehospital bypass to percutaneous coronary intervention centres. Implementation of either care strategies is variable across communities and neither may exist in some communities. The main objective is to compare prehospital care strategies for time to treatment and survival outcomes as well as cost effectiveness. Methods/Design PREDICT is a multicentre, prospective population-based cohort study of all chest pain patients 18 years or older presenting within 30 mins to 6 hours of symptom onset and treated with nitroglycerin, transported by paramedics in a number of different urban and rural regions in Ontario. The primary objective of this study is to compare the proportion of study subjects who receive reperfusion within the target door-to-reperfusion times in subjects obtained after four prehospital strategies: 12-lead ECG and advance emergency department (ED notification or 3-lead ECG monitoring and alert to dispatch prior to hospital arrival; either with or without the opportunity to bypass to a PCI centre. Discussion We anticipate four challenges to successful study implementation and have developed strategies for each: 1 diversity in the interpretation of the ethical and privacy issues across 47 research ethics boards/commiittees covering 71 hospitals, 2 remote oversight of data guardian abstraction, 3 timeliness of implementation, and 4 potential interference in the study by concurrent technological advances. Research ethics approvals from academic centres were obtained initially and submitted to non academic centre applications. Data guardians were trained by a single investigator and data entry is informed by a detailed data dictionary including variable definitions and abstraction instrucations and subjected to error and logic

  16. The ability of early changes in motivation to predict later antidepressant treatment response

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    Gorwood P

    2015-11-01

    at inclusion in future nonresponders (t=1.25, df=1,563, P=0.10. Its improvement at Week 2 was the most discriminating MAThyS dimension between future responders and nonresponders, and represents the best predictor of future response, with the highest area under the receptor operating characteristic curve (area under curve =0.616, 95% confidence interval [0.588–0.643], P<0.001. Finally, improvements in motivation correlated the most strongly with clinician-rated 16-item quick inventory of depressive symptoms improvement (r=-0.491, df=1,563, P<0.001.Conclusion: Motivation had the most capacity for early improvement, the best predictive value for response, and the largest global margin of progress in depressed outpatients. Assessing the evolution of self-reported motivation over time in major depressive disorder could offer an interesting complementary approach to predict response.Keywords: depression, agomelatine, dimension, motivation, treatment response

  17. Near-Infrared Spectroscopy in Schizophrenia: A Possible Biomarker for Predicting Clinical Outcome and Treatment Response

    Science.gov (United States)

    Koike, Shinsuke; Nishimura, Yukika; Takizawa, Ryu; Yahata, Noriaki; Kasai, Kiyoto

    2013-01-01

    Functional near-infrared spectroscopy (fNIRS) is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions) compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography), fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and non-invasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an fNIRS community

  18. Near-infrared spectroscopy in schizophrenia: A possible biomarker for predicting clinical outcome and treatment response

    Directory of Open Access Journals (Sweden)

    Shinsuke eKoike

    2013-11-01

    Full Text Available Functional near-infrared spectroscopy (fNIRS is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography, fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and noninvasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an

  19. Near-infrared spectroscopy in schizophrenia: a possible biomarker for predicting clinical outcome and treatment response.

    Science.gov (United States)

    Koike, Shinsuke; Nishimura, Yukika; Takizawa, Ryu; Yahata, Noriaki; Kasai, Kiyoto

    2013-01-01

    Functional near-infrared spectroscopy (fNIRS) is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions) compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography), fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and non-invasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an fNIRS community.

  20. Evaluation of clinical and immunological markers for predicting virological failure in a HIV/AIDS treatment cohort in Busia, Kenya.

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    Cecilia Ferreyra

    Full Text Available BACKGROUND: In resource-limited settings where viral load (VL monitoring is scarce or unavailable, clinicians must use immunological and clinical criteria to define HIV virological treatment failure. This study examined the performance of World Health Organization (WHO clinical and immunological failure criteria in predicting virological failure in HIV patients receiving antiretroviral therapy (ART. METHODS: In a HIV/AIDS program in Busia District Hospital, Kenya, a retrospective, cross-sectional cohort analysis was performed in April 2008 for all adult patients (>18 years old on ART for ≥12 months, treatment-naive at ART start, attending the clinic at least once in last 6 months, and who had given informed consent. Treatment failure was assessed per WHO clinical (disease stage 3 or 4 and immunological (CD4 cell count criteria, and compared with virological failure (VL >5,000 copies/mL. RESULTS: Of 926 patients, 123 (13.3% had clinically defined treatment failure, 53 (5.7% immunologically defined failure, and 55 (6.0% virological failure. Sensitivity, specificity, positive predictive value, and negative predictive value of both clinical and immunological criteria (combined in predicting virological failure were 36.4%, 83.5%, 12.3%, and 95.4%, respectively. CONCLUSIONS: In this analysis, clinical and immunological criteria were found to perform relatively poorly in predicting virological failure of ART. VL monitoring and new algorithms for assessing clinical or immunological treatment failure, as well as improved adherence strategies, are required in ART programs in resource-limited settings.