Automatic single- and multi-label enzymatic function prediction by machine learning

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Shervine Amidi

2017-03-01

Full Text Available The number of protein structures in the PDB database has been increasing more than 15-fold since 1999. The creation of computational models predicting enzymatic function is of major importance since such models provide the means to better understand the behavior of newly discovered enzymes when catalyzing chemical reactions. Until now, single-label classification has been widely performed for predicting enzymatic function limiting the application to enzymes performing unique reactions and introducing errors when multi-functional enzymes are examined. Indeed, some enzymes may be performing different reactions and can hence be directly associated with multiple enzymatic functions. In the present work, we propose a multi-label enzymatic function classification scheme that combines structural and amino acid sequence information. We investigate two fusion approaches (in the feature level and decision level and assess the methodology for general enzymatic function prediction indicated by the first digit of the enzyme commission (EC code (six main classes on 40,034 enzymes from the PDB database. The proposed single-label and multi-label models predict correctly the actual functional activities in 97.8% and 95.5% (based on Hamming-loss of the cases, respectively. Also the multi-label model predicts all possible enzymatic reactions in 85.4% of the multi-labeled enzymes when the number of reactions is unknown. Code and datasets are available at https://figshare.com/s/a63e0bafa9b71fc7cbd7.

Composition and predicted functional ecology of mussel - associated bacteria in Indonesian marine lakes

NARCIS (Netherlands)

Cleary, D.F.R.; Becking, L.E.; Polonia, A.; Freitas, R.M.; Gomes, N.

2015-01-01

In the present study, we sampled bacterial communities associated with mussels inhabiting two distinct coastal marine ecosystems in Kalimantan, Indonesia, namely, marine lakes and coastal mangroves. We used 16S rRNA gene pyrosequencing and predicted metagenomic analysis to compare microbial

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

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Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

Predicting Protein Function via Semantic Integration of Multiple Networks.

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Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

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Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-01

For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease

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Qi Lin

2018-04-01

Full Text Available Resting-state functional connectivity (rs-FC is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11 scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

Implicit and Explicit Associations with Erotic Stimuli in Sexually Functional and Dysfunctional Men.

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van Lankveld, Jacques; Odekerken, Ingrid; Kok-Verhoeven, Lydia; van Hooren, Susan; de Vries, Peter; van den Hout, Anja; Verboon, Peter

2015-08-01

Although conceptual models of sexual functioning have suggested a major role for implicit cognitive processing in sexual functioning, this has thus far, only been investigated in women. The aim of this study was to investigate the role of implicit cognition in sexual functioning in men. Men with (N = 29) and without sexual dysfunction (N = 31) were compared. Participants performed two single-target implicit association tests (ST-IAT), measuring the implicit association of visual erotic stimuli with attributes representing, respectively, valence ('liking') and motivation ('wanting'). Participants also rated the erotic pictures that were shown in the ST-IAT on the dimensions of valence, attractiveness, and sexual excitement to assess their explicit associations with these erotic stimuli. Participants completed the International Index of Erectile Functioning for a continuous measure of sexual functioning. Unexpectedly, compared with sexually functional men, sexually dysfunctional men were found to show stronger implicit associations of erotic stimuli with positive valence than with negative valence. Level of sexual functioning, however, was not predicted by explicit nor implicit associations. Level of sexual distress was predicted by explicit valence ratings, with positive ratings predicting higher levels of sexual distress. Men with and without sexual dysfunction differed significantly with regard to implicit liking. Research recommendations and implications are discussed. © 2015 International Society for Sexual Medicine.

Integration of relational and hierarchical network information for protein function prediction

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Jiang Xiaoyu

2008-08-01

Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

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Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Weaknesses in executive functioning predict the initiating of adolescents' alcohol use.

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Peeters, Margot; Janssen, Tim; Monshouwer, Karin; Boendermaker, Wouter; Pronk, Thomas; Wiers, Reinout; Vollebergh, Wilma

2015-12-01

Recently, it has been suggested that impairments in executive functioning might be risk factors for the onset of alcohol use rather than a result of heavy alcohol use. In the present study, we examined whether two aspects of executive functioning, working memory and response inhibition, predicted the first alcoholic drink and first binge drinking episode in young adolescents using discrete survival analyses. Adolescents were selected from several Dutch secondary schools including both mainstream and special education (externalizing behavioral problems). Participants were 534 adolescents between 12 and 14 years at baseline. Executive functioning and alcohol use were assessed four times over a period of two years. Working memory uniquely predicted the onset of first drink (p=.01) and first binge drinking episode (p=.04) while response inhibition only uniquely predicted the initiating of the first drink (p=.01). These results suggest that the association of executive functioning and alcohol consumption found in former studies cannot simply be interpreted as an effect of alcohol consumption, as weaknesses in executive functioning, found in alcohol naïve adolescents, predict the initiating of (binge) drinking. Though, prolonged and heavy alcohol use might further weaken already existing deficiencies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

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Zhili He

2018-02-01

Full Text Available Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN, representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5 increased significantly (P < 0.05 as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.

An integrative approach to ortholog prediction for disease-focused and other functional studies.

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Hu, Yanhui; Flockhart, Ian; Vinayagam, Arunachalam; Bergwitz, Clemens; Berger, Bonnie; Perrimon, Norbert; Mohr, Stephanie E

2011-08-31

Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt), for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM) and genes in genome-wide association study (GWAS) data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist). DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

Cardiac structure and function predicts functional decline in the oldest old.

Science.gov (United States)

Leibowitz, David; Jacobs, Jeremy M; Lande-Stessman, Irit; Gilon, Dan; Stessman, Jochanan

2018-02-01

Background This study examined the association between cardiac structure and function and the deterioration in activities of daily living (ADLs) in an age-homogenous, community-dwelling population of patients born in 1920-1921 over a five-year follow-up period. Design Longitudinal cohort study. Methods Patients were recruited from the Jerusalem Longitudinal Cohort Study, which has followed an age-homogenous cohort of Jerusalem residents born in 1920-1921. Patients underwent home echocardiography and were followed up for five years. Dependence was defined as needing assistance with one or more basic ADL. Standard echocardiographic assessment of cardiac structure and function, including systolic and diastolic function, was performed. Reassessment of ADLs was performed at the five-year follow-up. Results A total of 459 patients were included in the study. Of these, 362 (79%) showed a deterioration in at least one ADL at follow-up. Patients with functional deterioration had a significantly higher left ventricular mass index and left atrial volume with a lower ejection fraction. There was no significant difference between the diastolic parameters the groups in examined. When the data were examined categorically, a significantly larger percentage of patients with functional decline had an abnormal left ventricular ejection fraction and left ventricular hypertrophy. The association between left ventricular mass index and functional decline remained significant in all multivariate models. Conclusions In this cohort of the oldest old, an elevated left ventricular mass index, higher left atrial volumes and systolic, but not diastolic dysfunction, were predictive of functional disability.

GIMDA: Graphlet interaction-based MiRNA-disease association prediction.

Science.gov (United States)

Chen, Xing; Guan, Na-Na; Li, Jian-Qiang; Yan, Gui-Ying

2018-03-01

MicroRNAs (miRNAs) have been confirmed to be closely related to various human complex diseases by many experimental studies. It is necessary and valuable to develop powerful and effective computational models to predict potential associations between miRNAs and diseases. In this work, we presented a prediction model of Graphlet Interaction for MiRNA-Disease Association prediction (GIMDA) by integrating the disease semantic similarity, miRNA functional similarity, Gaussian interaction profile kernel similarity and the experimentally confirmed miRNA-disease associations. The related score of a miRNA to a disease was calculated by measuring the graphlet interactions between two miRNAs or two diseases. The novelty of GIMDA lies in that we used graphlet interaction to analyse the complex relationships between two nodes in a graph. The AUCs of GIMDA in global and local leave-one-out cross-validation (LOOCV) turned out to be 0.9006 and 0.8455, respectively. The average result of five-fold cross-validation reached to 0.8927 ± 0.0012. In case study for colon neoplasms, kidney neoplasms and prostate neoplasms based on the database of HMDD V2.0, 45, 45, 41 of the top 50 potential miRNAs predicted by GIMDA were validated by dbDEMC and miR2Disease. Additionally, in the case study of new diseases without any known associated miRNAs and the case study of predicting potential miRNA-disease associations using HMDD V1.0, there were also high percentages of top 50 miRNAs verified by the experimental literatures. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

An integrative approach to ortholog prediction for disease-focused and other functional studies

Directory of Open Access Journals (Sweden)

Perrimon Norbert

2011-08-01

Full Text Available Abstract Background Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. Results We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt, for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM and genes in genome-wide association study (GWAS data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist. Conclusions DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

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

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Yiming Hu

2017-06-01

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

Predicting functional recovery after acute ankle sprain.

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Sean R O'Connor

Full Text Available Ankle sprains are among the most common acute musculoskeletal conditions presenting to primary care. Their clinical course is variable but there are limited recommendations on prognostic factors. Our primary aim was to identify clinical predictors of short and medium term functional recovery after ankle sprain.A secondary analysis of data from adult participants (N = 85 with an acute ankle sprain, enrolled in a randomized controlled trial was undertaken. The predictive value of variables (age, BMI, gender, injury mechanism, previous injury, weight-bearing status, medial joint line pain, pain during weight-bearing dorsiflexion and lateral hop test recorded at baseline and at 4 weeks post injury were investigated for their prognostic ability. Recovery was determined from measures of subjective ankle function at short (4 weeks and medium term (4 months follow ups. Multivariate stepwise linear regression analyses were undertaken to evaluate the association between the aforementioned variables and functional recovery.Greater age, greater injury grade and weight-bearing status at baseline were associated with lower function at 4 weeks post injury (p<0.01; adjusted R square=0.34. Greater age, weight-bearing status at baseline and non-inversion injury mechanisms were associated with lower function at 4 months (p<0.01; adjusted R square=0.20. Pain on medial palpation and pain on dorsiflexion at 4 weeks were the most valuable prognostic indicators of function at 4 months (p< 0.01; adjusted R square=0.49.The results of the present study provide further evidence that ankle sprains have a variable clinical course. Age, injury grade, mechanism and weight-bearing status at baseline provide some prognostic information for short and medium term recovery. Clinical assessment variables at 4 weeks were the strongest predictors of recovery, explaining 50% of the variance in ankle function at 4 months. Further prospective research is required to highlight the factors

Associations and predictions of readmission or death in acutely admitted older medical patients using self-reported frailty and functional measures. A Danish cohort study

DEFF Research Database (Denmark)

Andreasen, Jane; Aadahl, Mette; Sørensen, Erik Elgaard

2018-01-01

OBJECTIVE: To assess whether frailty in acutely admitted older medical patients, assessed by a self-report questionnaire and evaluation of functional level at discharge, was associated with readmission or death within 6 months after discharge. A second objective was to assess the predictive...... measured. Associations were assessed using Cox regression with first unplanned readmission or death (all-causes) as the outcome. Prediction models including the three exposure variables and known risk factors were modelled using logistic regression and C-statistics. RESULTS: Of 1328 included patients, 50......% were readmitted or died within 6 months. When adjusted for gender and age, there was an 88% higher risk of readmission or death if the TFI scores were 8-13 points compared to 0-1 points (HR 1.88, CI 1.38;2.58). Likewise, higher TUG and lower GS scores were associated with higher risk of readmission...

Habitual fat intake predicts memory function in younger women

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Edward Leigh eGibson

2013-12-01

Full Text Available High intakes of fat have been linked to greater cognitive decline in old age, but such associations may already occur in younger adults. We tested memory and learning in 38 women (25-45 years old, recruited for a larger observational study in women with polycystic ovary syndrome. These women varied in health status, though not significantly between cases (n=23 and controls (n=15. Performance on tests sensitive to medial temporal lobe function (CANTABeclipse, Cambridge Cognition Ltd., i.e. verbal memory, visuo-spatial learning and delayed pattern matching, were compared with intakes of macronutrients from 7-day diet diaries and physiological indices of metabolic syndrome. Partial correlations were adjusted for age, activity and verbal IQ (National Adult Reading Test. Greater intakes of saturated and trans fats, and higher saturated to unsaturated fat ratio (Sat:UFA, were associated with more errors on the visuo-spatial task and with poorer word recall and recognition. Unexpectedly, higher UFA intake predicted poorer performance on the word recall and recognition measures. Fasting insulin was positively correlated with poorer word recognition only, whereas higher blood total cholesterol was associated only with visuo-spatial learning errors. None of these variables predicted performance on a delayed pattern matching test. The significant nutrient-cognition relationships were tested for mediation by total energy intake: saturated and trans fat intakes, and Sat:UFA, remained significant predictors specifically of visuo-spatial learning errors, whereas total fat and UFA intakes now predicted only poorer word recall. Examination of associations separately for mono- (MUFA and polyunsaturated fats suggested that only MUFA intake was predictive of poorer word recall. Saturated and trans fats, and fasting insulin, may already be associated with cognitive deficits in younger women. The findings need extending but may have important implications for public

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Predictive pulmonary-function value calculator... SERVICES (CONTINUED) MEDICAL DEVICES ANESTHESIOLOGY DEVICES Diagnostic Devices § 868.1890 Predictive pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze

2015-06-09

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

2015-01-01

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Computational prediction of drug-drug interactions based on drugs functional similarities.

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Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

2017-06-01

Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

Prediction Error During Functional and Non-Functional Action Sequences

DEFF Research Database (Denmark)

Nielbo, Kristoffer Laigaard; Sørensen, Jesper

2013-01-01

recurrent networks were made and the results are presented in this article. The simulations show that non-functional action sequences do indeed increase prediction error, but that context representations, such as abstract goal information, can modulate the error signal considerably. It is also shown...... that the networks are sensitive to boundaries between sequences in both functional and non-functional actions....

Prediction of human protein function from post-translational modifications and localization features

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Blom, Nikolaj

2002-01-01

a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects......We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from...

The function and failure of sensory predictions.

Science.gov (United States)

Bansal, Sonia; Ford, Judith M; Spering, Miriam

2018-04-23

Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Science.gov (United States)

Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

2018-01-01

ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

Association Between Brain Activation and Functional Connectivity.

Science.gov (United States)

Tomasi, Dardo; Volkow, Nora D

2018-04-13

The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

Emotion suppression moderates the quadratic association between RSA and executive function.

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Spangler, Derek P; Bell, Martha Ann; Deater-Deckard, Kirby

2015-09-01

There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated (a) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (b) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a 2-min resting period during which electrocardiogram (ECG) was continually assessed. In the next phase, the women completed an array of executive function and nonexecutive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. © 2015 Society for Psychophysiological Research.

Towards Predictive Association Theories

DEFF Research Database (Denmark)

Kontogeorgis, Georgios; Tsivintzelis, Ioannis; Michelsen, Michael Locht

2011-01-01

Association equations of state like SAFT, CPA and NRHB have been previously applied to many complex mixtures. In this work we focus on two of these models, the CPA and the NRHB equations of state and the emphasis is on the analysis of their predictive capabilities for a wide range of applications....... We use the term predictive in two situations: (i) with no use of binary interaction parameters, and (ii) multicomponent calculations using binary interaction parameters based solely on binary data. It is shown that the CPA equation of state can satisfactorily predict CO2–water–glycols–alkanes VLE...

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. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Idiopathic Pulmonary Fibrosis: Gender-Age-Physiology Index Stage for Predicting Future Lung Function Decline.

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Salisbury, Margaret L; Xia, Meng; Zhou, Yueren; Murray, Susan; Tayob, Nabihah; Brown, Kevin K; Wells, Athol U; Schmidt, Shelley L; Martinez, Fernando J; Flaherty, Kevin R

2016-02-01

Idiopathic pulmonary fibrosis is a progressive lung disease with variable course. The Gender-Age-Physiology (GAP) Index and staging system uses clinical variables to stage mortality risk. It is unknown whether clinical staging predicts future decline in pulmonary function. We assessed whether the GAP stage predicts future pulmonary function decline and whether interval pulmonary function change predicts mortality after accounting for stage. Patients with idiopathic pulmonary fibrosis (N = 657) were identified retrospectively at three tertiary referral centers, and baseline GAP stages were assessed. Mixed models were used to describe average trajectories of FVC and diffusing capacity of the lung for carbon monoxide (Dlco). Multivariable Cox proportional hazards models were used to assess whether declines in pulmonary function ≥ 10% in 6 months predict mortality after accounting for GAP stage. Over a 2-year period, GAP stage was not associated with differences in yearly lung function decline. After accounting for stage, a 10% decrease in FVC or Dlco over 6 months independently predicted death or transplantation (FVC hazard ratio, 1.37; Dlco hazard ratio, 1.30; both, P ≤ .03). Patients with GAP stage 2 with declining pulmonary function experienced a survival profile similar to patients with GAP stage 3, with 1-year event-free survival of 59.3% (95% CI, 49.4-67.8) vs 56.9% (95% CI, 42.2-69.1). Baseline GAP stage predicted death or lung transplantation but not the rate of future pulmonary function decline. After accounting for GAP stage, a decline of ≥ 10% over 6 months independently predicted death or lung transplantation. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Functional status and mortality prediction in community-acquired pneumonia.

Science.gov (United States)

Jeon, Kyeongman; Yoo, Hongseok; Jeong, Byeong-Ho; Park, Hye Yun; Koh, Won-Jung; Suh, Gee Young; Guallar, Eliseo

2017-10-01

Poor functional status (FS) has been suggested as a poor prognostic factor in both pneumonia and severe pneumonia in elderly patients. However, it is still unclear whether FS is associated with outcomes and improves survival prediction in community-acquired pneumonia (CAP) in the general population. Data on hospitalized patients with CAP and FS, assessed by the Eastern Cooperative Oncology Group (ECOG) scale were prospectively collected between January 2008 and December 2012. The independent association of FS with 30-day mortality in CAP patients was evaluated using multivariable logistic regression. Improvement in mortality prediction when FS was added to the CRB-65 (confusion, respiratory rate, blood pressure and age 65) score was evaluated for discrimination, reclassification and calibration. The 30-day mortality of study participants (n = 1526) was 10%. Mortality significantly increased with higher ECOG score (P for trend <0.001). In multivariable analysis, ECOG ≥3 was strongly associated with 30-day mortality (adjusted OR: 5.70; 95% CI: 3.82-8.50). Adding ECOG ≥3 significantly improved the discriminatory power of CRB-65. Reclassification indices also confirmed the improvement in discrimination ability when FS was combined with the CRB-65, with a categorized net reclassification index (NRI) of 0.561 (0.437-0.686), a continuous NRI of 0.858 (0.696-1.019) and a relative integrated discrimination improvement in the discrimination slope of 139.8 % (110.8-154.6). FS predicted 30-day mortality and improved discrimination and reclassification in consecutive CAP patients. Assessment of premorbid FS should be considered in mortality prediction in patients with CAP. © 2017 Asian Pacific Society of Respirology.

Endothelial function predicts progression of carotid intima-media thickness

DEFF Research Database (Denmark)

Halcox, J.P.; Donald, A.E.; Ellins, E.

2009-01-01

significant after adjustment for risk factors whether entered as separate variables or as Framingham Risk Score. Further adjustment for waist circumference, triglycerides, and employment grade had no significant effect. CONCLUSIONS: Systemic endothelial function was associated with progression of preclinical...... to its impact on the evolution of the atherosclerotic substrate. Flow-mediated dilatation testing provides an integrated vascular measure that may aid the prediction of structural disease evolution and represents a potential short- to intermediate-term outcome measure for evaluation of preventive...

Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

Science.gov (United States)

Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

2011-01-01

To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value Stroke Scale; β = 0.402, p stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

Science.gov (United States)

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa.

Science.gov (United States)

DeGuzman, Marisa; Shott, Megan E; Yang, Tony T; Riederer, Justin; Frank, Guido K W

2017-06-01

Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Female adolescents with anorexia nervosa (N=21; mean age, 16.4 years [SD=1.9]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 15.2 years [SD=2.4]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs.

ANGDelMut – a web-based tool for predicting and analyzing functional loss mechanisms of amyotrophic lateral sclerosis-associated angiogenin mutations [v2; ref status: indexed, http://f1000r.es/2mc

Directory of Open Access Journals (Sweden)

Aditya K Padhi

2013-12-01

Full Text Available ANGDelMut is a web-based tool for predicting the functional consequences of missense mutations in the angiogenin (ANG protein, which is associated with amyotrophic lateral sclerosis (ALS. Missense mutations in ANG result in loss of either ribonucleolytic activity or nuclear translocation activity or both of these functions, and in turn cause ALS. However, no web-based tools are available to predict whether a newly identified ANG mutation will possibly lead to ALS. More importantly, no web-implemented method is currently available to predict the mechanisms of loss-of-function(s of ANG mutants. In light of this observation, we developed the ANGDelMut web-based tool, which predicts whether an ANG mutation is deleterious or benign. The user selects certain attributes from the input panel, which serves as a query to infer whether a mutant will exhibit loss of ribonucleolytic activity or nuclear translocation activity or whether the overall stability will be affected. The output states whether the mutation is deleterious or benign, and if it is deleterious, gives the possible mechanism(s of loss-of-function. This web-based tool, freely available at http://bioschool.iitd.ernet.in/DelMut/, is the first of its kind to provide a platform for researchers and clinicians, to infer the functional consequences of ANG mutations and correlate their possible association with ALS ahead of experimental findings.

ANGDelMut – a web-based tool for predicting and analyzing functional loss mechanisms of amyotrophic lateral sclerosis-associated angiogenin mutations [v3; ref status: indexed, http://f1000r.es/2yt

Directory of Open Access Journals (Sweden)

Aditya K Padhi

2014-02-01

Full Text Available ANGDelMut is a web-based tool for predicting the functional consequences of missense mutations in the angiogenin (ANG protein, which is associated with amyotrophic lateral sclerosis (ALS. Missense mutations in ANG result in loss of either ribonucleolytic activity or nuclear translocation activity or both of these functions, and in turn cause ALS. However, no web-based tools are available to predict whether a newly identified ANG mutation will possibly lead to ALS. More importantly, no web-implemented method is currently available to predict the mechanisms of loss-of-function(s of ANG mutants. In light of this observation, we developed the ANGDelMut web-based tool, which predicts whether an ANG mutation is deleterious or benign. The user selects certain attributes from the input panel, which serves as a query to infer whether a mutant will exhibit loss of ribonucleolytic activity or nuclear translocation activity or whether the overall stability will be affected. The output states whether the mutation is deleterious or benign, and if it is deleterious, gives the possible mechanism(s of loss-of-function. This web-based tool, freely available at http://bioschool.iitd.ernet.in/DelMut/, is the first of its kind to provide a platform for researchers and clinicians, to infer the functional consequences of ANG mutations and correlate their possible association with ALS ahead of experimental findings.

SitesIdentify: a protein functional site prediction tool

Directory of Open Access Journals (Sweden)

Doig Andrew J

2009-11-01

Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

Energy Technology Data Exchange (ETDEWEB)

Polegato, Bertha F.; Minicucci, Marcos F.; Azevedo, Paula S.; Gonçalves, Andréa F.; Lima, Aline F.; Martinez, Paula F.; Okoshi, Marina P.; Okoshi, Katashi; Paiva, Sergio A. R.; Zornoff, Leonardo A. M., E-mail: lzornoff@fmb.unesp.br [Faculdade de Medicina de Botucatu - Universidade Estadual Paulista ' Júlio de mesquita Filho' - UNESP Botucatu, SP (Brazil)

2016-02-15

Heart failure prediction after acute myocardial infarction may have important clinical implications. To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset.

Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

International Nuclear Information System (INIS)

Polegato, Bertha F.; Minicucci, Marcos F.; Azevedo, Paula S.; Gonçalves, Andréa F.; Lima, Aline F.; Martinez, Paula F.; Okoshi, Marina P.; Okoshi, Katashi; Paiva, Sergio A. R.; Zornoff, Leonardo A. M.

2016-01-01

Heart failure prediction after acute myocardial infarction may have important clinical implications. To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset

Models for predicting objective function weights in prostate cancer IMRT

International Nuclear Information System (INIS)

Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

2015-01-01

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Models for predicting objective function weights in prostate cancer IMRT

Energy Technology Data Exchange (ETDEWEB)

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)

2015-04-15

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Functional Associations by Response Overlap (FARO, a functional genomics approach matching gene expression phenotypes.

Directory of Open Access Journals (Sweden)

Henrik Bjørn Nielsen

2007-08-01

Full Text Available The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving 'Functional Association(s by Response Overlap' (FARO between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our

Lifestyle Markers Predict Cognitive Function.

Science.gov (United States)

Masley, Steven C; Roetzheim, Richard; Clayton, Gwendolyn; Presby, Angela; Sundberg, Kelley; Masley, Lucas V

2017-01-01

Rates of mild cognitive impairment and Alzheimer's disease are increasing rapidly. None of the current treatment regimens for Alzheimer's disease are effective in arresting progression. Lifestyle choices may prevent cognitive decline. This study aims to clarify which factors best predict cognitive function. This was a prospective cross-sectional analysis of 799 men and women undergoing health and cognitive testing every 1 to 3 years at an outpatient center. This study utilizes data collected from the first patient visit. Participant ages were 18 to 88 (mean = 50.7) years and the sample was 26.6% female and 73.4% male. Measurements were made of body composition, fasting laboratory and anthropometric measures, strength and aerobic fitness, nutrient and dietary intake, and carotid intimal media thickness (IMT). Each participant was tested with a computerized neurocognitive test battery. Cognitive outcomes were assessed in bivariate analyses using t-tests and correlation coefficients and in multivariable analysis (controlling for age) using multiple linear regression. The initial bivariate analyses showed better Neurocognitive Index (NCI) scores with lower age, greater fitness scores (push-up strength, VO 2 max, and exercise duration during treadmill testing), and lower fasting glucose levels. Better cognitive flexibility scores were also noted with younger age, lower systolic blood pressure, lower body fat, lower carotid IMT scores, greater fitness, and higher alcohol intake. After controlling for age, factors that remained associated with better NCI scores include no tobacco use, lower fasting glucose levels, and better fitness (aerobic and strength). Higher cognitive flexibility scores remained associated with greater aerobic and strength fitness, lower body fat, and higher intake of alcohol. Modifiable biomarkers that impact cognitive performance favorably include greater aerobic fitness and strength, lower blood sugar levels, greater alcohol intake, lower body

Higher-order predictions for splitting functions and coefficient functions from physical evolution kernels

International Nuclear Information System (INIS)

Vogt, A; Soar, G.; Vermaseren, J.A.M.

2010-01-01

We have studied the physical evolution kernels for nine non-singlet observables in deep-inelastic scattering (DIS), semi-inclusive e + e - annihilation and the Drell-Yan (DY) process, and for the flavour-singlet case of the photon- and heavy-top Higgs-exchange structure functions (F 2 , F φ ) in DIS. All known contributions to these kernels show an only single-logarithmic large-x enhancement at all powers of (1-x). Conjecturing that this behaviour persists to (all) higher orders, we have predicted the highest three (DY: two) double logarithms of the higher-order non-singlet coefficient functions and of the four-loop singlet splitting functions. The coefficient-function predictions can be written as exponentiations of 1/N-suppressed contributions in Mellin-N space which, however, are less predictive than the well-known exponentiation of the ln k N terms. (orig.)

Physical Performance Is Associated with Executive Functioning in Older African American Women

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Brooke C. Schneider

2011-01-01

Full Text Available An older adult's ability to perform physical tasks is predictive of disability onset and is associated with declines in cognition. Risk factors for physical performance declines among African Americans, a group with the highest rates of disability, remain understudied. This study sought to identify demographic, health, and cognitive factors associated with lower-extremity physical performance in a sample of 106 African American women ages 56 to 91. After controlling for global cognitive functioning (Mini Mental State Exam, physical performance was associated with executive functioning (Stroop Color/Word, but not visuospatial construction (WASI Block Design or processing speed (Trail Making Test, Part A. Executive functioning remained associated with physical performance after entry of demographic variables, exercise, depression, disease burden, and body mass index (BMI. Age, and BMI were also significant in this model. Executive functioning, age and BMI are associated with lower-extremity physical performance among older African American women.

Predicting individual brain maturity using dynamic functional connectivity

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Jian eQin

2015-07-01

Full Text Available Neuroimaging-based functional connectivity (FC analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI (n=183, ages 7-30 and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains.

Bioinformatic prediction and functional characterization of human KIAA0100 gene

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He Cui

2017-02-01

Full Text Available Our previous study demonstrated that human KIAA0100 gene was a novel acute monocytic leukemia-associated antigen (MLAA gene. But the functional characterization of human KIAA0100 gene has remained unknown to date. Here, firstly, bioinformatic prediction of human KIAA0100 gene was carried out using online softwares; Secondly, Human KIAA0100 gene expression was downregulated by the clustered regularly interspaced short palindromic repeats (CRISPR/CRISPR-associated (Cas 9 system in U937 cells. Cell proliferation and apoptosis were next evaluated in KIAA0100-knockdown U937 cells. The bioinformatic prediction showed that human KIAA0100 gene was located on 17q11.2, and human KIAA0100 protein was located in the secretory pathway. Besides, human KIAA0100 protein contained a signalpeptide, a transmembrane region, three types of secondary structures (alpha helix, extended strand, and random coil , and four domains from mitochondrial protein 27 (FMP27. The observation on functional characterization of human KIAA0100 gene revealed that its downregulation inhibited cell proliferation, and promoted cell apoptosis in U937 cells. To summarize, these results suggest human KIAA0100 gene possibly comes within mitochondrial genome; moreover, it is a novel anti-apoptotic factor related to carcinogenesis or progression in acute monocytic leukemia, and may be a potential target for immunotherapy against acute monocytic leukemia.

COPRED: prediction of fold, GO molecular function and functional residues at the domain level.

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López, Daniel; Pazos, Florencio

2013-07-15

Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked. COPRED can be freely accessed at http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein 3D structures. The website includes a detailed help section and usage examples. pazos@cnb.csic.es.

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

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

2017-05-01

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

A path-based measurement for human miRNA functional similarities using miRNA-disease associations

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Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

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Sabbath, Erika; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-01-01

Background Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control, and their combination during working life predicted post-retirement performance on eight cognitive tests. Methods We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2,149). Psychosocial job characteristics were measured on average four years before retirement using Karasek’s Job Content Questionnaire (job demands, job control, demand-control combinations). We tested associations between these exposures and post-retirement performance on tests of executive function, visual-motor speed, psycho-motor speed, verbal memory, and verbal fluency using OLS regression. Results Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency, and semantic fluency after retirement (p’scognitive domains. In addition to work stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. PMID:27188277

GAPIT: genome association and prediction integrated tool.

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Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Identification of antibody glycosylation structures that predict monoclonal antibody Fc-effector function.

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Chung, Amy W; Crispin, Max; Pritchard, Laura; Robinson, Hannah; Gorny, Miroslaw K; Yu, Xiaojie; Bailey-Kellogg, Chris; Ackerman, Margaret E; Scanlan, Chris; Zolla-Pazner, Susan; Alter, Galit

2014-11-13

To determine monoclonal antibody (mAb) features that predict fragment crystalizable (Fc)-mediated effector functions against HIV. Monoclonal antibodies, derived from Chinese hamster ovary cells or Epstein-Barr virus-immortalized mouse heteromyelomas, with specificity to key regions of the HIV envelope including gp120-V2, gp120-V3 loop, gp120-CD4(+) binding site, and gp41-specific antibodies, were functionally profiled to determine the relative contribution of the variable and constant domain features of the antibodies in driving robust Fc-effector functions. Each mAb was assayed for antibody-binding affinity to gp140(SR162), antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP) and for the ability to bind to FcγRIIa, FcγRIIb and FcγRIIIa receptors. Antibody glycan profiles were determined by HPLC. Neither the specificity nor the affinity of the mAbs determined the potency of Fc-effector function. FcγRIIIa binding strongly predicted ADCC and decreased galactose content inversely correlated with ADCP, whereas N-glycolylneuraminic acid-containing structures exhibited enhanced ADCP. Additionally, the bi-antenary glycan arm onto which galactose was added predicted enhanced binding to FcγRIIIa and ADCC activity, independent of the specificity of the mAb. Our studies point to the specific Fc-glycan structures that can selectively promote Fc-effector functions independently of the antibody specificity. Furthermore, we demonstrated antibody glycan structures associated with enhanced ADCP activity, an emerging Fc-effector function that may aid in the control and clearance of HIV infection.

Clinical symptoms predict concurrent social and global functioning in an early psychosis sample.

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Cacciotti-Saija, Cristina; Langdon, Robyn; Ward, Philip B; Hickie, Ian B; Guastella, Adam J

2018-04-01

Although well established in chronic schizophrenia, the key determinants of functioning remain unknown during the early phase of a psychotic disorder. The aim of this study was to comprehensively examine the social cognitive, basic neurocognitive and clinical predictors of concurrent social functioning and global functioning in an early psychosis sample. This study examined the relationship between social cognition, basic neurocognition and clinical symptoms with concurrent functioning in 51 early psychosis individuals. Assessments included a range of self-report, observational and clinician-rated measures of cognitive, symptom severity and functioning domains. Results revealed a significant association between self-reported social function and lower levels of both social interaction anxiety and negative psychotic symptoms. A significant association was also observed between lower levels of negative psychotic symptoms and observed social functioning. Lastly, results demonstrated a significant association between reduced negative psychotic symptoms and clinician-rated global functioning. Clinical domains such as negative symptoms and social interaction anxiety significantly contribute to an optimal model predicting outcome during the early phase of a psychotic disorder. These clinical features may also provide useful markers of an individual's capacity for social participation. Clinical implications include the need for early targeted intervention to address social anxiety and negative psychotic symptoms to facilitate optimum patient outcome. © 2015 Wiley Publishing Asia Pty Ltd.

QCD dipole predictions for DIS and diffractive structure functions

International Nuclear Information System (INIS)

Royon, C.

1997-01-01

The proton structure function F 2 , the gluon density F G , and the longitudinal structure function F L are derived in the QCD dipole picture of BFKL dynamics. We use a three parameter fit to describe the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed within the same framework, and a new prediction for the proton diffractive structure function is obtained

[Predictive factors associated with severity of asthma exacerbations].

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Atiş, Sibel; Kaplan, Eylem Sercan; Ozge, Cengiz; Bayindir, Suzan

2008-01-01

Several factors have been accused for asthma exacerbations, however, very few studies have evaluated whether different factors predict severity of asthma exacerbation. We aimed to determine the predictive factors for severity of asthma exacerbation. Retrospective analysis of data on 93 patients visited our emergency-department because of asthma exacerbation was reviewed. Hospitalization in intensive care unit and/or intubation because of asthma was accepted as the criteria for severe exacerbation. Logistic regression analysis estimated the strength of association of each variable, potentially related to severe asthmatic exacerbation, with severe/very severe as compared to mild/moderate asthmatic exacerbation. Independent variables included in the analysis were age, sex, smoking history, inhaler steroid using, compliance with medication, chronic asthma severity, presence of additional atopic diseases, prick test positivity, provocative factors, number of short-acting beta(2)-agonist using, number of visits to emergency department for asthma over one year period, previous severe exacerbation, pulmonary functions, and blood eosinophil count. 20 were severe/very severe and 73 mild/moderate asthmatic exacerbation. Frequent using of short-acting beta(2)-agonist (OR= 1.5, 95% CI= 1.08-5.3, p= 0.003), noncompliance with medication (OR= 3.6, 95% CI= 1.3-9.9, p= 0.013), previous severe asthmatic exacerbation (OR= 3.8, 95% CI= 1.48-10.01, p= 0.005) and recent admission to hospital (OR= 2.9, 95% CI= 1.07-8.09, p= 0.037) were found to be predictive factors for severe asthmatic exacerbation. Different predictive factors, in particular frequent using of short-acting beta(2)-agonist and noncompliance with medication may be associated with severe asthma exacerbations compared to milder exacerbations. This suggests different mechanisms are responsible for severity of asthma exacerbation.

Lung perfusion SPECT in predicting postoperative pulmonary function in lung cancer

International Nuclear Information System (INIS)

Hirose, Yoshiaki; Imaeda, Takeyoshi; Doi, Hidetaka; Kokubo, Mitsuharu; Sakai, Satoshi; Hirose, Hajime

1993-01-01

The aim of this prospective study is to evaluate the availability of preoperative perfusion SPECT in predicting postoperative pulmonary function following resection. Twenty-three patients with lung cancer who were candidates for lobectomy were investigated preoperatively with spirometry, x-ray computed tomography and 99m Tc-macroaggregated albumin SPECT. Their postoperative pulmonary functions were predicted with these examinations. The forced vital capacity and the forced expiratory volume in one second were selected as parameters for overall pulmonary function. The postoperative pulmonary function was predicted by the following formula: Predicted postoperative value=observed preoperative value x precent perfusion of the lung not to be resected. The patients were reinvestigated with spirometry at 3 months and 6 months after lobectomy, and the values obtained were statistically compared with the predicted values. Close relationships were found between predicted and observed forced vital capacity (r=0.87, p<0.001), and predicted and observed forced expiratory volume in one second (r=0.90, p<0.001). The accurate prediction of pulmonary function after lobectomy could be achieved by means of lung perfusion SPECT. (author)

QCD dipole prediction for dis and diffractive structure functions

International Nuclear Information System (INIS)

Royon, CH.

1996-01-01

The F 2 , F G , R = F L /F T proton structure functions are derived in the QCD dipole picture of BFKL dynamics. We get a three parameter fit describing the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed, and a new prediction for the proton diffractive structure function is obtained. (author)

Fast dynamics perturbation analysis for prediction of protein functional sites

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Cohn Judith D

2008-01-01

Full Text Available Abstract Background We present a fast version of the dynamics perturbation analysis (DPA algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

Scoring function to predict solubility mutagenesis

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Deutsch Christopher

2010-10-01

Full Text Available Abstract Background Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention. Results We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM and the Lasso. Using statistics for leave-one-out (LOO, 10-fold, and 3-fold cross validations (CV for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%. Availability Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

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Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Predicting genotypes environmental range from genome-environment associations.

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Manel, Stéphanie; Andrello, Marco; Henry, Karine; Verdelet, Daphné; Darracq, Aude; Guerin, Pierre-Edouard; Desprez, Bruno; Devaux, Pierre

2018-05-17

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random Single Nucleotide Polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Network-based ranking methods for prediction of novel disease associated microRNAs.

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Le, Duc-Hau

2015-10-01

Many studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a "disease module" principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the "disease module" principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction. We constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm. Analyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In

Predictability of Genetic Interactions from Functional Gene Modules

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Jonathan H. Young

2017-02-01

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

Predicting Hydrologic Function With Aquatic Gene Fragments

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Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Predicting functional upstream open reading frames in Saccharomyces cerevisiae

Directory of Open Access Journals (Sweden)

Kristiansson Erik

2009-12-01

Full Text Available Abstract Background Some upstream open reading frames (uORFs regulate gene expression (i.e., they are functional and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not yet fully understood. In order to get a complete view of how uORFs are involved in gene regulation, it is expected that a large number of experimentally verified functional uORFs are needed. Unfortunately, wet-experiments to verify that uORFs are functional are expensive. Results In this paper, a new computational approach to predicting functional uORFs in the yeast Saccharomyces cerevisiae is presented. Our approach is based on inductive logic programming and makes use of a novel combination of knowledge about biological conservation, Gene Ontology annotations and genes' responses to different conditions. Our method results in a set of simple and informative hypotheses with an estimated sensitivity of 76%. The hypotheses predict 301 further genes to have 398 novel functional uORFs. Three (RPC11, TPK1, and FOL1 of these 301 genes have been hypothesised, following wet-experiments, by a related study to have functional uORFs. A comparison with another related study suggests that eleven of the predicted functional uORFs from genes LDB17, HEM3, CIN8, BCK2, PMC1, FAS1, APP1, ACC1, CKA2, SUR1, and ATH1 are strong candidates for wet-lab experimental studies. Conclusions Learning based prediction of functional uORFs can be done with a high sensitivity. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help to elucidate the regulatory roles of uORFs.

Improving protein function prediction methods with integrated literature data

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Gabow Aaron P

2008-04-01

Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

Science.gov (United States)

Sabbath, Erika L; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-10-01

Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control and their combination during working life predicted post-retirement performance on eight cognitive tests. We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2149). Psychosocial job characteristics were measured on average for 4 years before retirement using Karasek's Job Content Questionnaire (job demands, job control and demand-control combinations). We tested associations between these exposures and post-retirement performance on tests for executive function, visual-motor speed, psychomotor speed, verbal memory, and verbal fluency using ordinary least squares regression. Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency and semantic fluency after retirement (p'swork stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Prediction of Chemical Function: Model Development and ...

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The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

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Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

2016-05-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

Science.gov (United States)

Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

2015-01-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108

Combining Spot Sign and Intracerebral Hemorrhage Score to Estimate Functional Outcome: Analysis From the PREDICT Cohort.

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Schneider, Hauke; Huynh, Thien J; Demchuk, Andrew M; Dowlatshahi, Dar; Rodriguez-Luna, David; Silva, Yolanda; Aviv, Richard; Dzialowski, Imanuel

2018-06-01

The intracerebral hemorrhage (ICH) score is the most commonly used grading scale for stratifying functional outcome in patients with acute ICH. We sought to determine whether a combination of the ICH score and the computed tomographic angiography spot sign may improve outcome prediction in the cohort of a prospective multicenter hemorrhage trial. Prospectively collected data from 241 patients from the observational PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign) were analyzed. Functional outcome at 3 months was dichotomized using the modified Rankin Scale (0-3 versus 4-6). Performance of (1) the ICH score and (2) the spot sign ICH score-a scoring scale combining ICH score and spot sign number-was tested. Multivariable analysis demonstrated that ICH score (odds ratio, 3.2; 95% confidence interval, 2.2-4.8) and spot sign number (n=1: odds ratio, 2.7; 95% confidence interval, 1.1-7.4; n>1: odds ratio, 3.8; 95% confidence interval, 1.2-17.1) were independently predictive of functional outcome at 3 months with similar odds ratios. Prediction of functional outcome was not significantly different using the spot sign ICH score compared with the ICH score alone (spot sign ICH score area under curve versus ICH score area under curve: P =0.14). In the PREDICT cohort, a prognostic score adding the computed tomographic angiography-based spot sign to the established ICH score did not improve functional outcome prediction compared with the ICH score. © 2018 American Heart Association, Inc.

BRAIN NATRIURETIC PEPTIDE (BNP: BIOMARKER FOR RISK STRATIFICATION AND FUNCTIONAL RECOVERY PREDICTION IN ISCHEMIC STROKE

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STANESCU Ioana

2015-02-01

Full Text Available Functional outcome after cardiovascular and cerebrovascular events is traditionally predicted using demographic and clinical variables like age, gender, blood pressure, cholesterol levels, diabetes status, smoking habits or pre-existing morbidity. Identification of new variables will improve the risk stratification of specific categories of patients. Numerous blood-based biomarkers associated with increased cardiovascular risk have been identified; some of them even predict cardiovascular events. Investigators have tried to produce prediction models by incorporating traditional risk factors and biomarkers. (1. Widely-available, rapidly processed and less expensive biomarkers could be used in the future to guide management of complex cerebrovascular patients in order to maximize their recovery (2 Recently, studies have demonstrated that biomarkers can predict not only the risk for a specific clinical event, but also the risk of death of vascular cause and the functional outcome after cardiovascular or cerebrovascular events. Early prediction of fatal outcome after stroke may improve therapeutic strategies (such as the use of more aggressive treatments or inclusion of patients in clinical trials and guide decision-making processes in order to maximize patient’s chances for survival and recovery. (3 Long term functional outcome after stroke is one of the most difficult variables to predict. Elevated serum levels of brain natriuretic peptide (BNP are powerful predictor of outcomes in patients with cardiovascular disease (heart failure, atrial fibrillation. Potential role of BNP in predicting atrial fibrillation occurrence, cardio-embolic stroke and post-stroke mortality have been proved in many studies. However, data concerning the potential role of BNP in predicting short term and long term functional outcomes after stroke remain controversial.

Predicting gene function using hierarchical multi-label decision tree ensembles

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Kocev Dragi

2010-01-01

Full Text Available Abstract Background S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability. Results We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO. We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use. Conclusions Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.

Physiological stress responses predict sexual functioning and satisfaction differently in women who have and have not been sexually abused in childhood.

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Meston, Cindy M; Lorenz, Tierney A

2013-07-01

Physiological responses to sexual stimuli may contribute to the increased rate of sexual problems seen in women with childhood sexual abuse (CSA) histories. We compared two physiological stress responses as predictors of sexual function and satisfaction, sympathetic nervous system (SNS) activation and cortisol in women with (CSA, N = 136) and without CSA histories (NSA, N = 102). In CSA survivors, cortisol response to sexual stimuli did not significantly predict sexual functioning; however, in NSA women, cortisol increases were associated with poorer sexual functioning, and decreases with higher functioning. For women with CSA histories, lower SNS activity was associated with poorer sexual functioning. For CSA survivors with low lifetime trauma, lower SNS activity was associated with higher sexual satisfaction; for women with high lifetime trauma, the reverse was true. Decreased SNS activity during sexual stimuli predicted higher sexual functioning in NSA women with low lifetime exposure to traumatic events, but lower sexual functioning in those with high exposure. Differences between women with and without CSA histories in the association between cortisol and SNS response and sexual functioning and satisfaction suggests that CSA causes disruptions in both short and long-term stress responses to sexual stimuli that perpetuate into adulthood.

Intrinsic spontaneous brain activity predicts individual variability in associative memory in older adults.

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Zheng, Zhiwei; Li, Rui; Xiao, Fengqiu; He, Rongqiao; Zhang, Shouzi; Li, Juan

2018-04-19

Older adults demonstrate notable individual differences in associative memory. Here, resting-state functional magnetic resonance imaging (rsfMRI) was used to investigate whether intrinsic brain activity at rest could predict individual differences in associative memory among cognitively healthy older adults. Regional amplitude of low-frequency fluctuations (ALFF) analysis and a correlation-based resting-state functional connectivity (RSFC) approach were used to analyze data acquired from 102 cognitively normal elderly who completed the paired-associative learning test (PALT) and underwent fMRI scans. Participants were divided into two groups based on the retrospective self-reports on whether or not they utilized encoding strategies during the PALT. The behavioral results revealed better associative memory performance in the participants who reported utilizing memory strategies compared with participants who reported not doing so. The fMRI results showed that higher associative memory performance was associated with greater functional connectivity between the right superior frontal gyrus and the right posterior cerebellum lobe in the strategy group. The regional ALFF values in the right superior frontal gyrus were linked to associative memory performance in the no-strategy group. These findings suggest that the regional spontaneous fluctuations and functional connectivity during rest may subserve the individual differences in the associative memory in older adults, and that this is modulated by self-initiated memory strategy use. © 2018 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Physical activity and obesity mediate the association between childhood motor function and adolescents' academic achievement.

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Kantomaa, Marko T; Stamatakis, Emmanuel; Kankaanpää, Anna; Kaakinen, Marika; Rodriguez, Alina; Taanila, Anja; Ahonen, Timo; Järvelin, Marjo-Riitta; Tammelin, Tuija

2013-01-29

The global epidemic of obesity and physical inactivity may have detrimental implications for young people's cognitive function and academic achievement. This prospective study investigated whether childhood motor function predicts later academic achievement via physical activity, fitness, and obesity. The study sample included 8,061 children from the Northern Finland Birth Cohort 1986, which contains data about parent-reported motor function at age 8 y and self-reported physical activity, predicted cardiorespiratory fitness (cycle ergometer test), obesity (body weight and height), and academic achievement (grades) at age 16 y. Structural equation models with unstandardized (B) and standardized (β) coefficients were used to test whether, and to what extent, physical activity, cardiorespiratory fitness, and obesity at age 16 mediated the association between childhood motor function and adolescents' academic achievement. Physical activity was associated with a higher grade-point average, and obesity was associated with a lower grade-point average in adolescence. Furthermore, compromised motor function in childhood had a negative indirect effect on adolescents' academic achievement via physical inactivity (B = -0.023, 95% confidence interval = -0.031, -0.015) and obesity (B = -0.025, 95% confidence interval = -0.039, -0.011), but not via cardiorespiratory fitness. These results suggest that physical activity and obesity may mediate the association between childhood motor function and adolescents' academic achievement. Compromised motor function in childhood may represent an important factor driving the effects of obesity and physical inactivity on academic underachievement.

Physical activity and obesity mediate the association between childhood motor function and adolescents’ academic achievement

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Kantomaa, Marko T.; Stamatakis, Emmanuel; Kankaanpää, Anna; Kaakinen, Marika; Rodriguez, Alina; Taanila, Anja; Ahonen, Timo; Järvelin, Marjo-Riitta; Tammelin, Tuija

2013-01-01

The global epidemic of obesity and physical inactivity may have detrimental implications for young people’s cognitive function and academic achievement. This prospective study investigated whether childhood motor function predicts later academic achievement via physical activity, fitness, and obesity. The study sample included 8,061 children from the Northern Finland Birth Cohort 1986, which contains data about parent-reported motor function at age 8 y and self-reported physical activity, predicted cardiorespiratory fitness (cycle ergometer test), obesity (body weight and height), and academic achievement (grades) at age 16 y. Structural equation models with unstandardized (B) and standardized (β) coefficients were used to test whether, and to what extent, physical activity, cardiorespiratory fitness, and obesity at age 16 mediated the association between childhood motor function and adolescents’ academic achievement. Physical activity was associated with a higher grade-point average, and obesity was associated with a lower grade-point average in adolescence. Furthermore, compromised motor function in childhood had a negative indirect effect on adolescents’ academic achievement via physical inactivity (B = –0.023, 95% confidence interval = –0.031, –0.015) and obesity (B = –0.025, 95% confidence interval = –0.039, –0.011), but not via cardiorespiratory fitness. These results suggest that physical activity and obesity may mediate the association between childhood motor function and adolescents’ academic achievement. Compromised motor function in childhood may represent an important factor driving the effects of obesity and physical inactivity on academic underachievement. PMID:23277558

Association of Social Support and Family Environment with Cognitive Function in Peritoneal Dialysis Patients.

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Wang, Qin; Yang, Zhi-Kai; Sun, Xiu-Mei; Du, Yun; Song, Yi-Fan; Ren, Ye-Ping; Dong, Jie

♦ BACKGROUND: Cognitive impairment (CI) is a common phenomenon and predictive of high mortality in peritoneal dialysis (PD) patients. This study aimed to analyze the association of social support and family environment with cognitive function in PD patients. ♦ METHODS: This is a cross-sectional study of PD patients from Peking University First Hospital and the Second Affiliated Hospital of Harbin Medical University. Global cognitive function was measured using the Modified Mini-Mental State Examination (3MS), executive function was measured by the A and B trail-making tests, and other cognitive functions were measured by the Repeatable Battery for the Assessment of Neuropsychological Status. Social support was measured with the Social Support Scale developed by Xiaoshuiyuan and family environment was measured with the Chinese Version of the Family Environment Scale (FES-CV). ♦ RESULTS: The prevalence of CI and executive dysfunction among the 173 patients in the study was, respectively, 16.8% and 26.3%. Logistic regression found that higher global social support (odds ratio [OR] = 1.09, 1.01 - 1.17, p = 0.027) and subjective social support predicted higher prevalence of CI (OR = 1.13, 1.02 - 1.25, p = 0.022), adjusting for covariates. Analyses of the FES-CV dimensions found that greater independence was significantly associated with better immediate memory and delayed memory. Moreover, higher scores on achievement orientation were significantly associated with poorer language skills. ♦ CONCLUSIONS: Our findings indicate that social support is negatively associated with the cognitive function of PD patients and that some dimensions of the family environment are significantly associated with several domains of cognitive function. Copyright © 2017 International Society for Peritoneal Dialysis.

Linear Prediction Using Refined Autocorrelation Function

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M. Shahidur Rahman

2007-07-01

Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.

Predictive model for functional consequences of oral cavity tumour resections

NARCIS (Netherlands)

van Alphen, M.J.A.; Hageman, T.A.G.; Hageman, Tijmen Antoon Geert; Smeele, L.E.; Balm, Alfonsus Jacobus Maria; Balm, A.J.M.; van der Heijden, Ferdinand; Lemke, H.U.

2013-01-01

The prediction of functional consequences after treatment of large oral cavity tumours is mainly based on the size and location of the tumour. However, patient specific factors play an important role in the functional outcome, making the current predictions unreliable and subjective. An objective

Predicting estuarine benthic production using functional diversity

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Marina Dolbeth

2014-05-01

Full Text Available We considered an estuarine system having naturally low levels of diversity, but attaining considerable high production levels, and being subjected to different sorts of anthropogenic impacts and climate events to investigate the relationship between diversity and secondary production. Functional diversity measures were used to predict benthic production, which is considered as a proxy of the ecosystem provisioning services. To this end, we used a 14-year dataset on benthic invertebrate community production from a seagrass and a sandflat habitat and we adopted a sequential modeling approach, where abiotic, trait community weighted means (CWM and functional diversity indices were tested by generalized linear models (GLM, and their significant variables were then combined to produce a final model. Almost 90% of variance of the benthic production could be predicted by combining the number of locomotion types, the absolute maximum atmospheric temperature (proxy of the heat waves occurrence, the type of habitat and the mean body mass, by order of importance. This result is in agreement with the mass ratio hypothesis, where ecosystem functions/services can be chiefly predicted by the dominant trait in the community, here measured as CWM. The increase of benthic production with the number of locomotion types may be seen as greater possibility of using the resources available in the system. Such greater efficiency would increase production. The other variables were also discussed in line of the previous hypothesis and taking into account the general positive relationship obtained between production and functional diversity indices. Overall, it was concluded that traits representative of wider possibilities of using available resources and higher functional diversity are related with higher benthic production.

Predicting Cognitive, Functional, and Diagnostic Change over 4 Years Using Baseline Subjective Cognitive Complaints in the Sydney Memory and Ageing Study.

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Slavin, Melissa J; Sachdev, Perminder S; Kochan, Nicole A; Woolf, Claudia; Crawford, John D; Giskes, Katrina; Reppermund, Simone; Trollor, Julian N; Draper, Brian; Delbaere, Kim; Brodaty, Henry

2015-09-01

There is limited understanding of the usefulness of subjective cognitive complaint(s) (SCC) in predicting longitudinal outcome because most studies focus solely on memory (as opposed to nonmemory cognitive) complaints, do not collect data from both participants and informants, do not control for relevant covariates, and have limited outcome measures. Therefore the authors investigate the usefulness of participant and informant SCCs in predicting change in cognition, functional abilities, and diagnostic classification of mild cognitive impairment or dementia in a community-dwelling sample over 4 years. Nondemented participants (N = 620) in the Sydney Memory and Ageing Study aged between 70 and 90 years completed 15 memory and 9 nonmemory SCC questions. An informant completed a baseline questionnaire that included 15 memory and 4 nonmemory SCC questions relating to the participant. Neuropsychological, functional, and diagnostic assessments were carried out at baseline and again at 4-year follow-up. Cross-sectional and longitudinal analyses were carried out to determine the association between SCC indices and neuropsychological, functional, and diagnostic data while controlling for psychological measures. Once participant characteristics were controlled for, participant complaints were generally not predictive of cognitive or functional decline, although participant memory-specific complaints were predictive of diagnostic conversion. Informant-related memory questions were associated with global cognitive and functional decline and with diagnostic conversion over 4 years. Informant memory complaint questions were better than participant complaints in predicting cognitive and functional decline as well as diagnoses over 4 years. Copyright © 2015 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

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Kihara Daisuke

2010-05-01

Full Text Available Abstract Background A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance. Results Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, Escherichia coli, Saccharomyces cerevisiae, and Plasmodium falciparum (malaria. The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO category, i.e. Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the funSim score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the funSim score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted. Conclusion The analyses demonstrate that applying high confidence predictions from PFP

The association between daytime napping and cognitive functioning in chronic fatigue syndrome.

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Gotts, Zoe M; Ellis, Jason G; Deary, Vincent; Barclay, Nicola; Newton, Julia L

2015-01-01

The precise relationship between sleep and physical and mental functioning in chronic fatigue syndrome (CFS) has not been examined directly, nor has the impact of daytime napping. This study aimed to examine self-reported sleep in patients with CFS and explore whether sleep quality and daytime napping, specific patient characteristics (gender, illness length) and levels of anxiety and depression, predicted daytime fatigue severity, levels of daytime sleepiness and cognitive functioning, all key dimensions of the illness experience. 118 adults meeting the 1994 CDC case criteria for CFS completed a standardised sleep diary over 14 days. Momentary functional assessments of fatigue, sleepiness, cognition and mood were completed by patients as part of usual care. Levels of daytime functioning and disability were quantified using symptom assessment tools, measuring fatigue (Chalder Fatigue Scale), sleepiness (Epworth Sleepiness Scale), cognitive functioning (Trail Making Test, Cognitive Failures Questionnaire), and mood (Hospital Anxiety and Depression Scale). Hierarchical Regressions demonstrated that a shorter time since diagnosis, higher depression and longer wake time after sleep onset predicted 23.4% of the variance in fatigue severity (p naps predicted 25.6% of the variance in objective cognitive dysfunction (p napping predicted 32.2% of the variance in subjective cognitive dysfunction (p naps, those who mainly napped in the afternoon, and those with higher levels of anxiety, were more likely to be in the moderately sleepy group. Napping, particularly in the afternoon is associated with poorer cognitive functioning and more daytime sleepiness in CFS. These findings have clinical implications for symptom management strategies.

Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

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Le, Duc-Hau; Dao, Lan T M

2018-05-23

Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitation in experimentally identifying disease-lncRNA associations, computational methods have been proposed as a powerful tool to predict such associations. These methods are usually based on the similarities between diseases or lncRNAs since it was reported that similar diseases are associated with functionally similar lncRNAs. Therefore, prediction performance is highly dependent on how well the similarities can be captured. Previous studies have calculated the similarity between two diseases by mapping exactly each disease to a single Disease Ontology (DO) term, and then use a semantic similarity measure to calculate the similarity between them. However, the problem of this approach is that a disease can be described by more than one DO terms. Until now, there is no annotation database of DO terms for diseases except for genes. In contrast, Human Phenotype Ontology (HPO) is designed to fully annotate human disease phenotypes. Therefore, in this study, we constructed disease similarity networks/matrices using HPO instead of DO. Then, we used these networks/matrices as inputs of two representative machine learning-based and network-based ranking algorithms, that is, regularized least square and heterogeneous graph-based inference, respectively. The results showed that the prediction performance of the two algorithms on HPO-based is better than that on DO-based networks/matrices. In addition, our method can predict 11 novel cancer-associated lncRNAs, which are supported by literature evidence. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prediction of Associations between OMIM Diseases and MicroRNAs by Random Walk on OMIM Disease Similarity Network

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Hailin Chen

2013-01-01

Full Text Available Increasing evidence has revealed that microRNAs (miRNAs play important roles in the development and progression of human diseases. However, efforts made to uncover OMIM disease-miRNA associations are lacking and the majority of diseases in the OMIM database are not associated with any miRNA. Therefore, there is a strong incentive to develop computational methods to detect potential OMIM disease-miRNA associations. In this paper, random walk on OMIM disease similarity network is applied to predict potential OMIM disease-miRNA associations under the assumption that functionally related miRNAs are often associated with phenotypically similar diseases. Our method makes full use of global disease similarity values. We tested our method on 1226 known OMIM disease-miRNA associations in the framework of leave-one-out cross-validation and achieved an area under the ROC curve of 71.42%. Excellent performance enables us to predict a number of new potential OMIM disease-miRNA associations and the newly predicted associations are publicly released to facilitate future studies. Some predicted associations with high ranks were manually checked and were confirmed from the publicly available databases, which was a strong evidence for the practical relevance of our method.

Scoring protein relationships in functional interaction networks predicted from sequence data.

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Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

Combining specificity determining and conserved residues improves functional site prediction

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Gelfand Mikhail S

2009-06-01

Full Text Available Abstract Background Predicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core. Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities. Results Here we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs, as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples. Conclusion The results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

QCD predictions for weak neutral current structure functions

International Nuclear Information System (INIS)

Wu Jimin

1987-01-01

Employing the analytic expression (to the next leading order) for non-singlet component of structure function which the author got from QCD theory and putting recent experiment result of neutral current structure function at Q 2 = 11 (GeV/C) 2 as input, the QCD prediction for neutral current structure function of their scaling violation behaviours was given

Association of lung function and chronic obstructive pulmonary disease with American Heart Association's Life's Simple 7 cardiovascular health metrics.

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Fan, Wenjun; Lee, Hwa; Lee, Angela; Kieu, Chi; Wong, Nathan D

2017-10-01

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the U.S. There is a strong association between COPD and cardiovascular (CV) disease; however, the relation between COPD and CV health factors is not well defined. We examined the relation between lung function and CV health factors defined by American Heart Association's (AHA) Life's Simple 7 (LS7). We studied 6352 adults aged ≥20 from the National Health and Nutrition Examination Survey (NHANES) 2009-2012. Analysis of variance was used to compare mean FEV1% of predicted across levels of each LS7 metric and population attributable risk was calculated based on COPD prevalence. We also conducted linear regression and logistic regression analyses to determine the association between lung function, COPD and LS7 score. Overall 19.9% of subjects were defined as having COPD. Subjects in the highest categories of the LS7 metrics had the highest mean values of FEV1% of predicted (p < 0.0001 except for total cholesterol). Current smoking and hypertension had a population attributed risk of 21.8% and 21.1% of COPD, respectively. Compared to subjects with 0 ideal health factors, the gender and ethnicity-adjusted odds (95% CI) for COPD were 0.45 (0.22-0.93), 0.22 (0.11-0.43) for those with 4 and 5-7 factors, but adjustment for age attenuated this relation. LS7 score is associated with lung function as well as the odds of COPD that is largely explained by age. Studies are needed to show if promotion of CV health will preserve healthy lung function. Copyright © 2017 Elsevier Ltd. All rights reserved.

Response predictions using the observed autocorrelation function

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam; H. Brodtkorb, Astrid; Jensen, Jørgen Juncher

2018-01-01

This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine......-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input...... show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action)....

Obesity and unhealthy lifestyle associated with poor executive function among Malaysian adolescents.

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Tee, Joyce Ying Hui; Gan, Wan Ying; Tan, Kit-Aun; Chin, Yit Siew

2018-01-01

The understanding on the roles of obesity and lifestyle behaviors in predicting executive function of adolescents has been limited. Low executive function proficiency may have adverse effects on adolescents' school academic performance. This cross-sectional study aimed to examine the relationship between BMI-for-age and multiple lifestyle behaviors (operationalized as meal consumption, physical activity, and sleep quality) with executive function (operationalized as inhibition, working memory, and cognitive flexibility) on a sample of Malaysian adolescents aged between 12 and 16 years (N = 513). Participants were recruited from two randomly selected schools in the state of Selangor in Malaysia. Using a self-administered questionnaire, parent participants provided information concerning their sociodemographic data, whereas adolescent participants provided information regarding their meal consumptions, physical activity, and sleep quality. The modified Harvard step test was used to assess adolescents' aerobic fitness, while Stroop color-word, digit span, and trail-making tests were used to assess adolescents' inhibition, working memory, and cognitive flexibility, respectively. Three separate hierarchical regression analyses were conducted for each outcome namely, inhibition, working memory, and cognitive flexibility. After adjusted for sociodemographic factors and BMI-for-age, differential predictors of inhibition and working memory were found. Habitual sleep efficiency significantly and positively predicted inhibition. Regular dinner intakes, physical activity levels, and sleep quality significantly and positively predicted working memory. Household income emerged as a consistent predictor for all executive function domains. In conclusion, an increased trend of obesity and unhealthy lifestyles among adolescents were found to be associated with poorer executive function. Regular dinner intakes, higher physical activity levels and better sleep quality predicted better

Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

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Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

2013-05-01

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

Development and validation of a prediction model for loss of physical function in elderly hemodialysis patients.

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Fukuma, Shingo; Shimizu, Sayaka; Shintani, Ayumi; Kamitani, Tsukasa; Akizawa, Tadao; Fukuhara, Shunichi

2017-09-05

Among aging hemodialysis patients, loss of physical function has become a major issue. We developed and validated a model of predicting loss of physical function among elderly hemodialysis patients. We conducted a cohort study involving maintenance hemodialysis patients  ≥65 years of age from the Dialysis Outcomes and Practice Pattern Study in Japan. The derivation cohort included 593 early phase (1996-2004) patients and the temporal validation cohort included 447 late-phase (2005-12) patients. The main outcome was the incidence of loss of physical function, defined as the 12-item Short Form Health Survey physical function score decreasing to 0 within a year. Using backward stepwise logistic regression by Akaike's Information Criteria, six predictors (age, gender, dementia, mental health, moderate activity and ascending stairs) were selected for the final model. Points were assigned based on the regression coefficients and the total score was calculated by summing the points for each predictor. In total, 65 (11.0%) and 53 (11.9%) hemodialysis patients lost their physical function within 1 year in the derivation and validation cohorts, respectively. This model has good predictive performance quantified by both discrimination and calibration. The proportion of the loss of physical function increased sequentially through low-, middle-, and high-score categories based on the model (2.5%, 11.7% and 22.3% in the validation cohort, respectively). The loss of physical function was strongly associated with 1-year mortality [adjusted odds ratio 2.48 (95% confidence interval 1.26-4.91)]. We developed and validated a risk prediction model with good predictive performance for loss of physical function in elderly hemodialysis patients. Our simple prediction model may help physicians and patients make more informed decisions for healthy longevity. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA.

The predictive value of arterial stiffness on major adverse cardiovascular events in individuals with mildly impaired renal function

Directory of Open Access Journals (Sweden)

Han J

2016-08-01

Full Text Available Jie Han,* Xiaona Wang,* Ping Ye, Ruihua Cao, Xu Yang, Wenkai Xiao, Yun Zhang, Yongyi Bai, Hongmei Wu Department of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, People’s Republic of China *These authors contributed equally to this work Objectives: Despite growing evidence that arterial stiffness has important predictive value for cardiovascular disease in patients with advanced stages of chronic kidney disease, the predictive significance of arterial stiffness in individuals with mildly impaired renal function has not been established. The aim of this study was to evaluate the predictive value of arterial stiffness on cardiovascular disease in this specific population. Materials and methods: We analyzed measurements of arterial stiffness (carotid–femoral pulse-wave velocity [cf-PWV] and the incidence of major adverse cardiovascular events (MACEs in 1,499 subjects from a 4.8-year longitudinal study. Results: A multivariate Cox proportional-hazard regression analysis showed that in individuals with normal renal function (estimated glomerular filtration rate [eGFR] ≥90 mL/min/1.73 m2, the baseline cf-PWV was not associated with occurrence of MACEs (hazard ratio 1.398, 95% confidence interval 0.748–2.613; P=0.293. In individuals with mildly impaired renal function (eGFR <90 mL/min/1.73 m2, a higher baseline cf-PWV level was associated with a higher risk of MACEs (hazard ratio 2.334, 95% confidence interval 1.082–5.036; P=0.031. Conclusion: Arterial stiffness is a moderate and independent predictive factor for MACEs in individuals with mildly impaired renal function (eGFR <90 mL/min/1.73 m2. Keywords: epidemiology, arterial stiffness, impaired renal function, predictive value, MACEs

What specific facets of executive function are associated with academic functioning in youth with attention-deficit/hyperactivity disorder?

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Langberg, Joshua M; Dvorsky, Melissa R; Evans, Steven W

2013-10-01

The purpose of the study was to evaluate the relation between ratings of Executive Function (EF) and academic functioning in a sample of 94 middle-school-aged youth with Attention-Deficit/Hyperactivity Disorder (ADHD; Mage = 11.9; 78 % male; 21 % minority). This study builds on prior work by evaluating associations between multiple specific aspects of EF (e.g., working memory, inhibition, and planning and organization) as rated by both parents and teachers on the Behavior Rating Inventory of Executive Function (BRIEF), with multiple academic outcomes, including school grades and homework problems. Further, this study examined the relationship between EF and academic outcomes above and beyond ADHD symptoms and controlled for a number of potentially important covariates, including intelligence and achievement scores. The EF Planning and Organization subscale as rated by both parents and teachers predicted school grades above and beyond symptoms of ADHD and relevant covariates. Parent ratings of youth's ability to transition effectively between tasks/situations (Shift subscale) also predicted school grades. Parent-rated symptoms of inattention, hyperactivity/impulsivity, and planning and organization abilities were significant in the final model predicting homework problems. In contrast, only symptoms of inattention and the Organization of Materials subscale from the BRIEF were significant in the teacher model predicting homework problems. Organization and planning abilities are highly important aspects academic functioning for middle-school-aged youth with ADHD. Implications of these findings for the measurement of EF, and organization and planning abilities in particular, are discussed along with potential implications for intervention.

Financial Exploitation Is Associated With Structural and Functional Brain Differences in Healthy Older Adults.

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Spreng, R Nathan; Cassidy, Benjamin N; Darboh, Bri S; DuPre, Elizabeth; Lockrow, Amber W; Setton, Roni; Turner, Gary R

2017-10-01

Age-related brain changes leading to altered socioemotional functioning may increase vulnerability to financial exploitation. If confirmed, this would suggest a novel mechanism leading to heightened financial exploitation risk in older adults. Development of predictive neural markers could facilitate increased vigilance and prevention. In this preliminary study, we sought to identify structural and functional brain differences associated with financial exploitation in older adults. Financially exploited older adults (n = 13, 7 female) and a matched cohort of older adults who had been exposed to, but avoided, a potentially exploitative situation (n = 13, 7 female) were evaluated. Using magnetic resonance imaging, we examined cortical thickness and resting state functional connectivity. Behavioral data were collected using standardized cognitive assessments, self-report measures of mood and social functioning. The exploited group showed cortical thinning in anterior insula and posterior superior temporal cortices, regions associated with processing affective and social information, respectively. Functional connectivity encompassing these regions, within default and salience networks, was reduced, while between network connectivity was increased. Self-reported anger and hostility was higher for the exploited group. We observed financial exploitation associated with brain differences in regions involved in socioemotional functioning. These exploratory and preliminary findings suggest that alterations in brain regions implicated in socioemotional functioning may be a marker of financial exploitation risk. Large-scale, prospective studies are necessary to validate this neural mechanism, and develop predictive markers for use in clinical practice. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.

Load-related brain activation predicts spatial working memory performance in youth aged 9-12 and is associated with executive function at earlier ages.

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Huang, Anna S; Klein, Daniel N; Leung, Hoi-Chung

2016-02-01

Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9-12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Load-related brain activation predicts spatial working memory performance in youth aged 9–12 and is associated with executive function at earlier ages

Science.gov (United States)

Huang, Anna S.; Klein, Daniel N.; Leung, Hoi-Chung

2015-01-01

Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9–12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. PMID:26562059

PRISM offers a comprehensive genomic approach to transcription factor function prediction

KAUST Repository

Wenger, A. M.; Clarke, S. L.; Guturu, H.; Chen, J.; Schaar, B. T.; McLean, C. Y.; Bejerano, G.

2013-01-01

The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

KAUST Repository

Wenger, A. M.

2013-02-04

The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80.

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Vaughan, Leslie; Leng, Xiaoyan; La Monte, Michael J; Tindle, Hilary A; Cochrane, Barbara B; Shumaker, Sally A

2016-03-01

We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65-80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Women's Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [SD] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65-80) has far-reaching implications for improving late-life (after age 80) functional independence. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Perceived functioning has ethnic-specific associations in systemic sclerosis: another dimension of personalized medicine.

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McNearney, Terry A; Hunnicutt, Sonya E; Fischbach, Michael; Friedman, Alan W; Aguilar, Martha; Ahn, Chul W; Reveille, John D; Lisse, Jeffrey R; Baethge, Bruce A; Goel, Niti; Mayes, Maureen D

2009-12-01

To measure self-reported physical and mental functioning and associated clinical features at study entry in 3 ethnic groups with systemic sclerosis (SSc). Sixty Hispanic, 39 African American, and 104 Caucasian patients with recent-onset SSc ( fatigue scores > IBQ > clinical variables (hypertension, skin score, and percentage predicted DLCO). Scleroderma-HAQ scores had ethnic-specific associations with IBQ > AHI scores > most clinical and laboratory variables. Decreased mental component summary (MCS) scores associated with AHI > ISEL. Ethnic-specific immunogenetic variables HLA-DQB1*0202 (Caucasian) and HLA-DRB 1*11 (African American), and HLA-DQA1*0501 (Hispanic) also associated with MCS. Antinuclear autoantibodies, anti-topoisomerase I, and RNA polymerases I and III also demonstrated associations with functioning in African American and Hispanic groups. Clinical, psychosocial, and immunogenetic variables had ethnic-specific associations with perceived physical and mental functioning. Consideration of ethnic-specific psychological and behavioral support in designing more personalized, relevant therapeutic interventions for the patient may improve therapeutic efficacy in SSc.

FunSAV: predicting the functional effect of single amino acid variants using a two-stage random forest model.

Directory of Open Access Journals (Sweden)

Mingjun Wang

Full Text Available Single amino acid variants (SAVs are the most abundant form of known genetic variations associated with human disease. Successful prediction of the functional impact of SAVs from sequences can thus lead to an improved understanding of the underlying mechanisms of why a SAV may be associated with certain disease. In this work, we constructed a high-quality structural dataset that contained 679 high-quality protein structures with 2,048 SAVs by collecting the human genetic variant data from multiple resources and dividing them into two categories, i.e., disease-associated and neutral variants. We built a two-stage random forest (RF model, termed as FunSAV, to predict the functional effect of SAVs by combining sequence, structure and residue-contact network features with other additional features that were not explored in previous studies. Importantly, a two-step feature selection procedure was proposed to select the most important and informative features that contribute to the prediction of disease association of SAVs. In cross-validation experiments on the benchmark dataset, FunSAV achieved a good prediction performance with the area under the curve (AUC of 0.882, which is competitive with and in some cases better than other existing tools including SIFT, SNAP, Polyphen2, PANTHER, nsSNPAnalyzer and PhD-SNP. The sourcecodes of FunSAV and the datasets can be downloaded at http://sunflower.kuicr.kyoto-u.ac.jp/sjn/FunSAV.

LDAP: a web server for lncRNA-disease association prediction.

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Lan, Wei; Li, Min; Zhao, Kaijie; Liu, Jin; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2017-02-01

Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources. Then, we implement this method as a web server for lncRNA-disease association prediction (LDAP). The input of the LDAP server is the lncRNA sequence. The LDAP predicts potential lncRNA-disease associations by using a bagging SVM classifier based on lncRNA similarity and disease similarity. The web server is available at http://bioinformatics.csu.edu.cn/ldap jxwang@mail.csu.edu.cn. Supplementary data are available at Bioinformatics online.

Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

NARCIS (Netherlands)

Al-Shahib, A.; Breitling, R.; Gilbert, D.

2005-01-01

Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

Reduced lung function is independently associated with increased risk of type 2 diabetes in Korean men

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Kwon Chang-Hee

2012-04-01

Full Text Available Abstract Background Reduced lung function is associated with incident insulin resistance and diabetes. The aim of this study was to assess the relationship between lung function and incident type 2 diabetes in Korean men. Methods This study included 9,220 men (mean age: 41.4 years without type 2 diabetes at baseline who were followed for five years. Subjects were divided into four groups according to baseline forced vital capacity (FVC (% predicted and forced expiratory volume in one second (FEV1 (% predicted quartiles. The incidence of type 2 diabetes at follow-up was compared according to FVC and FEV1 quartiles. Results The overall incidence of type 2 diabetes was 2.2%. Reduced lung function was significantly associated with the incidence of type 2 diabetes after adjusting for age, BMI, education, smoking, exercise, alcohol, and HOMA-IR. Both FVC and FEV1 were negatively associated with type 2 diabetes (P 1 had a significantly higher odds ratio for type 2 diabetes compared with the highest quartile after adjusting for age and BMI (2.15 [95% CI 1.02-4.57] and 2.19 [95% CI 1.09-4.42]. Conclusions Reduced lung function is independently associated with the incidence of type 2 diabetes in Korean men.

FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications.

Science.gov (United States)

Backenroth, Daniel; He, Zihuai; Kiryluk, Krzysztof; Boeva, Valentina; Pethukova, Lynn; Khurana, Ekta; Christiano, Angela; Buxbaum, Joseph D; Ionita-Laza, Iuliana

2018-05-03

We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources). Copyright © 2018 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Integrative approaches to the prediction of protein functions based on the feature selection

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Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

Predictive assessment of models for dynamic functional connectivity

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

2018-01-01

represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

Robust Predictive Functional Control for Flight Vehicles Based on Nonlinear Disturbance Observer

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Yinhui Zhang

2015-01-01

Full Text Available A novel robust predictive functional control based on nonlinear disturbance observer is investigated in order to address the control system design for flight vehicles with significant uncertainties, external disturbances, and measurement noise. Firstly, the nonlinear longitudinal dynamics of the flight vehicle are transformed into linear-like state-space equations with state-dependent coefficient matrices. And then the lumped disturbances are considered in the linear structure predictive model of the predictive functional control to increase the precision of the predictive output and resolve the intractable mismatched disturbance problem. As the lumped disturbances cannot be derived or measured directly, the nonlinear disturbance observer is applied to estimate the lumped disturbances, which are then introduced to the predictive functional control to replace the unknown actual lumped disturbances. Consequently, the robust predictive functional control for the flight vehicle is proposed. Compared with the existing designs, the effectiveness and robustness of the proposed flight control are illustrated and validated in various simulation conditions.

Brachial-ankle pulse wave velocity predicts decline in renal function and cardiovascular events in early stages of chronic kidney disease.

Science.gov (United States)

Yoon, Hye Eun; Shin, Dong Il; Kim, Sung Jun; Koh, Eun Sil; Hwang, Hyeon Seok; Chung, Sungjin; Shin, Seok Joon

2013-01-01

In this study, we investigated the predictive capacity of the brachial-ankle aortic pulse wave velocity (baPWV), a marker of arterial stiffness, for the decline in renal function and for cardiovascular events in the early stages of chronic kidney disease (CKD). Two hundred forty-one patients who underwent a comprehensive check-up were included and were divided into two groups according to their estimated glomerular filtration rates (eGFR): patients with CKD categories G2, G3a and G3b (30 ≤ eGFR function, the eGFR change, was determined by the slope of eGFR against time. We analysed whether baPWV was associated with eGFR change or predicted cardiovascular events. baPWV was independently associated with eGFR change in a multivariate analysis of the total patients (β=-0.011, p=0.011) and remained significantly associated with eGFR change in a subgroup analysis of the eGFR function and short-term cardiovascular events.

Ecological transition predictably associated with gene degeneration.

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Wessinger, Carolyn A; Rausher, Mark D

2015-02-01

Gene degeneration or loss can significantly contribute to phenotypic diversification, but may generate genetic constraints on future evolutionary trajectories, potentially restricting phenotypic reversal. Such constraints may manifest as directional evolutionary trends when parallel phenotypic shifts consistently involve gene degeneration or loss. Here, we demonstrate that widespread parallel evolution in Penstemon from blue to red flowers predictably involves the functional inactivation and degeneration of the enzyme flavonoid 3',5'-hydroxylase (F3'5'H), an anthocyanin pathway enzyme required for the production of blue floral pigments. Other types of genetic mutations do not consistently accompany this phenotypic shift. This pattern may be driven by the relatively large mutational target size of degenerative mutations to this locus and the apparent lack of associated pleiotropic effects. The consistent degeneration of F3'5'H may provide a mechanistic explanation for the observed asymmetry in the direction of flower color evolution in Penstemon: Blue to red transitions are common, but reverse transitions have not been observed. Although phenotypic shifts in this system are likely driven by natural selection, internal constraints may generate predictable genetic outcomes and may restrict future evolutionary trajectories. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

Science.gov (United States)

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

The association between daytime napping and cognitive functioning in chronic fatigue syndrome.

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Zoe M Gotts

Full Text Available The precise relationship between sleep and physical and mental functioning in chronic fatigue syndrome (CFS has not been examined directly, nor has the impact of daytime napping. This study aimed to examine self-reported sleep in patients with CFS and explore whether sleep quality and daytime napping, specific patient characteristics (gender, illness length and levels of anxiety and depression, predicted daytime fatigue severity, levels of daytime sleepiness and cognitive functioning, all key dimensions of the illness experience.118 adults meeting the 1994 CDC case criteria for CFS completed a standardised sleep diary over 14 days. Momentary functional assessments of fatigue, sleepiness, cognition and mood were completed by patients as part of usual care. Levels of daytime functioning and disability were quantified using symptom assessment tools, measuring fatigue (Chalder Fatigue Scale, sleepiness (Epworth Sleepiness Scale, cognitive functioning (Trail Making Test, Cognitive Failures Questionnaire, and mood (Hospital Anxiety and Depression Scale.Hierarchical Regressions demonstrated that a shorter time since diagnosis, higher depression and longer wake time after sleep onset predicted 23.4% of the variance in fatigue severity (p <.001. Being male, higher depression and more afternoon naps predicted 25.6% of the variance in objective cognitive dysfunction (p <.001. Higher anxiety and depression and morning napping predicted 32.2% of the variance in subjective cognitive dysfunction (p <.001. When patients were classified into groups of mild and moderate sleepiness, those with longer daytime naps, those who mainly napped in the afternoon, and those with higher levels of anxiety, were more likely to be in the moderately sleepy group.Napping, particularly in the afternoon is associated with poorer cognitive functioning and more daytime sleepiness in CFS. These findings have clinical implications for symptom management strategies.

Predicting Multiple Functions of Sustainable Flood Retention Basins under Uncertainty via Multi-Instance Multi-Label Learning

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Qinli Yang

2015-03-01

Full Text Available The ambiguity of diverse functions of sustainable flood retention basins (SFRBs may lead to conflict and risk in water resources planning and management. How can someone provide an intuitive yet efficient strategy to uncover and distinguish the multiple potential functions of SFRBs under uncertainty? In this study, by exploiting both input and output uncertainties of SFRBs, the authors developed a new data-driven framework to automatically predict the multiple functions of SFRBs by using multi-instance multi-label (MIML learning. A total of 372 sustainable flood retention basins, characterized by 40 variables associated with confidence levels, were surveyed in Scotland, UK. A Gaussian model with Monte Carlo sampling was used to capture the variability of variables (i.e., input uncertainty, and the MIML-support vector machine (SVM algorithm was subsequently applied to predict the potential functions of SFRBs that have not yet been assessed, allowing for one basin belonging to different types (i.e., output uncertainty. Experiments demonstrated that the proposed approach enables effective automatic prediction of the potential functions of SFRBs (e.g., accuracy >93%. The findings suggest that the functional uncertainty of SFRBs under investigation can be better assessed in a more comprehensive and cost-effective way, and the proposed data-driven approach provides a promising method of doing so for water resources management.

The mediating role of coping strategy in the association between family functioning and nonsuicidal self-injury among Taiwanese adolescents.

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Ren, Yaxuan; Lin, Min-Pei; Liu, Yin-Han; Zhang, Xu; Wu, Jo Yung-Wei; Hu, Wei-Hsuan; Xu, Sian; You, Jianing

2018-01-22

Nock's (2009) integrated theoretical model suggests that both intrapersonal and interpersonal factors contribute to the development of nonsuicidal self-injury (NSSI). Based on this model, the present study examined the roles of family functioning and coping strategy in predicting NSSI, as well as the mediating effect of coping strategy in the relationship between family functioning and NSSI. Gender differences on the associations of these variables were also examined. A sample of 1,989 secondary school students (52.0% females) in Taiwan was assessed by self-report measures of perceived family functioning, coping strategy, and NSSI. Results showed that both family functioning and avoidance/emotion-focused coping strategy predicted NSSI. Additionally, the association between family functioning and NSSI was mediated by avoidance/emotion-focused coping strategy. Gender differences were not found on the associations among these study variables. These data provided evidences that the Nock's (2009) integrated theoretical model may help to explain how coping strategy mediates the effect of family functioning on NSSI. The implications of the findings for future research and intervention were discussed. © 2018 Wiley Periodicals, Inc.

Differential RISC association of endogenous human microRNAs predicts their inhibitory potential.

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Flores, Omar; Kennedy, Edward M; Skalsky, Rebecca L; Cullen, Bryan R

2014-04-01

It has previously been assumed that the generally high stability of microRNAs (miRNAs) reflects their tight association with Argonaute (Ago) proteins, essential components of the RNA-induced silencing complex (RISC). However, recent data have suggested that the majority of mature miRNAs are not, in fact, Ago associated. Here, we demonstrate that endogenous human miRNAs vary widely, by >100-fold, in their level of RISC association and show that the level of Ago binding is a better indicator of inhibitory potential than is the total level of miRNA expression. While miRNAs of closely similar sequence showed comparable levels of RISC association in the same cell line, these varied between different cell types. Moreover, the level of RISC association could be modulated by overexpression of complementary target mRNAs. Together, these data indicate that the level of RISC association of a given endogenous miRNA is regulated by the available RNA targetome and predicts miRNA function.

Disorganized Symptoms and Executive Functioning Predict Impaired Social Functioning in Subjects at Risk for Psychosis

OpenAIRE

Eslami, Ali; Jahshan, Carol; Cadenhead, Kristin S.

2011-01-01

Predictors of social functioning deficits were assessed in 22 individuals “at risk” for psychosis. Disorganized symptoms and executive functioning predicted social functioning at follow-up. Early intervention efforts that focus on social and cognitive skills are indicated in this vulnerable population.

Patient-specific prediction of functional recovery after stroke.

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Douiri, Abdel; Grace, Justin; Sarker, Shah-Jalal; Tilling, Kate; McKevitt, Christopher; Wolfe, Charles DA; Rudd, Anthony G

2017-07-01

Background and aims Clinical predictive models for stroke recovery could offer the opportunity of targeted early intervention and more specific information for patients and carers. In this study, we developed and validated a patient-specific prognostic model for monitoring recovery after stroke and assessed its clinical utility. Methods Four hundred and ninety-five patients from the population-based South London Stroke Register were included in a substudy between 2002 and 2004. Activities of daily living were assessed using Barthel Index) at one, two, three, four, six, eight, 12, 26, and 52 weeks after stroke. Penalized linear mixed models were developed to predict patients' functional recovery trajectories. An external validation cohort included 1049 newly registered stroke patients between 2005 and 2011. Prediction errors on discrimination and calibration were assessed. The potential clinical utility was evaluated using prognostic accuracy measurements and decision curve analysis. Results Predictive recovery curves showed good accuracy, with root mean squared deviation of 3 Barthel Index points and a R 2 of 83% up to one year after stroke in the external cohort. The negative predictive values of the risk of poor recovery (Barthel Index <8) at three and 12 months were also excellent, 96% (95% CI [93.6-97.4]) and 93% [90.8-95.3], respectively, with a potential clinical utility measured by likelihood ratios (LR+:17 [10.8-26.8] at three months and LR+:11 [6.5-17.2] at 12 months). Decision curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 5% for predictive risk of poor outcomes. Conclusions A recovery curves tool seems to accurately predict progression of functional recovery in poststroke patients.

Novel prediction model of renal function after nephrectomy from automated renal volumetry with preoperative multidetector computed tomography (MDCT).

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Isotani, Shuji; Shimoyama, Hirofumi; Yokota, Isao; Noma, Yasuhiro; Kitamura, Kousuke; China, Toshiyuki; Saito, Keisuke; Hisasue, Shin-ichi; Ide, Hisamitsu; Muto, Satoru; Yamaguchi, Raizo; Ukimura, Osamu; Gill, Inderbir S; Horie, Shigeo

2015-10-01

The predictive model of postoperative renal function may impact on planning nephrectomy. To develop the novel predictive model using combination of clinical indices with computer volumetry to measure the preserved renal cortex volume (RCV) using multidetector computed tomography (MDCT), and to prospectively validate performance of the model. Total 60 patients undergoing radical nephrectomy from 2011 to 2013 participated, including a development cohort of 39 patients and an external validation cohort of 21 patients. RCV was calculated by voxel count using software (Vincent, FUJIFILM). Renal function before and after radical nephrectomy was assessed via the estimated glomerular filtration rate (eGFR). Factors affecting postoperative eGFR were examined by regression analysis to develop the novel model for predicting postoperative eGFR with a backward elimination method. The predictive model was externally validated and the performance of the model was compared with that of the previously reported models. The postoperative eGFR value was associated with age, preoperative eGFR, preserved renal parenchymal volume (RPV), preserved RCV, % of RPV alteration, and % of RCV alteration (p volumetry and clinical indices might yield an important tool for predicting postoperative renal function.

An Influence Function Method for Predicting Store Aerodynamic Characteristics during Weapon Separation,

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1981-05-14

8217 AO-Ail 777 GRUMMAN AEROSPACE CORP BETHPAGE NY F/G 20/4 AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC C--ETCCU) MAY 8 1 R MEYER, A...CENKO, S YARDS UNCLASSIFIED N ’.**~~N**n I EHEEKI j~j .25 Q~4 111110 111_L 5. AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC...extended to their logical conclusion one is led quite naturally to consideration of an " Influence Function Method" for I predicting store aerodynamic

Prediction of postoperative pulmonary function using 99mTc-MAA perfusion lung SPECT

International Nuclear Information System (INIS)

Hosokawa, Nobuyuki; Tanabe, Masatada; Satoh, Katashi; Takashima, Hitoshi; Ohkawa, Motoomi; Maeda, Masazumi; Tamai, Toyosato; Kojima, Kanji.

1995-01-01

In order to predict postoperative pulmonary function, 99m Tc-MAA perfusion lung SPECT and spirometry were performed preoperatively in 52 patients with resectable primary lung cancer; 44 underwent lobectomy, eight pneumonectomy. Local pulmonary function (called local effective volume) was evaluated according to the degree of radionuclide distribution of each voxel in the SPECT images. The total effective volume was defined as the sum of the local effective volume, and the residual effective volume was the total effective volume excluding loss after operation. Predicted pulmonary function (VC and FEV 1.0) was calculated by the following formula: Predicted value=preoperative value x percent of the residual effective volume. Postoperative pulmonary function was predicted in the same patients by means of 99m Tc-MAA perfusion lung planar scintigraphy and X-ray CT. The patients were reinvestigated with spirometry at one and four months after surgery, and the values were compared with the predicted values. The correlations between the predicted values using SPECT and measured postoperative pulmonary function were highly significant (VC: r=0.867, FEV1.0: r=0.864 one month after operation; VC: r=0.860, FEV1.0: r=0.907 4 months after operation). The predicted values calculated using SPECT were accurate compared with the predicted values calculated using planar scintigraphy or X-ray CT. The patients with predicted FEV1.0 of less than 0.8 liter required home oxygen therapy. This method is valuable for the prediction of postoperative pulmonary function before the surgical procedure. (author)

Regional differences in prediction models of lung function in Germany

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Schäper Christoph

2010-04-01

Full Text Available Abstract Background Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation. Methods Within three studies (KORA C, SHIP-I, ECRHS-I in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values. Results The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal but not extremely high or low lung function values in the whole study population. Conclusions Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.

Ventromedial Prefrontal Cortex Activation Is Associated with Memory Formation for Predictable Rewards

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Bialleck, Katharina A.; Schaal, Hans-Peter; Kranz, Thorsten A.; Fell, Juergen; Elger, Christian E.; Axmacher, Nikolai

2011-01-01

During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC. PMID:21326612

Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.

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Christopher Y Park

Full Text Available A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction. We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics

Predicting restoration of kidney function during CRRT-free intervals

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Heise Daniel

2012-01-01

Full Text Available Abstract Background Renal failure is common in critically ill patients and frequently requires continuous renal replacement therapy (CRRT. CRRT is discontinued at regular intervals for routine changes of the disposable equipment or for replacing clogged filter membrane assemblies. The present study was conducted to determine if the necessity to continue CRRT could be predicted during the CRRT-free period. Materials and methods In the period from 2003 to 2006, 605 patients were treated with CRRT in our ICU. A total of 222 patients with 448 CRRT-free intervals had complete data sets and were used for analysis. Of the total CRRT-free periods, 225 served as an evaluation group. Twenty-nine parameters with an assumed influence on kidney function were analyzed with regard to their potential to predict the restoration of kidney function during the CRRT-free interval. Using univariate analysis and logistic regression, a prospective index was developed and validated in the remaining 223 CRRT-free periods to establish its prognostic strength. Results Only three parameters showed an independent influence on the restoration of kidney function during CRRT-free intervals: the number of previous CRRT cycles (medians in the two outcome groups: 1 vs. 2, the "Sequential Organ Failure Assessment"-score (means in the two outcome groups: 8.3 vs. 9.2 and urinary output after the cessation of CRRT (medians in two outcome groups: 66 ml/h vs. 10 ml/h. The prognostic index, which was calculated from these three variables, showed a satisfactory potential to predict the kidney function during the CRRT-free intervals; Receiver operating characteristic (ROC analysis revealed an area under the curve of 0.798. Conclusion Restoration of kidney function during CRRT-free periods can be predicted with an index calculated from three variables. Prospective trials in other hospitals must clarify whether our results are generally transferable to other patient populations.

Relationship functioning moderates the association between depressive symptoms and life stressors.

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Trombello, Joseph M; Schoebi, Dominik; Bradbury, Thomas N

2011-02-01

Data from 172 newlywed couples were collected over the first 4 years of marriage to test how behaviors demonstrated during marital interactions moderate associations between depressive symptoms and subsequent life stressors. Depressive symptoms and behaviors coded from problem-solving and social support interactions were analyzed as predictors of nonmarital stressors that were interpersonal and dependent on the participant's actions. Behavioral codes were found to moderate 3 of 16 symptom-to-life event associations for husbands. Husbands' reports of more depressive symptoms predicted greater levels of stress when husbands' positive affect and hard negative affect during problem-solving were relatively infrequent and when wives made frequent displays of positive behaviors during husbands' support topics. These effects remained after controlling for marital satisfaction. For wives, behavioral moderators did not interact with depressive symptoms to predict changes in stress, but marital satisfaction consistently interacted with depressive symptoms to predict future stressors beyond interpersonal behaviors. Specifically, for wives, stress generation was more evident when relationship satisfaction was low than when it was high. Our results, though different for men and women, suggest that relationship functioning can alter associations between depressive symptoms and life stress in the early years of marriage. (PsycINFO Database Record (c) 2011 APA, all rights reserved). PsycINFO Database Record (c) 2011 APA, all rights reserved.

Particle correlations in the recombination model associated with modified Kuti-Weisskopf structure functions

International Nuclear Information System (INIS)

Takasugi, E.; Tata, X.

1982-01-01

The recombination model associated with modified Kuti-Weisskopf multiquark structure functions is used to analyze particle production by hadronic collisions. The justification of the use of the impulse approximation in these processes and the universal nature of the recombination process are discussed. Single-meson inclusive production in the fragmentation domains of the proton, the pion, and the kaon is used as an input to determine the primitive structure functions. Our parameter-free predictions for low-p/sub T/ multimeson and associated meson-baryon inclusive production are found to be in good agreement with a large amount of recently obtained correlation data. It is pointed out, however, that reactions involving multivalence recombination fall outside the scope of present considerations

Prospective associations between bilingualism and executive function in Latino children: sustained effects while controlling for biculturalism.

Science.gov (United States)

Riggs, Nathaniel R; Shin, Hee-Sung; Unger, Jennifer B; Spruijt-Metz, Donna; Pentz, Mary Ann

2014-10-01

The study purpose was to test 1-year prospective associations between English-Spanish bilingualism and executive function in 5th to 6th grade students while controlling for biculturalism. Participants included 182 US Latino students (50 % female). Self-report surveys assessed biculturalism, bilingualism, and executive function (i.e., working memory, organizational skills, inhibitory control, and emotional control, as well as a summary executive function score). General linear model regressions demonstrated that bilingualism significantly predicted the summary executive function score as well as working memory such that bilingual proficiency was positively related to executive function. Results are the first to demonstrate (a) prospective associations between bilingualism to executive function while controlling for the potential third variable of biculturalism, and (b) a principal role for working memory in this relationship. Since executive function is associated with a host of health outcomes, one implication of study findings is that bilingualism may have an indirect protective influence on youth development.

Predicting functional decline and survival in amyotrophic lateral sclerosis.

Science.gov (United States)

Ong, Mei-Lyn; Tan, Pei Fang; Holbrook, Joanna D

2017-01-01

Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score-climbing stairs were sufficient to predict survival class. Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1-2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials.

Protein function prediction using neighbor relativity in protein-protein interaction network.

Science.gov (United States)

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predictive factors associated with death of elderly in nursing homes.

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Sung, Kiwol

2014-06-01

An increasing elderly population reflects a great need for readily accessible, clinically useful methods to identify mortality-related factors in nursing home residents. The purpose of this study was to identify factors associated with the deaths of nursing home residents. Data was collected from a Minimal Data Set of 195 elderly nursing home residents, followed by analysis of demographic factors, disease and nursing condition factors, Activities of Daily Living (ADL), cognitive function, behavioral patterns, and dysfunctional status. Major factors associated with death among nursing home residents were identified as dyspnea (odds ratio [OR] = 4.88), problematic behaviors (OR = 3.95), and ADL (OR = 3.61). These variables accounted for 31.1% of the variance in death. Dyspnea, problematic behaviors, and ADL data were identified as the key factors associated with death among nursing home residents. Future plans for the prediction of death among nursing home residents can be made by nursing staff, factoring in these identified variables, to ensure more comfortable conditions and more responsive care. Copyright © 2014. Published by Elsevier B.V.

Critical evidence for the prediction error theory in associative learning.

Science.gov (United States)

Terao, Kanta; Matsumoto, Yukihisa; Mizunami, Makoto

2015-03-10

In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. Complete evidence for the prediction error theory, however, has not been obtained in any learning systems: Prediction error theory stems from the finding of a blocking phenomenon, but blocking can also be accounted for by other theories, such as the attentional theory. We demonstrated blocking in classical conditioning in crickets and obtained evidence to reject the attentional theory. To obtain further evidence supporting the prediction error theory and rejecting alternative theories, we constructed a neural model to match the prediction error theory, by modifying our previous model of learning in crickets, and we tested a prediction from the model: the model predicts that pharmacological intervention of octopaminergic transmission during appetitive conditioning impairs learning but not formation of reward prediction itself, and it thus predicts no learning in subsequent training. We observed such an "auto-blocking", which could be accounted for by the prediction error theory but not by other competitive theories to account for blocking. This study unambiguously demonstrates validity of the prediction error theory in associative learning.

Thigh muscle volume predicted by anthropometric measurements and correlated with physical function in the older adults.

Science.gov (United States)

Chen, B B; Shih, T T F; Hsu, C Y; Yu, C W; Wei, S Y; Chen, C Y; Wu, C H; Chen, C Y

2011-06-01

(1) to correlate thigh muscle volume measured by magnetic resonance image (MRI) with anthropometric measurements and physical function in elderly subjects; (2) to predict MRI-measured thigh muscle volume using anthropometric measurements and physical functional status in elderly subjects. Cross-sectional, nonrandomized study. Outpatient clinic in Taiwan. Sixty-nine elderly subjects (33 men and 36 women) aged 65 and older. The anthropometric data (including body height, body weight, waist size, and thigh circumference), physical activity and function (including grip strength, bilateral quadriceps muscle power, the up and go test, chair rise, and five meters walk time) and bioelectrical impedance analysis data (including total body fat mass, fat-free mass, and predictive muscle size) were measured. MRI-measured muscle volume of both thighs was used as the reference standard. The MRI-measured thigh volume was positively correlated with all anthropometric data, quadriceps muscle power and the up and go test as well as fat-free mass and predictive muscle mass, whereas it was negatively associated with age and walk time. In predicting thigh muscle volume, the variables of age, gender, body weight, and thigh circumference were significant predictors in the linear regression model: Muscle volume (cm3) =4226.3－42.5 × Age (year)－955.7 × gender (male=1, female=2) + 45.9 × body weight(kg) + 60.0 × thigh circumference (cm) (r2 = 0.745, P estimate = 581.6 cm3). The current work provides evidence of a strong relationship between thigh muscle volume and physical function in the elderly. We also developed a prediction equation model using anthropometric measurements. This model is a simple and noninvasive method for everyday clinical practice and follow-up.

Dynamic prediction of cumulative incidence functions by direct binomial regression.

Science.gov (United States)

Grand, Mia K; de Witte, Theo J M; Putter, Hein

2018-03-25

In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights. We extend the approach by combining it with landmarking to enable dynamic prediction of the cumulative incidence function. The proposed models are very flexible, as they allow the covariates to have complex time-varying effects, and we illustrate how to investigate possible time-varying structures using Wald tests. The models are fitted using generalized estimating equations. The method is applied to bone marrow transplant data and the performance is investigated in a simulation study. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Resting state functional connectivity predicts neurofeedback response

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Dustin eScheinost

2014-09-01

Full Text Available Tailoring treatments to the specific needs and biology of individual patients – personalized medicine – requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD. Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI, to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC and anterior prefrontal cortex, Brodmann area (BA 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Science.gov (United States)

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural

The timing of associative memory formation: frontal lobe and anterior medial temporal lobe activity at associative binding predicts memory

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Hales, J. B.

2011-01-01

The process of associating items encountered over time and across variable time delays is fundamental for creating memories in daily life, such as for stories and episodes. Forming associative memory for temporally discontiguous items involves medial temporal lobe structures and additional neocortical processing regions, including prefrontal cortex, parietal lobe, and lateral occipital regions. However, most prior memory studies, using concurrently presented stimuli, have failed to examine the temporal aspect of successful associative memory formation to identify when activity in these brain regions is predictive of associative memory formation. In the current study, functional MRI data were acquired while subjects were shown pairs of sequentially presented visual images with a fixed interitem delay within pairs. This design allowed the entire time course of the trial to be analyzed, starting from onset of the first item, across the 5.5-s delay period, and through offset of the second item. Subjects then completed a postscan recognition test for the items and associations they encoded during the scan and their confidence for each. After controlling for item-memory strength, we isolated brain regions selectively involved in associative encoding. Consistent with prior findings, increased regional activity predicting subsequent associative memory success was found in anterior medial temporal lobe regions of left perirhinal and entorhinal cortices and in left prefrontal cortex and lateral occipital regions. The temporal separation within each pair, however, allowed extension of these findings by isolating the timing of regional involvement, showing that increased response in these regions occurs during binding but not during maintenance. PMID:21248058

Measure of functional independence dominates discharge outcome prediction after inpatient rehabilitation for stroke.

Science.gov (United States)

Brown, Allen W; Therneau, Terry M; Schultz, Billie A; Niewczyk, Paulette M; Granger, Carl V

2015-04-01

Identifying clinical data acquired at inpatient rehabilitation admission for stroke that accurately predict key outcomes at discharge could inform the development of customized plans of care to achieve favorable outcomes. The purpose of this analysis was to use a large comprehensive national data set to consider a wide range of clinical elements known at admission to identify those that predict key outcomes at rehabilitation discharge. Sample data were obtained from the Uniform Data System for Medical Rehabilitation data set with the diagnosis of stroke for the years 2005 through 2007. This data set includes demographic, administrative, and medical variables collected at admission and discharge and uses the FIM (functional independence measure) instrument to assess functional independence. Primary outcomes of interest were functional independence measure gain, length of stay, and discharge to home. The sample included 148,367 people (75% white; mean age, 70.6±13.1 years; 97% with ischemic stroke) admitted to inpatient rehabilitation a mean of 8.2±12 days after symptom onset. The total functional independence measure score, the functional independence measure motor subscore, and the case-mix group were equally the strongest predictors for any of the primary outcomes. The most clinically relevant 3-variable model used the functional independence measure motor subscore, age, and walking distance at admission (r(2)=0.107). No important additional effect for any other variable was detected when added to this model. This analysis shows that a measure of functional independence in motor performance and age at rehabilitation hospital admission for stroke are predominant predictors of outcome at discharge in a uniquely large US national data set. © 2015 American Heart Association, Inc.

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H)

Science.gov (United States)

Boezeman, Edwin J.; Nieuwenhuijsen, Karen; Sluiter, Judith K.

2016-01-01

Objectives: To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Methods: Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. Results: The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (pvalue and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers. PMID:27010085

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H).

Science.gov (United States)

Boezeman, Edwin J; Nieuwenhuijsen, Karen; Sluiter, Judith K

2016-05-25

To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (ppredictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers.

Functional SNP associated with birth weight in independent populations identified with a permutation step added to GBLUP-GWAS

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This study was conducted as an initial assessment of a newly available genotyping assay containing about 34,000 common SNP included on previous SNP chips, and 199,000 sequence variants predicted to affect gene function. Objectives were to identify functional variants associated with birth weight in...

Handgrip strength predicts functional decline at discharge in hospitalized male elderly: a hospital cohort study.

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Carmen García-Peña

Full Text Available Functional decline after hospitalization is a common adverse outcome in elderly. An easy to use, reproducible and accurate tool to identify those at risk would aid focusing interventions in those at higher risk. Handgrip strength has been shown to predict adverse outcomes in other settings. The aim of this study was to determine if handgrip strength measured upon admission to an acute care facility would predict functional decline (either incident or worsening of preexisting at discharge among older Mexican, stratified by gender. In addition, cutoff points as a function of specificity would be determined. A cohort study was conducted in two hospitals in Mexico City. The primary endpoint was functional decline on discharge, defined as a 30-point reduction in the Barthel Index score from that of the baseline score. Handgrip strength along with other variables was measured at initial assessment, including: instrumental activities of daily living, cognition, depressive symptoms, delirium, hospitalization length and quality of life. All analyses were stratified by gender. Logistic regression to test independent association between handgrip strength and functional decline was performed, along with estimation of handgrip strength test values (specificity, sensitivity, area under the curve, etc.. A total of 223 patients admitted to an acute care facility between 2007 and 2009 were recruited. A total of 55 patients (24.7% had functional decline, 23.46% in male and 25.6% in women. Multivariate analysis showed that only males with low handgrip strength had an increased risk of functional decline at discharge (OR 0.88, 95% CI 0.79-0.98, p = 0.01, with a specificity of 91.3% and a cutoff point of 20.65 kg for handgrip strength. Females had not a significant association between handgrip strength and functional decline. Measurement of handgrip strength on admission to acute care facilities may identify male elderly patients at risk of having functional decline

Handgrip Strength Predicts Functional Decline at Discharge in Hospitalized Male Elderly: A Hospital Cohort Study

Science.gov (United States)

García-Peña, Carmen; García-Fabela, Luis C.; Gutiérrez-Robledo, Luis M.; García-González, Jose J.; Arango-Lopera, Victoria E.; Pérez-Zepeda, Mario U.

2013-01-01

Functional decline after hospitalization is a common adverse outcome in elderly. An easy to use, reproducible and accurate tool to identify those at risk would aid focusing interventions in those at higher risk. Handgrip strength has been shown to predict adverse outcomes in other settings. The aim of this study was to determine if handgrip strength measured upon admission to an acute care facility would predict functional decline (either incident or worsening of preexisting) at discharge among older Mexican, stratified by gender. In addition, cutoff points as a function of specificity would be determined. A cohort study was conducted in two hospitals in Mexico City. The primary endpoint was functional decline on discharge, defined as a 30-point reduction in the Barthel Index score from that of the baseline score. Handgrip strength along with other variables was measured at initial assessment, including: instrumental activities of daily living, cognition, depressive symptoms, delirium, hospitalization length and quality of life. All analyses were stratified by gender. Logistic regression to test independent association between handgrip strength and functional decline was performed, along with estimation of handgrip strength test values (specificity, sensitivity, area under the curve, etc.). A total of 223 patients admitted to an acute care facility between 2007 and 2009 were recruited. A total of 55 patients (24.7%) had functional decline, 23.46% in male and 25.6% in women. Multivariate analysis showed that only males with low handgrip strength had an increased risk of functional decline at discharge (OR 0.88, 95% CI 0.79–0.98, p = 0.01), with a specificity of 91.3% and a cutoff point of 20.65 kg for handgrip strength. Females had not a significant association between handgrip strength and functional decline. Measurement of handgrip strength on admission to acute care facilities may identify male elderly patients at risk of having functional decline, and

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

International Nuclear Information System (INIS)

Goudarzi, Sobhan; Jafari, Sajad; Moradi, Mohammad Hassan; Sprott, J.C.

2016-01-01

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

Energy Technology Data Exchange (ETDEWEB)

Goudarzi, Sobhan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Jafari, Sajad, E-mail: sajadjafari@aut.ac.ir [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Moradi, Mohammad Hassan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Sprott, J.C. [Department of Physics, University of Wisconsin–Madison, Madison, WI 53706 (United States)

2016-02-15

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

Baseline social amotivation predicts 1-year functioning in UHR subjects: A validation and prospective investigation.

Science.gov (United States)

Lam, Max; Abdul Rashid, Nur Amirah; Lee, Sara-Ann; Lim, Jeanette; Foussias, George; Fervaha, Gagan; Ruhrman, Stephan; Remington, Gary; Lee, Jimmy

2015-12-01

Social amotivation and diminished expression have been reported to underlie negative symptomatology in schizophrenia. In the current study we sought to establish and validate these negative symptom domains in a large cohort of schizophrenia subjects (n=887) and individuals who are deemed to be Ultra-High Risk (UHR) for psychosis. Confirmatory factor analysis conducted on PANSS item domains demonstrate that the dual negative symptom domains exist in schizophrenia and UHR subjects. We further sought to examine if these negative symptom domains were associated with functioning in UHR subjects. Linear regression analyses confirmed that social amotivation predicted functioning in UHR subjects prospectively at 1 year follow up. Results suggest that the association between social amotivation and functioning is generalisable beyond schizophrenia populations to those who are at-risk of developing psychosis. Social amotivation may be an important dimensional clinical construct to be studied across a range of psychiatric conditions. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Association between high-density lipoprotein cholesterol level and pulmonary function in healthy Korean adolescents: the JS high school study.

Science.gov (United States)

Park, Ji Hye; Mun, Seyeon; Choi, Dong Phil; Lee, Joo Young; Kim, Hyeon Chang

2017-12-11

Accumulating evidence suggests that high-density lipoprotein (HDL) cholesterol is associated with pulmonary function and pulmonary disorders. The aim of this study was to evaluate the association between HDL cholesterol and pulmonary function in healthy adolescents. This cross-sectional study was based on data collected for the JS High School study. The analysis included 644 adolescents (318 male and 326 female) aged 15-16 years old and free from asthma or chronic obstructive pulmonary disease. Fasting blood samples were collected for hematologic and biochemical assessment. Forced vital capacity volume (FVC) and forced expiratory volume in the 1 s (FEV1) were measured using dry-rolling-seal spirometry. The associations between HDL cholesterol and pulmonary function were analyzed using multiple linear regression models. Among male adolescents, an increase of 1.0 mg/dL in HDL cholesterol was associated with 10 mL decrease in FVC (p = 0.013) and FEV1 (p = 0.013) after adjusting for age, height, weight, alcohol drinking, smoking, physical activity, systolic blood pressure, total cholesterol, triglyceride, and monthly household income. Percent predicted values of FVC (p = 0.036) and FEV1 (p = 0.017) were also inversely associated with HDL cholesterol. However, among female adolescents, HDL cholesterol level was not significantly associated with absolute or percent predictive value of FVC and FEV1. Higher HDL cholesterol level may be associated with decreased pulmonary function among healthy male adolescents. The sex differences observed in the association between HDL cholesterol and pulmonary function need further investigation.

Improved survival prediction from lung function data in a large population sample

DEFF Research Database (Denmark)

Miller, M.R.; Pedersen, O.F.; Lange, P.

2008-01-01

Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease.......1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP....... In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method...

IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

Science.gov (United States)

Wong, Aaron K; Krishnan, Arjun; Yao, Victoria; Tadych, Alicja; Troyanskaya, Olga G

2015-07-01

IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

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Douglas D Thompson

Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

Re: Cross-Sectional and Longitudinal Associations of Sexual Function with Urinary Tract Symptoms in Men with Benign Prostatic Hyperplasia

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Fwu C-W

2015-03-01

Full Text Available In this study authors examine the cross-sectional associations between baseline characteristics and sexual function and the longitudinal associations between change in lower urinary tract symptoms and change in sexual function among men with benign prostatic hyperplasia. The cross-sectional cohort included 2.916 men who completed Brief Male Sexual Function Inventory (BMSFI at baseline. The longitudinal cohort included 672 men who were randomized to placebo. Increased age, less education, obesity and severe lower urinary tract symptoms were found significantly associated poorer sexual drive, erectile dysfunction, ejaculatory function, sexual problem assessment and overall satisfaction. However, none of these baseline characteristics predicted change in sexual function in the longitudinal cohort. The decline in sexual dysfunction associated with worsening of lower urinary tract symptoms in men assigned to placebo was small.

Clinical and functional criteria for predicting asthma in infants

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Yu. L. Mizemitskiy

2015-01-01

Full Text Available Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability assessment were used. Immunological examination included determination of the serum levels of immunoglobulin E and interleuMn-17A. The infants who had sustained acute obstructive bronchitis were followed up for 12-36 months. Results. The infants who had sustained acute obstructive bronchitis in the presence of mild perinatal CNS damage caused by hypoxia were typified by high respiratory morbidity; early-onset bronchial obstruction; long-term bronchial obstruction relief; high incidence of grade 2 respiratory failure in acute obstructive bronchitis. These patients developed asthma more often than twice and repeated episodes of bronchial obstruction. ROC analysis was used to elaborate clinical and functional criteria for predicting the development of asthma in infants. Conclusion. The proposed additional clinical and functional criteria characterizing external respiratory dysfunction and autonomic homeostatic changes contribute to the early diagnosis of asthma and substantially increase the validity of prediction of its development in children younger than 3 years, which is of great importance for goal-oriented preventive measures.

Prediction of postoperative respiratory function of lung cancer patients using 99mTc-MAA SPECT

International Nuclear Information System (INIS)

Kokubo, Mitsuharu; Sakai, Satoshi; Miyata, Tomoyuki

1991-01-01

In this study, we evaluated the correlation between the predicted postoperative respiratory function using 99m Tc-MAA SPECT with chest CT and the postoperative respiratory function. 99m Tc-MAA SPECT were performed in 10 patients with lung cancer who underwent lobectomy. We measured the fractional loss in the pulmonary flow of the lobe to be resected using 99m Tc-MAA SPECT with chest CT. The value of predicted postoperative respiratory function was measured as follows: the value of predicted postoperative respiratory function=the value of preoperative respiratory function x (1-the fractional loss in the pulmonary flow of the lobe to be resected). Postoperative forced vital capacity (FVC), forced expiratory volume in the first second (FEV 1.0 ) and % vital capacity (%VC) were predicted in this study, and were compared to the respiratory function at three months and six months after operation. The predicted postoperative respiratory function was highly correlated with the actually observed postoperative respiratory function. (author)

Higher Mobility Scores in Patients with Cystic Fibrosis Are Associated with Better Lung Function

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Aneesha Thobani

2015-01-01

Full Text Available Objective. The purpose of this study was to determine whether mobility and physical activity were associated with lung function in adults with cystic fibrosis (CF. Design. This was a prospective cohort observational study in an urban, academic, specialized care center. Participants were ambulatory, nonhospitalized adults with CF. Main Outcome Measures. Mobility was assessed monthly by the Life-Space Assessment (LSA questionnaire and quarterly by pedometer. Lung function was assessed by spirometry. Results. Twenty-seven subjects participated. Subjects recorded mean pedometer steps of 20,213 ± 11,331 over three days and FEV1% predicted of 77.48% ± 22.60% over one year. The LSA score at enrollment was correlated with initial pedometer steps (r=0.42 and P=0.03, and mean LSA score over one year was correlated with mean number of steps (r=0.51 and P=0.007. LSA mobility and pedometer scores were correlated with FEV1% predicted at enrollment and throughout the study. Conclusions. Mobility and physical activity measured by LSA questionnaire and pedometer are positively associated with lung function in adults with CF. This study confirms the importance of mobility and physical activity and supports the utility of a simple office-based questionnaire as a measure of mobility in adults with CF.

Higher mobility scores in patients with cystic fibrosis are associated with better lung function.

Science.gov (United States)

Thobani, Aneesha; Alvarez, Jessica A; Blair, Shaina; Jackson, Kaila; Gottlieb, Eric R; Walker, Seth; Tangpricha, Vin

2015-01-01

The purpose of this study was to determine whether mobility and physical activity were associated with lung function in adults with cystic fibrosis (CF). This was a prospective cohort observational study in an urban, academic, specialized care center. Participants were ambulatory, nonhospitalized adults with CF. Mobility was assessed monthly by the Life-Space Assessment (LSA) questionnaire and quarterly by pedometer. Lung function was assessed by spirometry. Twenty-seven subjects participated. Subjects recorded mean pedometer steps of 20,213 ± 11,331 over three days and FEV1% predicted of 77.48% ± 22.60% over one year. The LSA score at enrollment was correlated with initial pedometer steps (r = 0.42 and P = 0.03), and mean LSA score over one year was correlated with mean number of steps (r = 0.51 and P = 0.007). LSA mobility and pedometer scores were correlated with FEV1% predicted at enrollment and throughout the study. Mobility and physical activity measured by LSA questionnaire and pedometer are positively associated with lung function in adults with CF. This study confirms the importance of mobility and physical activity and supports the utility of a simple office-based questionnaire as a measure of mobility in adults with CF.

FDG F18/Rest Tl 201 SPECT patterns in recent myocardial infarction. Predictive value for regional function recovery

Energy Technology Data Exchange (ETDEWEB)

Massardo, Teresa [Universidad de Chile, Hospital Clinico. Centro de Medicina Nuclear, Santiago (Chile); Gonzalez, Patricio; Coll, Claudia; Yovanovich, Jorge; Jofre, M Josefina; Humeres, Pamela; Sierralta, Paulina; Chamorro, Hernan; Ramirez, Alfredo; Kunstmann, Sonia; Lopez, Hector; Aramburu, Ivonne; Bru, Solange [Universidad de Chile, Santiago (Chile). Hospital Clinico. Centros de Medicina Nuclear e Cardiovascular; Clinica Santa Maria, Santiago [Chile

2003-04-01

Background: detecting viability is important after recent myocardial infarction (MI). SPECT FDG/Tl flow-metabolism patterns for predicting functional recovery were analyzed in this setting. Method: forty-one patients were studied (56+-12 years; 80% males) with Tl 201 at rest and FDG F 18 SPECT at a mean of 8.9 days post MI (range:1-24). All had baseline and 3 month follow-up echocardiography (Echo) and initial coronary angiography. They were submitted to primary PTCA in 12 cases, late PTCA in 15 and bypass surgery in 10 and thrombolysis was performed in 4 patients as only procedure. A total of 345 culprit artery territory segments were interpreted by 3 nuclear independent observers. Analysis included segments with or without abnormal motion. Results: FDG/Tl 201 on patient basis, had: sensitivity 91%; specificity 56%; positive predictive value 88 %; negative predictive value (NPV) 63% and accuracy 83%. The analysis of segments with abnormal contractility showed values of 67%, 69%, 44%, 85% and 68%, respectively. Reverse mismatch with FDG/Tl appears to predict viability similarly to classical mismatch; severe or moderate match was highly associated with no functional recovery (NPV 85%). Conclusion: flow-perfusion patterns are variable in recent MI. FDG/Tl 201 SPECT has acceptable accuracy for predicting functional recovery and excellent NPV to further exclude viability (author)

FDG F18/Rest Tl 201 SPECT patterns in recent myocardial infarction. Predictive value for regional function recovery

International Nuclear Information System (INIS)

Massardo, Teresa; Gonzalez, Patricio; Coll, Claudia; Yovanovich, Jorge; Jofre, M. Josefina; Humeres, Pamela; Sierralta, Paulina; Chamorro, Hernan; Ramirez, Alfredo; Kunstmann, Sonia; Lopez, Hector; Aramburu, Ivonne; Bru, Solange; Clinica Santa Maria, Santiago

2003-01-01

Background: detecting viability is important after recent myocardial infarction (MI). SPECT FDG/Tl flow-metabolism patterns for predicting functional recovery were analyzed in this setting. Method: forty-one patients were studied (56+-12 years; 80% males) with Tl 201 at rest and FDG F 18 SPECT at a mean of 8.9 days post MI (range:1-24). All had baseline and 3 month follow-up echocardiography (Echo) and initial coronary angiography. They were submitted to primary PTCA in 12 cases, late PTCA in 15 and bypass surgery in 10 and thrombolysis was performed in 4 patients as only procedure. A total of 345 culprit artery territory segments were interpreted by 3 nuclear independent observers. Analysis included segments with or without abnormal motion. Results: FDG/Tl 201 on patient basis, had: sensitivity 91%; specificity 56%; positive predictive value 88 %; negative predictive value (NPV) 63% and accuracy 83%. The analysis of segments with abnormal contractility showed values of 67%, 69%, 44%, 85% and 68%, respectively. Reverse mismatch with FDG/Tl appears to predict viability similarly to classical mismatch; severe or moderate match was highly associated with no functional recovery (NPV 85%). Conclusion: flow-perfusion patterns are variable in recent MI. FDG/Tl 201 SPECT has acceptable accuracy for predicting functional recovery and excellent NPV to further exclude viability (author)

Prediction of postoperative lung function after pulmonary resection

International Nuclear Information System (INIS)

Yoshikawa, Koichi

1988-01-01

Lung scintigraphy and ordinary lung function test as well as split lung function test by using bronchospirometry was performed in 78 patients with primary lung cancer and clinical significance of ventilation and perfusion scintigraphy was evaluated. Results obtained from this study are as follows. 1) The ratio of right VC to total VC obtained by preoperative bronchospirometry was well correlated to the ratio of right lung count to the total lung count obtained by ventiration and/or perfusion scintigraphy (r = 0.84, r = 0.69). 2) Evaluation of the data obtained from the patients undergoing pneumonectomy indicated that the right and left VC obtained preoperatively by bronchospirometry have their clinical significance only in the form of left to right ratio not in the form their absolure value. 3) As to the reliability of predicting the residual vital capacity after pneumonectomy on the basis of left-to-right of lung scintigraphy, ventilation scintigraphy is more reliable than perfusion scintigraphy. 4) Irrespective of using ventilation scintigraphy or perfusion scintigraphy, Ali's formular showed high reliability in predicting the residual vital capacity as well as FEV 1.0 after lobectomy. 5) Reduction of the perfusion rate in the operated side of the lung is more marked than of the ventilation rate, resulting in a significant elevation of ventilation/perfusion ratio of the operated side of the lung. From the results descrived above, it can be said that lung ventilation and perfusion scintigraphy are very useful method to predict the residual lung function as well as the change of ventilation/perfusion ratio after pulmonary resection. (author)

Executive functioning performance predicts subjective and physiological acute stress reactivity: preliminary results.

Science.gov (United States)

Hendrawan, Donny; Yamakawa, Kaori; Kimura, Motohiro; Murakami, Hiroki; Ohira, Hideki

2012-06-01

Individual differences in baseline executive functioning (EF) capacities have been shown to predict state anxiety during acute stressor exposure. However, no previous studies have clearly demonstrated the relationship between EF and physiological measures of stress. The present study investigated the efficacy of several well-known EF tests (letter fluency, Stroop test, and Wisconsin Card Sorting Test) in predicting both subjective and physiological stress reactivity during acute psychosocial stress exposure. Our results show that letter fluency served as the best predictor for both types of reactivity. Specifically, the higher the letter fluency score, the lower the acute stress reactivity after controlling for the baseline stress response, as indicated by lower levels of state anxiety, negative mood, salivary cortisol, and skin conductance. Moreover, the predictive power of the letter fluency test remained significant for state anxiety and cortisol indices even after further adjustments for covariates by adding the body mass index (BMI) as a covariate. Thus, good EF performance, as reflected by high letter fluency scores, may dampen acute stress responses, which suggests that EF processes are directly associated with aspects of stress regulation. Copyright © 2012 Elsevier B.V. All rights reserved.

Usefulness of MR coronal imaging of the ''pyramidal line''. Predictive value in motor function of stroke patients

International Nuclear Information System (INIS)

Satoh, Kenichi; Matsuzaki, Takayuki; Shimazaki, Mitsunori

1997-01-01

A coronal image was obtained along a straight line between the front edge of the medulla and the deepest point of the interpeduncular cistern in the midsagittal plane (the ''pyramidal line''). This coronal image along the pyramidal line revealed the pyramidal tract extending from the internal capsule down to the medulla. Using this technique, we studied 25 patients with motor deficit associated with cerebrovascular disease. We predicted the possibility of their recovery in the subacute stage. We were able to predict the recovery in 23 patients (92%). We conclude that a coronal image along the pyramidal line is useful for the understanding of relation between pyramidal tract and lesion and for predicting motor function. (author)

Usefulness of MR coronal imaging of the ``pyramidal line``. Predictive value in motor function of stroke patients

Energy Technology Data Exchange (ETDEWEB)

Satoh, Kenichi; Matsuzaki, Takayuki; Shimazaki, Mitsunori [Hakodate Red Cross Hospital, Hokkaido (Japan)

1997-06-01

A coronal image was obtained along a straight line between the front edge of the medulla and the deepest point of the interpeduncular cistern in the midsagittal plane (the ``pyramidal line``). This coronal image along the pyramidal line revealed the pyramidal tract extending from the internal capsule down to the medulla. Using this technique, we studied 25 patients with motor deficit associated with cerebrovascular disease. We predicted the possibility of their recovery in the subacute stage. We were able to predict the recovery in 23 patients (92%). We conclude that a coronal image along the pyramidal line is useful for the understanding of relation between pyramidal tract and lesion and for predicting motor function. (author)

Inductive matrix completion for predicting gene-disease associations.

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Natarajan, Nagarajan; Dhillon, Inderjit S

2014-06-15

Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has bigdata.ices.utexas.edu/project/gene-disease. © The Author 2014. Published by Oxford University Press.

A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

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Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

Water hammer prediction and control: the Green's function method

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Xuan, Li-Jun; Mao, Feng; Wu, Jie-Zhi

2012-04-01

By Green's function method we show that the water hammer (WH) can be analytically predicted for both laminar and turbulent flows (for the latter, with an eddy viscosity depending solely on the space coordinates), and thus its hazardous effect can be rationally controlled and minimized. To this end, we generalize a laminar water hammer equation of Wang et al. (J. Hydrodynamics, B2, 51, 1995) to include arbitrary initial condition and variable viscosity, and obtain its solution by Green's function method. The predicted characteristic WH behaviors by the solutions are in excellent agreement with both direct numerical simulation of the original governing equations and, by adjusting the eddy viscosity coefficient, experimentally measured turbulent flow data. Optimal WH control principle is thereby constructed and demonstrated.

The Role of Family Functioning, Peer Attachment and Academic Performance in predicting of Happiness in Adolescent Girls

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Maryam Salehzadeh

2017-02-01

Full Text Available The purpose of this research was to determine the role of family functioning (FF, academic performance (EP and peer attachment (PA in predicting of happiness adolescent girls. Therefore, 344 high school female students in Yazd were selected through multi-stage random sampling and were asked to complete the Oxford Happiness Questionnaire, Family Assessment Device (FAD, and Inventory of Parent and Peer Attachment. Students' grade point average was considered as the measure of academic performance.  The results of analysis of regression showed that all the subscales of family functioning and peers attachment and also academic performance have significant correlation with happiness yet only "the roles and relationships" of family performance and peers attachment could predict happiness. Attachment to peers was the strongest factor. However, academic performance did not have a significant role in prediction of student's happiness. In accordance with the findings of developmental psychology, peers and family are the two most important psychological constructs that have the most significant roles in predicting the happiness of adolescent girls. But academic performance did not have a significant role in predicting student's happiness, thereby it can challenge the social common belief in educational systems regarding the strong association between academic performance and well-being and happiness.

Prediction of basal metabolic rate in overweight/obese and non-obese subjects and its relation to pulmonary function tests.

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Merghani, Tarig H; Alawad, Azza O; Ibrahim, Rihab M; Abdelmoniem, Asim M

2015-08-15

Few studies investigated the association between basal metabolic rate (BMR) and indicators of pulmonary function. This study was conducted to estimate BMR in overweight/obese and non-obese healthy subjects using four commonly used predictive equations and to investigate its relation to the indicators of lung function tests (LFT). A cross sectional study was conducted in Tabuk University, Tabuk, Saudi Arabia. A total of 201 students (98 males and 103 females) participated in the study. Four different values of BMR were calculated for each participant using four different predictive equations (Harris-Benedict, Mifflin, FAO/WHO/UNU and Henry-Rees). A portable All-flow spirometer (Clement Clarke International, Harlow, UK) was used for measurements of LFT. Significantly higher values of spirometric indicators (p BMR values predicted with the four equations were significantly higher in the males compared to the females and among the overweight/obese compared to the non-obese subjects (p BMR values and the indicators of LFT was statistically insignificant (p > 0.05). Mean values of LFT indicators are not related to the estimated values of BMR. A practical calculation of BMR based on direct measurement of oxygen consumption is recommended to confirm the absence of this association.

RANDOM FUNCTIONS AND INTERVAL METHOD FOR PREDICTING THE RESIDUAL RESOURCE OF BUILDING STRUCTURES

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Shmelev Gennadiy Dmitrievich

2017-11-01

Full Text Available Subject: possibility of using random functions and interval prediction method for estimating the residual life of building structures in the currently used buildings. Research objectives: coordination of ranges of values to develop predictions and random functions that characterize the processes being predicted. Materials and methods: when performing this research, the method of random functions and the method of interval prediction were used. Results: in the course of this work, the basic properties of random functions, including the properties of families of random functions, are studied. The coordination of time-varying impacts and loads on building structures is considered from the viewpoint of their influence on structures and representation of the structures’ behavior in the form of random functions. Several models of random functions are proposed for predicting individual parameters of structures. For each of the proposed models, its scope of application is defined. The article notes that the considered approach of forecasting has been used many times at various sites. In addition, the available results allowed the authors to develop a methodology for assessing the technical condition and residual life of building structures for the currently used facilities. Conclusions: we studied the possibility of using random functions and processes for the purposes of forecasting the residual service lives of structures in buildings and engineering constructions. We considered the possibility of using an interval forecasting approach to estimate changes in defining parameters of building structures and their technical condition. A comprehensive technique for forecasting the residual life of building structures using the interval approach is proposed.

Plant functional traits predict green roof ecosystem services.

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Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

2015-02-17

Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services.

Low free triiodothyronine predicts poor functional outcome after acute ischemic stroke.

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Suda, Satoshi; Muraga, Kanako; Kanamaru, Takuya; Okubo, Seiji; Abe, Arata; Aoki, Junya; Suzuki, Kentaro; Sakamoto, Yuki; Shimoyama, Takashi; Nito, Chikako; Kimura, Kazumi

2016-09-15

The aim of this study was to investigate the association of admission serum thyroid hormone concentration with clinical characteristics and functional outcomes in patients after acute ischemic stroke. We retrospectively enrolled 398 consecutive patients admitted to our stroke center between July 2010 and April 2012. Serum thyroid stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) were evaluated upon admission. Neurological severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) upon admission and the modified Rankin Scale (mRS) upon discharge. Poor outcome was defined as a mRS score of 3-5 or death (mRS score 6). Separate analyses were conducted according to outcome and quartile serum FT3 concentration. In total, 164 patients (41.2%) demonstrated a poor outcome. Age, male gender, blood glucose level, arterial fibrillation, dyslipidemia, smoking, NIHSS score, cardioembolic stroke type, and periventricular hyperintensities, but not FT4 or TSH, were significantly associated with poor functional outcome. Furthermore, poor functional outcome was independently associated with low FT3 (<2.29pg/mL). In comparisons between FT3 quartiles (Q1 [≤2.11pg/mL], Q2 [2.12-2.45pg/mL], Q3 [2.46-2.77pg/mL], Q4 [≥2.78pg/mL]), patients with poor outcomes were more frequent in Q1 than in Q4 after multivariate adjustment. Death was more frequent in Q1 than in Q4 after adjustment for risk factors and comorbidities, but this difference was non-significant after additional adjustment for age and NIHSS score. Our data suggest that a lower FT3 value upon admission may predict a poor functional outcome in patients with acute ischemic stroke. Further large-scale prospective studies are required to clarify the role of thyroid hormone in the acute phase of ischemic stroke. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of postoperative respiratory function of lung cancer patients using quantitative lung scans

International Nuclear Information System (INIS)

Konishi, Hiroshi

1982-01-01

Quantitative sup(99m)Tc-MISA inhalation scan and sup(99m)Tc-MAA perfusion scan were performed in 35 patients with lung cancer who underwent lobectomies. Quantitative 133 Xe ventilation-perfusion scans were also performed in 34 patients with lung cancer who underwent lobectomies. To predict functional loss after lobectomy, the proportion of the No. of segments in the lobe to be resected to the No. of entire segments of that lung was provided for the study. Postoperative FVC, FEVsub(1.0) and MVV were predicted in the study, and which were compared to the respiratory function at one month after operation and more than four months after operation. The predicted postoperative respiratory function was highly correlated with the actually observed postoperative respiratory function (0.7413 lt r lt 0.9278, p lt 0.001). In this study, the postoperative respiratory function was proven to be quite accurately predicted preoperatively with combination of quantitative lung scans and spirometric respiratory function. Therefore this method is useful not only for judgement of operative indication but also for choice of operative method and for counterplan of postoperative respiratory insufficiency. (J.P.N.)

Deficits of entropy modulation in schizophrenia are predicted by functional connectivity strength in the theta band and structural clustering.

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Gomez-Pilar, Javier; de Luis-García, Rodrigo; Lubeiro, Alba; de Uribe, Nieves; Poza, Jesús; Núñez, Pablo; Ayuso, Marta; Hornero, Roberto; Molina, Vicente

2018-01-01

Spectral entropy (SE) allows comparing task-related modulation of electroencephalogram (EEG) between patients and controls, i.e. spectral changes of the EEG associated to task performance. A SE modulation deficit has been replicated in different schizophrenia samples. To investigate the underpinnings of SE modulation deficits in schizophrenia, we applied graph-theory to EEG recordings during a P300 task and fractional anisotropy (FA) data from diffusion tensor imaging in 48 patients (23 first episodes) and 87 healthy controls. Functional connectivity was assessed from phase-locking values among sensors in the theta band, and structural connectivity was based on FA values for the tracts connecting pairs of regions. From those data, averaged clustering coefficient (CLC), characteristic path-length (PL) and connectivity strength (CS, also known as density) were calculated for both functional and structural networks. The corresponding functional modulation values were calculated as the difference in SE and CLC, PL and CS between the pre-stimulus and response windows during the task. The results revealed a higher functional CS in the pre-stimulus window in patients, predictive of smaller modulation of SE in this group. The amount of increase in theta CS from pre-stimulus to response related to SE modulation in patients and controls. Structural CLC was associated with SE modulation in the patients. SE modulation was predictive of negative symptoms, whereas CLC and PL modulation was associated with cognitive performance in the patients. These results support that a hyperactive functional connectivity and/or structural connective deficits in the patients hamper the dynamical modulation of connectivity underlying cognition.

DIANA-microT web server: elucidating microRNA functions through target prediction.

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Maragkakis, M; Reczko, M; Simossis, V A; Alexiou, P; Papadopoulos, G L; Dalamagas, T; Giannopoulos, G; Goumas, G; Koukis, E; Kourtis, K; Vergoulis, T; Koziris, N; Sellis, T; Tsanakas, P; Hatzigeorgiou, A G

2009-07-01

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

Application of Functional Use Predictions to Aid in Structure ...

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Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

Going outdoors daily predicts long-term functional and health benefits among ambulatory older people.

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Jacobs, Jeremy M; Cohen, Aaron; Hammerman-Rozenberg, Robert; Azoulay, Daniel; Maaravi, Yoram; Stessman, Jochanan

2008-04-01

This article examines the association between frequency of going out of the house and health and functional status among older people. A randomly chosen cohort of ambulatory participants born in 1920 or 1921 from the Jerusalem Longitudinal Study underwent assessments for health, functional, and psychosocial variables at ages 70 and 77. Twelve-year mortality data were collected. Women went out daily less than did men. Participants going out daily at age 70 reported significantly fewer new complaints at age 77 of musculoskeletal pain, sleep problems, urinary incontinence, and decline in activities of daily living (ADLs). Logistic regression analysis indicated that not going out daily at age 70 was predictive of subsequent dependence in ADL, poor self-rated health, and urinary incontinence at age 77. Going out daily is beneficial among independent older people, correlating with reduced functional decline and improved health measures.

Prediction of microbe-disease association from the integration of neighbor and graph with collaborative recommendation model.

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Huang, Yu-An; You, Zhu-Hong; Chen, Xing; Huang, Zhi-An; Zhang, Shanwen; Yan, Gui-Ying

2017-10-16

Accumulating clinical researches have shown that specific microbes with abnormal levels are closely associated with the development of various human diseases. Knowledge of microbe-disease associations can provide valuable insights for complex disease mechanism understanding as well as the prevention, diagnosis and treatment of various diseases. However, little effort has been made to predict microbial candidates for human complex diseases on a large scale. In this work, we developed a new computational model for predicting microbe-disease associations by combining two single recommendation methods. Based on the assumption that functionally similar microbes tend to get involved in the mechanism of similar disease, we adopted neighbor-based collaborative filtering and a graph-based scoring method to compute association possibility of microbe-disease pairs. The promising prediction performance could be attributed to the use of hybrid approach based on two single recommendation methods as well as the introduction of Gaussian kernel-based similarity and symptom-based disease similarity. To evaluate the performance of the proposed model, we implemented leave-one-out and fivefold cross validations on the HMDAD database, which is recently built as the first database collecting experimentally-confirmed microbe-disease associations. As a result, NGRHMDA achieved reliable results with AUCs of 0.9023 ± 0.0031 and 0.9111 in the validation frameworks of fivefold CV and LOOCV. In addition, 78.2% microbe samples and 66.7% disease samples are found to be consistent with the basic assumption of our work that microbes tend to get involved in the similar disease clusters, and vice versa. Compared with other methods, the prediction results yielded by NGRHMDA demonstrate its effective prediction performance for microbe-disease associations. It is anticipated that NGRHMDA can be used as a useful tool to search the most potential microbial candidates for various diseases, and therefore

Fungal NRPS-dependent siderophores: From function to prediction

DEFF Research Database (Denmark)

Sørensen, Jens Laurids; Knudsen, Michael; Hansen, Frederik Teilfeldt

2014-01-01

discuss the function of siderophores in relation to fungal iron uptake mechanisms and their importance for coexistence with host organisms. The chemical nature of the major groups of siderophores and their regulation is described along with the function and architecture of the large multi-domain enzymes...... responsible for siderophore synthesis, namely the non-ribosomal peptide synthetases (NRPSs). Finally, we present the most recent advances in our understanding of the structural biology of fungal NRPSs and discuss opportunities for the development of a fungal NRPS prediction server...

Stressful life events predict delayed functional recovery following treatment for mania in bipolar disorder.

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Yan-Meier, Leslie; Eberhart, Nicole K; Hammen, Constance L; Gitlin, Michael; Sokolski, Kenneth; Altshuler, Lori

2011-04-30

Identifying predictors of functional recovery in bipolar disorder is critical to treatment efforts to help patients re-establish premorbid levels of role adjustment following an acute manic episode. The current study examined the role of stressful life events as potential obstacles to recovery of functioning in various roles. 65 patients with bipolar I disorder participated in a longitudinal study of functional recovery following clinical recovery from a manic episode. Stressful life events were assessed as predictors of concurrent vs. delayed recovery of role functioning in 4 domains (friends, family, home duties, work/school). Despite clinical recovery, a subset of patients experienced delayed functional recovery in various role domains. Moreover, delayed functional recovery was significantly associated with presence of one or more stressors in the prior 3 months, even after controlling for mood symptoms. Presence of a stressor predicted longer time to functional recovery in life domains, up to 112 days in work/school. Interventions that provide monitoring, support, and problem-solving may be needed to help prevent or mitigate the effects of stress on functional recovery. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Characterization and Prediction of Chemical Functions and ...

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Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

Nanoparticles-cell association predicted by protein corona fingerprints

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Palchetti, S.; Digiacomo, L.; Pozzi, D.; Peruzzi, G.; Micarelli, E.; Mahmoudi, M.; Caracciolo, G.

2016-06-01

In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a ``protein corona'' layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø ~ 100-250 nm) and surface chemistry (unmodified and PEGylated) to investigate the relationships between NP physicochemical properties (nanoparticle size, aggregation state and surface charge), protein corona fingerprints (PCFs), and NP-cell association. We found out that none of the NPs' physicochemical properties alone was exclusively able to account for association with human cervical cancer cell line (HeLa). For the entire library of NPs, a total of 436 distinct serum proteins were detected. We developed a predictive-validation modeling that provides a means of assessing the relative significance of the identified corona proteins. Interestingly, a minor fraction of the HC, which consists of only 8 PCFs were identified as main promoters of NP association with HeLa cells. Remarkably, identified PCFs have several receptors with high level of expression on the plasma membrane of HeLa cells.In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a ``protein corona'' layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø ~ 100-250 nm) and surface

Organization of intrinsic functional brain connectivity predicts decisions to reciprocate social behavior.

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Cáceda, Ricardo; James, G Andrew; Gutman, David A; Kilts, Clinton D

2015-10-01

Reciprocation of trust exchanges is central to the development of interpersonal relationships and societal well-being. Understanding how humans make pro-social and self-centered decisions in dyadic interactions and how to predict these choices has been an area of great interest in social neuroscience. A functional magnetic resonance imaging (fMRI) based technology with potential clinical application is the study of resting state brain connectivity. We tested if resting state connectivity may predict choice behavior in a social context. Twenty-nine healthy adults underwent resting state fMRI before performing the Trust Game, a two person monetary exchange game. We assessed the ability of patterns of resting-state functional brain organization, demographic characteristics and a measure of moral development, the Defining Issues Test (DIT-2), to predict individuals' decisions to reciprocate money during the Trust Game. Subjects reciprocated in 74.9% of the trials. Independent component analysis identified canonical resting-state networks. Increased functional connectivity between the salience (bilateral insula/anterior cingulate) and central executive (dorsolateral prefrontal cortex/ posterior parietal cortex) networks significantly predicted the choice to reciprocate pro-social behavior (R(2) = 0.20, p = 0.015). Stepwise linear regression analysis showed that functional connectivity between these two networks (p = 0.002), age (p = 0.007) and DIT-2 personal interest schema score (p = 0.032) significantly predicted reciprocity behavior (R(2) = 0.498, p = 0.001). Intrinsic functional connectivity between neural networks in conjunction with other individual characteristics may be a valuable tool for predicting performance during social interactions. Future replication and temporal extension of these findings may bolster the understanding of decision making in clinical, financial and marketing settings. Copyright © 2015 Elsevier B.V. All rights reserved.

Delivery Mode and the Transition of Pioneering Gut-Microbiota Structure, Composition and Predicted Metabolic Function

Directory of Open Access Journals (Sweden)

Noel T. Mueller

2017-12-01

Full Text Available Cesarean (C-section delivery, recently shown to cause excess weight gain in mice, perturbs human neonatal gut microbiota development due to the lack of natural mother-to-newborn transfer of microbes. Neonates excrete first the in-utero intestinal content (referred to as meconium hours after birth, followed by intestinal contents reflective of extra-uterine exposure (referred to as transition stool 2 to 3 days after birth. It is not clear when the effect of C-section on the neonatal gut microbiota emerges. We examined bacterial DNA in carefully-collected meconium, and the subsequent transitional stool, from 59 neonates [13 born by scheduled C-section and 46 born by vaginal delivery] in a private hospital in Brazil. Bacterial DNA was extracted, and the V4 region of the 16S rRNA gene was sequenced using the Illumina MiSeq (San Diego, CA, USA platform. We found evidence of bacterial DNA in the majority of meconium samples in our study. The bacterial DNA structure (i.e., beta diversity of meconium differed significantly from that of the transitional stool microbiota. There was a significant reduction in bacterial alpha diversity (e.g., number of observed bacterial species and change in bacterial composition (e.g., reduced Proteobacteria in the transition from meconium to stool. However, changes in predicted microbiota metabolic function from meconium to transitional stool were only observed in vaginally-delivered neonates. Within sample comparisons showed that delivery mode was significantly associated with bacterial structure, composition and predicted microbiota metabolic function in transitional-stool samples, but not in meconium samples. Specifically, compared to vaginally delivered neonates, the transitional stool of C-section delivered neonates had lower proportions of the genera Bacteroides, Parabacteroides and Clostridium. These differences led to C-section neonates having lower predicted abundance of microbial genes related to metabolism of

The Temporal Association Between Executive Function and Life-Space Mobility in Old Age.

Science.gov (United States)

Poranen-Clark, Taina; von Bonsdorff, Mikaela B; Rantakokko, Merja; Portegijs, Erja; Eronen, Johanna; Pynnönen, Katja; Eriksson, Johan G; Viljanen, Anne; Rantanen, Taina

2018-05-09

Life-space mobility, an indicator of community mobility, describes person's movements in terms of the distance from home, the frequency of movement, and the need of assistance for movement. Executive function (EF) is a higher-order cognitive function that supervises motor control and plays a key role in a person's ability to function independently. Cognitive impairment often co-occurs with restricted life-space mobility; however, the direction of the longitudinal associations between EF and life-space mobility is unclear. The aim of this study was to investigate the temporal associations between EF and life-space mobility among community-dwelling older people. One hundred eight community-dwelling persons aged 76 to 91 years participated in the 2 year follow-up study. EF was measured with the Trail Making Test. The Life-Space Assessment (range 0-120, higher scores indicate more mobility) was used to assess life-space mobility. Cross-lagged model design was used to examine longitudinal relationship between EF and life-space mobility. The model was adjusted for age and gender. Average age of participants at baseline was 82.2 (SD 4.1) years and 59% were women. Better EF at baseline predicted higher life-space mobility at follow-up (path coefficient = 3.81, 95% confidential interval; 0.84, 6.78, p = .012), whereas baseline life-space mobility did not predict EF at follow-up. EF was a determinant of life-space mobility. Supporting EF may enhance maintaining independence and active participation in old age.

Challenges in microbial ecology: Building predictive understanding of community function and dynamics

DEFF Research Database (Denmark)

Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...... is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved....

Predicted equations for ventilatory function among Kuching (Sarawak, Malaysia) population.

Science.gov (United States)

Djojodibroto, R D; Pratibha, G; Kamaluddin, B; Manjit, S S; Sumitabha, G; Kumar, A Deva; Hashami, B

2009-12-01

Spirometry data of 869 individuals (males and females) between the ages of 10 to 60 years were analyzed. The analysis yielded the following conclusions: 1. The pattern of Forced Vital Capacity (FVC) and Forced Expiratory Volume in One Second (FEV1) for the selected subgroups seems to be gender dependant: in males, the highest values were seen in the Chinese, followed by the Malay, and then the Dayak; in females, the highest values were seen in the Chinese, followed by the Dayak, and then the Malay. 2. Smoking that did not produce respiratory symptom was not associated with a decline in lung function, in fact we noted higher values in smokers as compared to nonsmokers. 3. Prediction formulae (54 in total) are worked out for FVC & FEV1 for the respective gender and each of the selected subgroups.

PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

Science.gov (United States)

Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

2009-02-15

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

STOPGAP: a database for systematic target opportunity assessment by genetic association predictions.

Science.gov (United States)

Shen, Judong; Song, Kijoung; Slater, Andrew J; Ferrero, Enrico; Nelson, Matthew R

2017-09-01

We developed the STOPGAP (Systematic Target OPportunity assessment by Genetic Association Predictions) database, an extensive catalog of human genetic associations mapped to effector gene candidates. STOPGAP draws on a variety of publicly available GWAS associations, linkage disequilibrium (LD) measures, functional genomic and variant annotation sources. Algorithms were developed to merge the association data, partition associations into non-overlapping LD clusters, map variants to genes and produce a variant-to-gene score used to rank the relative confidence among potential effector genes. This database can be used for a multitude of investigations into the genes and genetic mechanisms underlying inter-individual variation in human traits, as well as supporting drug discovery applications. Shell, R, Perl and Python scripts and STOPGAP R data files (version 2.5.1 at publication) are available at https://github.com/StatGenPRD/STOPGAP . Some of the most useful STOPGAP fields can be queried through an R Shiny web application at http://stopgapwebapp.com . matthew.r.nelson@gsk.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation: The Maugeri Model.

Science.gov (United States)

Scrutinio, Domenico; Lanzillo, Bernardo; Guida, Pietro; Mastropasqua, Filippo; Monitillo, Vincenzo; Pusineri, Monica; Formica, Roberto; Russo, Giovanna; Guarnaschelli, Caterina; Ferretti, Chiara; Calabrese, Gianluigi

2017-12-01

Prediction of outcome after stroke rehabilitation may help clinicians in decision-making and planning rehabilitation care. We developed and validated a predictive tool to estimate the probability of achieving improvement in physical functioning (model 1) and a level of independence requiring no more than supervision (model 2) after stroke rehabilitation. The models were derived from 717 patients admitted for stroke rehabilitation. We used multivariable logistic regression analysis to build each model. Then, each model was prospectively validated in 875 patients. Model 1 included age, time from stroke occurrence to rehabilitation admission, admission motor and cognitive Functional Independence Measure scores, and neglect. Model 2 included age, male gender, time since stroke onset, and admission motor and cognitive Functional Independence Measure score. Both models demonstrated excellent discrimination. In the derivation cohort, the area under the curve was 0.883 (95% confidence intervals, 0.858-0.910) for model 1 and 0.913 (95% confidence intervals, 0.884-0.942) for model 2. The Hosmer-Lemeshow χ 2 was 4.12 ( P =0.249) and 1.20 ( P =0.754), respectively. In the validation cohort, the area under the curve was 0.866 (95% confidence intervals, 0.840-0.892) for model 1 and 0.850 (95% confidence intervals, 0.815-0.885) for model 2. The Hosmer-Lemeshow χ 2 was 8.86 ( P =0.115) and 34.50 ( P =0.001), respectively. Both improvement in physical functioning (hazard ratios, 0.43; 0.25-0.71; P =0.001) and a level of independence requiring no more than supervision (hazard ratios, 0.32; 0.14-0.68; P =0.004) were independently associated with improved 4-year survival. A calculator is freely available for download at https://goo.gl/fEAp81. This study provides researchers and clinicians with an easy-to-use, accurate, and validated predictive tool for potential application in rehabilitation research and stroke management. © 2017 American Heart Association, Inc.

Disciplinary style and child abuse potential: association with indicators of positive functioning in children with behavior problems.

Science.gov (United States)

Rodriguez, Christina M; Eden, Ann M

2008-06-01

Reduction of ineffective parenting is promoted in parent training components of mental health treatment for children with externalizing behavior disorders, but minimal research has considered whether disciplinary style and lower abuse risk could also be associated with positive functioning in such children. The present study examined whether lower dysfunctional disciplinary style and child abuse risk was associated with children's positive self-concept, adaptive attributional style, and hopefulness. Recruited from children undergoing treatment for disruptive behavior disorders, 69 mother-child dyads participated, with maternal caregivers reporting on their disciplinary style and abuse potential and children reporting independently on their positive functioning (adaptive attributional style, overall self-concept, and hopelessness). Findings supported the hypothesized association, with lower scores on mothers' dysfunctional discipline style and abuse potential significantly predicting children's reported positive functioning. Future research directions pertaining to more adaptive functioning in children with behavior problems are discussed.

Clinical and functional criteria for predicting asthma in infants

OpenAIRE

Yu. L. Mizemitskiy; V. A. Pavlenko; I. M. Melnikova

2015-01-01

Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability asses...

Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

Science.gov (United States)

Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

2017-10-01

Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Depression in Schizophrenia: Associations With Cognition, Functional Capacity, Everyday Functioning, and Self-Assessment.

Science.gov (United States)

Harvey, Philip D; Twamley, Elizabeth W; Pinkham, Amy E; Depp, Colin A; Patterson, Thomas L

2017-05-01

Depressed mood has a complex relationship with self-evaluation of personal competence in multiple populations. The absence of depression may be associated with overestimation of abilities, while mild depression seems to lead to accurate self-assessment. Significant depression may lead to underestimation of functioning. In this study, we expand on our previous work by directly comparing the association between different levels of depression, everyday functioning, cognitive and functional capacity performance, and self-assessment of everyday functioning in a large (n = 406) sample of outpatients with schizophrenia. Participants with very low self-reported depression overestimated their everyday functioning compared with informant reports. Higher levels of depression were associated with more accurate self-assessment, but no subgroup of patients underestimated their functioning. Depressive symptom severity was associated with poorer informant-rated social functioning, but there were no differences in vocational functioning, everyday activities, cognitive performance, and functional capacity associated with the severity of self-reported depression. There was minimal evidence of impact of depression on most aspects of everyday functioning and objective test performance and a substantial relationship between depression and accuracy of self-assessment. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Function and Phenotype prediction through Data and Knowledge Fusion

KAUST Repository

Vespoor, Karen

2016-01-01

I will introduce the use of text mining techniques to support analysis of biological data sets, and will specifically discuss applications in protein function and phenotype prediction, as well as analysis of genetic variants that are supported

Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

Science.gov (United States)

Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki

2017-01-01

The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.

Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.

Directory of Open Access Journals (Sweden)

Xin Wang

Full Text Available Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the 'search space' for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package

Executive functioning predicts reading, mathematics, and theory of mind during the elementary years.

Science.gov (United States)

Cantin, Rachelle H; Gnaedinger, Emily K; Gallaway, Kristin C; Hesson-McInnis, Matthew S; Hund, Alycia M

2016-06-01

The goal of this study was to specify how executive functioning components predict reading, mathematics, and theory of mind performance during the elementary years. A sample of 93 7- to 10-year-old children completed measures of working memory, inhibition, flexibility, reading, mathematics, and theory of mind. Path analysis revealed that all three executive functioning components (working memory, inhibition, and flexibility) mediated age differences in reading comprehension, whereas age predicted mathematics and theory of mind directly. In addition, reading mediated the influence of executive functioning components on mathematics and theory of mind, except that flexibility also predicted mathematics directly. These findings provide important details about the development of executive functioning, reading, mathematics, and theory of mind during the elementary years. Copyright © 2016 Elsevier Inc. All rights reserved.

Association with humans and seasonality interact to reverse predictions for animal space use.

Science.gov (United States)

Laver, Peter N; Alexander, Kathleen A

2018-01-01

Variation in animal space use reflects fitness trade-offs associated with ecological constraints. Associated theories such as the metabolic theory of ecology and the resource dispersion hypothesis generate predictions about what drives variation in animal space use. But, metabolic theory is usually tested in macro-ecological studies and is seldom invoked explicitly in within-species studies. Full evaluation of the resource dispersion hypothesis requires testing in more species. Neither have been evaluated in the context of anthropogenic landscape change. In this study, we used data for banded mongooses ( Mungos mungo ) in northeastern Botswana, along a gradient of association with humans, to test for effects of space use drivers predicted by these theories. We used Bayesian parameter estimation and inference from linear models to test for seasonal differences in space use metrics and to model seasonal effects of space use drivers. Results suggest that space use is strongly associated with variation in the level of overlap that mongoose groups have with humans. Seasonality influences this association, reversing seasonal space use predictions historically-accepted by ecologists. We found support for predictions of the metabolic theory when moderated by seasonality, by association with humans and by their interaction. Space use of mongooses living in association with humans was more concentrated in the dry season than the wet season, when historically-accepted ecological theory predicted more dispersed space use. Resource richness factors such as building density were associated with space use only during the dry season. We found negligible support for predictions of the resource dispersion hypothesis in general or for metabolic theory where seasonality and association with humans were not included. For mongooses living in association with humans, space use was not associated with patch dispersion or group size over both seasons. In our study, living in association

A new method for predicting functional recovery of stroke patients with hemiplegia: logarithmic modelling.

Science.gov (United States)

Koyama, Tetsuo; Matsumoto, Kenji; Okuno, Taiji; Domen, Kazuhisa

2005-10-01

To examine the validity and applicability of logarithmic modelling for predicting functional recovery of stroke patients with hemiplegia. Longitudinal postal survey. Stroke patients with hemiplegia staying in a long-term rehabilitation facility, who had been referred from acute medical service 30-60 days after onset. Functional Independence Measure (FIM) scores were periodically assessed during hospitalization. For each individual, a logarithmic formula that was scaled by an interval increase in FIM scores during the initial 2-6 weeks was used for predicting functional recovery. For the study, we recruited 18 patients who showed a wide variety of disability levels on admission (FIM scores 25-107). For each patient, the predicted FIM scores derived from the logarithmic formula matched the actual change in FIM scores. The changes predicted the recovery of motor rather than cognitive functions. Regression analysis showed a close fit between logarithmic modelling and actual FIM scores (across-subject R2 = 0.945). Provided with two initial time-point samplings, logarithmic modelling allows accurate prediction of functional recovery for individuals. Because the modelling is mathematically simple, it can be widely applied in daily clinical practice.

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

Science.gov (United States)

Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers.

Directory of Open Access Journals (Sweden)

Andrew T Kwon

2011-12-01

Full Text Available We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions.

Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

Science.gov (United States)

Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

2017-06-01

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

Spatially distributed flame transfer functions for predicting combustion dynamics in lean premixed gas turbine combustors

Energy Technology Data Exchange (ETDEWEB)

Kim, K.T.; Lee, J.G.; Quay, B.D.; Santavicca, D.A. [Center for Advanced Power Generation, Department of Mechanical and Nuclear Engineering, Pennsylvania State University, University Park, PA (United States)

2010-09-15

The present paper describes a methodology to improve the accuracy of prediction of the eigenfrequencies and growth rates of self-induced instabilities and demonstrates its application to a laboratory-scale, swirl-stabilized, lean-premixed, gas turbine combustor. The influence of the spatial heat release distribution is accounted for using local flame transfer function (FTF) measurements. The two-microphone technique and CH{sup *} chemiluminescence intensity measurements are used to determine the input (inlet velocity perturbation) and the output functions (heat release oscillation), respectively, for the local flame transfer functions. The experimentally determined local flame transfer functions are superposed using the flame transfer function superposition principle, and the result is incorporated into an analytic thermoacoustic model, in order to predict the linear stability characteristics of a given system. Results show that when the flame length is not acoustically compact the model prediction calculated using the local flame transfer functions is better than the prediction made using the global flame transfer function. In the case of a flame in the compact flame regime, accurate predictions of eigenfrequencies and growth rates can be obtained using the global flame transfer function. It was also found that the general response characteristics of the local FTF (gain and phase) are qualitatively the same as those of the global FTF. (author)

Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth

2014-01-01

This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... These properties facilitate the design of speed controllers by placement of the closed-loop poles (when constraints are not active) and systematic adaptation towards changes in the operating point. Vibration control of undamped modes is achieved by imposing a certain degree of stability to the closed-loop system....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....

Homology modeling and in silico prediction of Ulcerative colitis associated polymorphisms of NOD1.

Science.gov (United States)

Majumdar, Ishani; Nagpal, Isha; Paul, Jaishree

2017-10-01

Cytosolic pattern recognition receptors play key roles in innate immune response. Nucleotide binding and oligomerisation domain containing protein 1 (NOD1) belonging to the Nod-like receptor C (NLRC) sub-family of Nod-like receptors (NLRs) is important for detection and clearance of intra-cellular Gram negative bacteria. NOD1 is involved in activation of pro-inflammatory pathways. Limited structural data is available for NOD1. Using different templates for each domain of NOD1, we determined the full-length homology model of NOD1. ADP binding amino acids within the nucleotide binding domain (NBD) of NOD1 were also predicted. Key residues in inter-domain interaction were identified by sequence comparison with Oryctolagus cuniculus NOD2, a related protein. Interactions between NBD and winged helix domain (WHD) were found to be conserved in NOD1. Functional and structural effect of single nucleotide polymorphisms within the NOD1 NBD domain associated with susceptibility risk to Ulcerative colitis (UC), an inflammatory disorder of the colon was evaluated by in silico studies. Mutations W219R and L349P were predicted to be damaging and disease associated by prediction programs SIFT, PolyPhen2, PANTHER, SNP&GO, PhD SNP and SNAP2. We further validated the effect of W219R and L349P mutation on NOD1 function in vitro. Elevated mRNA expression of pro-inflammatory cytokines IL8 and IL-1β was seen as compared to the wild type NOD1 in intestinal epithelial cell line HT29 when stimulated with NOD1 ligand. Thus, these mutations may indeed have a bearing on pathogenesis of inflammation during UC. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Functional Dysphagia Scale Is a Useful Tool for Predicting Aspiration Pneumonia in Patients With Parkinson Disease.

Science.gov (United States)

Lee, Jong Hwa; Lee, Kyeong Woo; Kim, Sang Beom; Lee, Sook Joung; Chun, Sang Myung; Jung, Sung Moon

2016-06-01

To describe the correlation between the functional dysphagia scale and aspiration pneumonia and which characteristics influence the occurrence of aspiration pneumonia in patients with idiopathic Parkinson disease. Fifty-three patients with idiopathic Parkinson disease were prospectively evaluated in this study. Disease severity and functional status were measured by modified Hoehn and Yahr (H&Y) staging, Schwab and England activities of daily living (S-E ADL) scale and Korean version of Mini-Mental State Examination (K-MMSE). Swallowing function was evaluated by the functional dysphagia scale (FDS) and the penetration-aspiration scale (PAS) based on a videofluoroscopic swallowing study. The patients were followed up for 3 months and divided into two groups according to the occurrence of aspiration pneumonia. The correlation between the variables and aspiration pneumonia was analyzed. Eight patients of the 53 patients were allocated to the aspiration pneumonia group and 45 patients to the non-aspiration pneumonia group. The patients in the aspiration pneumonia group had significantly higher H&Y staging, and scored lower on S-E ADL scale and K-MMSE. The patients in the aspiration pneumonia group had significantly higher scores on FDS and PAS. A multiple logistic regression analysis showed that the S-E ADL scale and the FDS were associated with the occurrence of aspiration pneumonia in the patients with Parkinson disease. Given that the FDS can quantitatively assess the functional problems associated with dysphagia, it can be clinically effective in predicting the occurrence of aspiration pneumonia, and the FDS and the S-E ADL scale could be predictive variables for aspiration pneumonia in patients with Parkinson disease.

Obesity-associated biomarkers and executive function in children.

Science.gov (United States)

Miller, Alison L; Lee, Hannah J; Lumeng, Julie C

2015-01-01

There is a growing focus on links between obesity and cognitive decline in adulthood, including Alzheimer's disease. It is also increasingly recognized that obesity in youth is associated with poorer cognitive function, specifically executive functioning skills such as inhibitory control and working memory, which are critical for academic achievement. Emerging literature provides evidence for possible biological mechanisms driven by obesity; obesity-associated biomarkers such as adipokines, obesity-associated inflammatory cytokines, and obesity-associated gut hormones have been associated with learning, memory, and general cognitive function. To date, examination of obesity-associated biology with brain function has primarily occurred in animal models. The few studies examining such biologically mediated pathways in adult humans have corroborated the animal data, but this body of work has gone relatively unrecognized by the pediatric literature. Despite the fact that differences in these biomarkers have been found in association with obesity in children, the possibility that obesity-related biology could affect brain development in children has not been actively considered. We review obesity-associated biomarkers that have shown associations with neurocognitive skills, specifically executive functioning skills, which have far-reaching implications for child development. Understanding such gut-brain associations early in the lifespan may yield unique intervention implications.

Evidence for a Functional Hierarchy of Association Networks.

Science.gov (United States)

Choi, Eun Young; Drayna, Garrett K; Badre, David

2018-05-01

Patient lesion and neuroimaging studies have identified a rostral-to-caudal functional gradient in the lateral frontal cortex (LFC) corresponding to higher-order (complex or abstract) to lower-order (simple or concrete) cognitive control. At the same time, monkey anatomical and human functional connectivity studies show that frontal regions are reciprocally connected with parietal and temporal regions, forming parallel and distributed association networks. Here, we investigated the link between the functional gradient of LFC regions observed during control tasks and the parallel, distributed organization of association networks. Whole-brain fMRI task activity corresponding to four orders of hierarchical control [Badre, D., & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19, 2082-2099, 2007] was compared with a resting-state functional connectivity MRI estimate of cortical networks [Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125-1165, 2011]. Critically, at each order of control, activity in the LFC and parietal cortex overlapped onto a common association network that differed between orders. These results are consistent with a functional organization based on separable association networks that are recruited during hierarchical control. Furthermore, corticostriatal functional connectivity MRI showed that, consistent with their participation in functional networks, rostral-to-caudal LFC and caudal-to-rostral parietal regions had similar, order-specific corticostriatal connectivity that agreed with a striatal gating model of hierarchical rule use. Our results indicate that hierarchical cognitive control is subserved by parallel and distributed association networks, together forming

Gene-specific function prediction for non-synonymous mutations in monogenic diabetes genes.

Directory of Open Access Journals (Sweden)

Quan Li

Full Text Available The rapid progress of genomic technologies has been providing new opportunities to address the need of maturity-onset diabetes of the young (MODY molecular diagnosis. However, whether a new mutation causes MODY can be questionable. A number of in silico methods have been developed to predict functional effects of rare human mutations. The purpose of this study is to compare the performance of different bioinformatics methods in the functional prediction of nonsynonymous mutations in each MODY gene, and provides reference matrices to assist the molecular diagnosis of MODY. Our study showed that the prediction scores by different methods of the diabetes mutations were highly correlated, but were more complimentary than replacement to each other. The available in silico methods for the prediction of diabetes mutations had varied performances across different genes. Applying gene-specific thresholds defined by this study may be able to increase the performance of in silico prediction of disease-causing mutations.

Resting right ventricular function is associated with exercise performance in PAH, but not in CTEPH.

Science.gov (United States)

Rehman, Michaela Beatrice; Howard, Luke S; Christiaens, Luc P; Gill, Dipender; Gibbs, J Simon R; Nihoyannopoulos, Petros

2018-02-01

To assess whether resting right ventricular (RV) function assessed by Global RV longitudinal strain (RVLS) and RV fractional area change (FAC) is associated with exercise performance in pulmonary arterial hypertension (PAH) and in chronic thromboembolic pulmonary hypertension (CTEPH). We prospectively recruited 46 consecutive patients with PAH and 42 patients with CTEPH who were referred for cardio-pulmonary exercise testing (CPET) and transthoracic echocardiography. Resting RV systolic function was assessed with RVLS and FAC. CPET parameters analyzed were percentage of predicted maximal oxygen consumption (VO2max) and the slope of ventilation against carbon dioxide production (VE/VCO2). Spearman correlation was performed between echocardiographic measurements and CPET measurements. In PAH, spearman correlation found an association between RVLS and VE/VCO2 (coefficient = 0.556, P PAH, resting RV function as assessed by FAC or RVLS is associated with exercise performance and could therefore make a significant contribution to non-invasive assessment in PAH patients. This association is not found in CTEPH, suggesting a disconnection between resting RV function and exercise performance, with implications for the use of exercise measurements as a prognostic marker and clinical/research endpoint in CTEPH. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

Application of Functional Link Artificial Neural Network for Prediction of Machinery Noise in Opencast Mines

Directory of Open Access Journals (Sweden)

Santosh Kumar Nanda

2011-01-01

Full Text Available Functional link-based neural network models were applied to predict opencast mining machineries noise. The paper analyzes the prediction capabilities of functional link neural network based noise prediction models vis-à-vis existing statistical models. In order to find the actual noise status in opencast mines, some of the popular noise prediction models, for example, ISO-9613-2, CONCAWE, VDI, and ENM, have been applied in mining and allied industries to predict the machineries noise by considering various attenuation factors. Functional link artificial neural network (FLANN, polynomial perceptron network (PPN, and Legendre neural network (LeNN were used to predict the machinery noise in opencast mines. The case study is based on data collected from an opencast coal mine of Orissa, India. From the present investigations, it could be concluded that the FLANN model give better noise prediction than the PPN and LeNN model.

Dynamic range of frontoparietal functional modulation is associated with working memory capacity limitations in older adults.

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Hakun, Jonathan G; Johnson, Nathan F

2017-11-01

Older adults tend to over-activate regions throughout frontoparietal cortices and exhibit a reduced range of functional modulation during WM task performance compared to younger adults. While recent evidence suggests that reduced functional modulation is associated with poorer task performance, it remains unclear whether reduced range of modulation is indicative of general WM capacity-limitations. In the current study, we examined whether the range of functional modulation observed over multiple levels of WM task difficulty (N-Back) predicts in-scanner task performance and out-of-scanner psychometric estimates of WM capacity. Within our sample (60-77years of age), age was negatively associated with frontoparietal modulation range. Individuals with greater modulation range exhibited more accurate N-Back performance. In addition, despite a lack of significant relationships between N-Back and complex span task performance, range of frontoparietal modulation during the N-Back significantly predicted domain-general estimates of WM capacity. Consistent with previous cross-sectional findings, older individuals with less modulation range exhibited greater activation at the lowest level of task difficulty but less activation at the highest levels of task difficulty. Our results are largely consistent with existing theories of neurocognitive aging (e.g. CRUNCH) but focus attention on dynamic range of functional modulation asa novel marker of WM capacity-limitations in older adults. Copyright © 2017 Elsevier Inc. All rights reserved.

New-onset diabetes mellitus after living-donor liver transplantation: association with graft synthetic function.

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Yagi, Shintaro; Kaido, Toshimi; Iida, Taku; Yoshizawa, Atsushi; Okajima, Hideaki; Uemoto, Shinji

2017-06-01

It is now known that post-transplant graft function after deceased-donor liver transplantation and living-donor liver transplantation (LDLT) differ; however, there is no report assessing the relationship between graft function and the development of new-onset diabetes mellitus after transplantation (NODAT). We conducted this study to identify the predictive risk factors for NODAT, including graft function after LDLT. The subjects of this study were 175 adult recipients who underwent LDLT at Kyoto University Hospital between 2006 and 2010, and survived for more than 3 months (median observation period, 1046 days). The 1-, 2-, and 3-year incidences of NODAT after LDLT were 26.1, 32.0, and 33.4%, respectively. Pre-transplant diabetes was associated with poor survival (p = 0.0048), whereas NODAT was not associated with patient survival. In the multivariate analysis, recipient age ≥40, a tacrolimus trough level ≥8 ng/mL 3 months after LDLT, and cholinesterase (ChE) <185 IU/L 3 months after LDLT were the independent risk factors for NODAT. Poor graft synthetic function 3 months after LDLT as well as older age of the recipient and a higher tacrolimus concentration were strongly associated with NODAT development after LDLT.

Obsessive compulsive symptoms are associated with better functioning independently of cognition in schizophrenia.

Science.gov (United States)

Kontis, Dimitrios; Theochari, Eirini; Nikolakopoulou, Mary; Andreopoulou, Angeliki; Vassos, Dimitrios; Grigoriou, Vasileios; Vassilouli, Spyridoula; Giannakopoulou, Dimitra; Kouloumbi, Maria; Tsaltas, Eleftheria

2016-10-01

Although the relationship of obsessive-compulsive symptoms (OCSs) with both cognition and social functioning (SF) has already been the focus of research in schizophrenia, the moderation of the relationship of OCSs with SF by cognition has not been explored to date. We investigated the association of OCSs with SF and its interaction with cognition in schizophrenia. We recruited 110 schizophrenia patients and assessed OCSs (Yale-Brown Scale), schizophrenia symptoms (Positive and Negative Syndrome Scale), SF (Strauss-Carpenter Scale) and cognition. 51 patients had one obsessive-compulsive symptom or more, whereas 59 patients had no obsessive compulsive-symptom, according to the Yale-Brown Scale. We mainly investigated: a) the predictive effect of OCSs on SF, controlling for cognition, illness duration and symptoms' severity and b) the moderating effect of cognition on the OCSs-SF relationship. The mean score of OCSs for patients having at least one symptom was 13.43 (SD=8.32). Higher OCSs predicted increased SF (B=0.98, t=2.41, df=88, p=0.018). This relationship was driven by the association of compulsions with job functioning (B=0.074, t=2.029, df=88, p=0.046). Patients without OCSs demonstrated worse functioning compared with those having at least one obsessive-compulsive symptom (mean difference=2.496, t=3.732, df=88, p<0.001). We failed to find evidence that cognition moderates the effect of OCSs on SF. There may be a beneficial effect of OCSs on SF in patients with schizophrenia which is independent of their cognitive performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Iowa Gambling Task Performance and Executive Function Predict Low-income Urban Preadolescents’ Risky Behaviors

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Ursache, Alexandra; Raver, C. Cybele

2015-01-01

This study examines preadolescents’ reports of risk-taking as predicted by two different, but related inhibitory control systems involving sensitivity to reward and loss on the one hand, and higher order processing in the context of cognitive conflict, known as executive functioning (EF), on the other. Importantly, this study examines these processes with a sample of inner-city, low-income preadolescents and as such examines the ways in which these processes may be related to risky behaviors as a function of children's levels of both concurrent and chronic exposure to household poverty. As part of a larger longitudinal study, 382 children (ages 9 -11) provided a self-report of risky behaviors and participated in the Iowa Gambling task, assessing bias for infrequent loss (preference for infrequent, high magnitude versus frequent, low magnitude loss) and the Hearts and Flowers task assessing executive functioning. Results demonstrated that a higher bias for infrequent loss was associated with higher risky behaviors for children who demonstrated lower EF. Furthermore, bias for infrequent loss was most strongly associated with higher risk-taking for children facing highest levels of poverty. Implications for early identification and prevention of risk-taking in inner-city preadolescents are discussed. PMID:26412918

Socioeconomic Status, Subjective Social Status, and Perceived Stress: Associations with Stress Physiology and Executive Functioning.

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Ursache, Alexandra; Noble, Kimberly G; Blair, Clancy

2015-01-01

Several studies have investigated associations between socioeconomic status (SES) and indicators of children's physiological and cognitive self-regulation. Although objective measures of family SES may be good proxies for families' experiences of disadvantage, less is known about subjective aspects of families' experiences. We hypothesize that subjective social status (SSS) and perceived stress may be important independent predictors of children's stress physiology and executive functioning (EF). Eighty-two children from diverse SES backgrounds were administered EF measures and provided saliva samples for cortisol assay. Caregivers reported on objective SES, SSS, and perceived stress. Results suggest that SES and SSS are both independently and positively related to EF. In models predicting stress physiology, higher perceived stress was associated with lower baseline cortisol. Moreover, SES and age interacted to predict cortisol levels such that among younger children, lower SES was associated with higher cortisol, whereas among older children, lower SES was associated with lower cortisol. Results highlight the importance of considering both objective and subjective indicators of families' SES and stressful experiences in relation to multiple aspects of children's self-regulation.

Bedside Ultrasound of Quadriceps to Predict Rehospitalization and Functional Decline in Hospitalized Elders

Directory of Open Access Journals (Sweden)

Ana Clara Guerreiro

2017-07-01

Full Text Available ObjectiveTo evaluate the capacity of total anterior thigh thickness, quadriceps muscle thickness, and quadriceps contractile index, all measured by bedside ultrasound, to predict rehospitalization, functional decline, and death in elderly patients 3 months after hospital discharge. To evaluate intra and interobserver reproducibility of the dominant thigh evaluation method by point of care ultrasound.MethodsCohort study of patients aged 65 years or more admitted to a medium complexity unit in a teaching hospital in southern Brazil. Comprehensive geriatric assessment and ultrasound evaluation of the dominant thigh of each participant were performed. After 3 months of hospital discharge, telephone contact was made to evaluate the outcomes of rehospitalization or death and functional decline—assessed by the 100 points Barthel scale and defined as a decrease of five or more points.Results100 participants were included. There was no statistically significant difference between intraobserver measurements in the GEE method analysis (p > 0.05, and the mean bias obtained in Bland–Altman plots was close to zero in all four analyses performed, suggesting good intra and interobserver agreement. There was a significant correlation between the echographic measurements (quadriceps thickness and contractile index and gait speed, timed up and go, and handgrip tests. There was a significant association between contractile index (quadriceps thickness over total anterior thigh thickness multiplied by 100 lower than 60% and functional decline (relative risk 1.35; CI 95% 1.10–1.65; p = 0.003 as well as between the thickness of the quadriceps and rehospitalization or death, in both individuals with preserved walking capacity and in bedridden elders (relative risk 1.34; CI 95% 1.02–1.75; p = 0.04.ConclusionThe ultrasonographic method to evaluate thigh thickness was easily applicable and reproducible. The thickness of the quadriceps could

Computation of piecewise affine terminal cost functions for model predictive control

NARCIS (Netherlands)

Brunner, F.D.; Lazar, M.; Allgöwer, F.; Fränzle, Martin; Lygeros, John

2014-01-01

This paper proposes a method for the construction of piecewise affine terminal cost functions for model predictive control (MPC). The terminal cost function is constructed on a predefined partition by solving a linear program for a given piecewise affine system, a stabilizing piecewise affine

Prediction of renal functional recovery after relief of upper urinary tract obstruction

International Nuclear Information System (INIS)

Kalika, V.; Bard, R.H.; Iloreta, A.; Freeman, L.M.; Heller, S.; Blaufox, M.D.

1981-01-01

Renal cortical regions of interest were used prospectively to predict recoverability of renal function in 27 patients with unilateral or bilateral urinary tract obstruction. In these 27 patients 36 kidneys with short-term or long-term obstruction were studied. The 131iodine radiohippuran renogram curves were generated from areas of interest from the renal cortex and from the whole kidney. Curves generated during obstruction were evaluated qualitatively to determine if regional cortical renograms exhibited a more normal appearance than total kidney curves. After relief of obstruction renograms generated from the whole kidney were evaluated for evidence of renal functional recovery. Cortical curves obtained before relief obstruction were judged normal, with an abnormal whole kidney renogram in 20 of 36 kidneys. The whole kidney renogram improved after relief of obstruction in all 20 cases. Cortical curves for the remaining 16 kidneys before relief of obstruction had the same abnormal appearance as the whole kidney renogram. After relief of obstruction no evidence of kidney function improvement as measured by the renogram was evident in 14 kidneys. The over-all accuracy of this test of renal functional recoverability was 94 per cent. These data support the hypothesis that when cortical curves appear more normal than total kidney curves there is a strong likelihood of postoperative improvement in renal function when the obstruction is relieved. Abnormal cortical curves are associated with a poor prognosis for renal functional improvement

Converging evidence for the association of functional genetic variation in the serotonin receptor 2a gene with prefrontal function and olanzapine treatment.

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Blasi, Giuseppe; De Virgilio, Caterina; Papazacharias, Apostolos; Taurisano, Paolo; Gelao, Barbara; Fazio, Leonardo; Ursini, Gianluca; Sinibaldi, Lorenzo; Andriola, Ileana; Masellis, Rita; Romano, Raffaella; Rampino, Antonio; Di Giorgio, Annabella; Lo Bianco, Luciana; Caforio, Grazia; Piva, Francesco; Popolizio, Teresa; Bellantuono, Cesario; Todarello, Orlando; Kleinman, Joel E; Gadaleta, Gemma; Weinberger, Daniel R; Bertolino, Alessandro

2013-09-01

Serotonin (5-hydroxytryptamine) receptor 2a (5-HT2AR) signaling is important for modulation of corticostriatal pathways and prefrontal activity during cognition. Furthermore, newer antipsychotic drugs target 5-HT2AR. A single-nucleotide polymorphism in the 5-HT2AR gene (HTR2A rs6314, C>T; OMIM 182135) has been weakly associated with differential 5-HT2AR signaling and with physiologic as well as behavioral effects. To use a hierarchical approach to determine the functional effects of this single-nucleotide polymorphism on 5-HT2AR messenger RNA and protein expression, on prefrontal phenotypes linked with genetic risk for schizophrenia, and on treatment with olanzapine. In silico predictions, in vitro, and case-control investigations. Academic and clinical facilities. The postmortem study included 112 brains from healthy individuals; the in vivo investigation included a total sample of 371 healthy individuals and patients with schizophrenia. EXPOSURES Patients received olanzapine monotherapy for 8 weeks. In silico predictions, messenger RNA, and protein expression in postmortem human prefrontal cortex and HeLa cells, functional magnetic resonance imaging prefrontal activity and behavior during working memory and attention in healthy individuals, and response to an 8-week trial of olanzapine treatment in patients with schizophrenia. Bioinformatic analysis predicted that rs6314 alters patterns of splicing, with possible effects on HTR2A expression. Moreover, the T allele was associated with reduced prefrontal messenger RNA expression in postmortem prefrontal cortex, with reduced protein expression in vitro, inefficient prefrontal blood oxygen level-dependent functional magnetic resonance imaging response during working memory and attentional control processing, and impaired working memory and attention behavior, as well as with attenuated improvement in negative symptoms after olanzapine treatment. Our results suggest that HTR2A rs6314 affects 5-HT2AR expression and

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

Development of associations and kinetic models for microbiological data to be used in comprehensive food safety prediction software.

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Halder, Amit; Black, D Glenn; Davidson, P Michael; Datta, Ashim

2010-08-01

The objective of this study was to use an existing database of food products and their associated processes, link it with a list of the foodborne pathogenic microorganisms associated with those products and finally identify growth and inactivation kinetic parameters associated with those pathogens. The database was to be used as a part of the development of comprehensive software which could predict food safety and quality for any food product. The main issues in building such a predictive system included selection of predictive models, associations of different food types with pathogens (as determined from outbreak histories), and variability in data from different experiments. More than 1000 data sets from published literature were analyzed and grouped according to microorganisms and food types. Final grouping of data consisted of the 8 most prevalent pathogens for 14 different food groups, covering all of the foods (>7000) listed in the USDA Natl. Nutrient Database. Data for each group were analyzed in terms of 1st-order inactivation, 1st-order growth, and sigmoidal growth models, and their kinetic response for growth and inactivation as a function of temperature were reported. Means and 95% confidence intervals were calculated for prediction equations. The primary advantage in obtaining group-specific kinetic data is the ability to extend microbiological growth and death simulation to a large array of product and process possibilities, while still being reasonably accurate. Such simulation capability could provide vital ''what if'' scenarios for industry, Extension, and academia in food safety.

A large-scale evaluation of computational protein function prediction

NARCIS (Netherlands)

Radivojac, P.; Clark, W.T.; Oron, T.R.; Schnoes, A.M.; Wittkop, T.; Kourmpetis, Y.A.I.; Dijk, van A.D.J.; Friedberg, I.

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be

Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

Science.gov (United States)

Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

2017-09-01

This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

A comprehensive evaluation of potential lung function associated genes in the SpiroMeta general population sample.

Directory of Open Access Journals (Sweden)

Ma'en Obeidat

Full Text Available Lung function measures are heritable traits that predict population morbidity and mortality and are essential for the diagnosis of chronic obstructive pulmonary disease (COPD. Variations in many genes have been reported to affect these traits, but attempts at replication have provided conflicting results. Recently, we undertook a meta-analysis of Genome Wide Association Study (GWAS results for lung function measures in 20,288 individuals from the general population (the SpiroMeta consortium.To comprehensively analyse previously reported genetic associations with lung function measures, and to investigate whether single nucleotide polymorphisms (SNPs in these genomic regions are associated with lung function in a large population sample.We analysed association for SNPs tagging 130 genes and 48 intergenic regions (+/-10 kb, after conducting a systematic review of the literature in the PubMed database for genetic association studies reporting lung function associations.The analysis included 16,936 genotyped and imputed SNPs. No loci showed overall significant association for FEV(1 or FEV(1/FVC traits using a carefully defined significance threshold of 1.3×10(-5. The most significant loci associated with FEV(1 include SNPs tagging MACROD2 (P = 6.81×10(-5, CNTN5 (P = 4.37×10(-4, and TRPV4 (P = 1.58×10(-3. Among ever-smokers, SERPINA1 showed the most significant association with FEV(1 (P = 8.41×10(-5, followed by PDE4D (P = 1.22×10(-4. The strongest association with FEV(1/FVC ratio was observed with ABCC1 (P = 4.38×10(-4, and ESR1 (P = 5.42×10(-4 among ever-smokers.Polymorphisms spanning previously associated lung function genes did not show strong evidence for association with lung function measures in the SpiroMeta consortium population. Common SERPINA1 polymorphisms may affect FEV(1 among smokers in the general population.

Self-reported Physical Activity Predicts Pain Inhibitory and Facilitatory Function

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Naugle, Kelly M.; Riley, Joseph L.

2013-01-01

Considerable evidence suggests regular physical activity can reduce chronic pain symptoms. Dysfunction of endogenous facilitatory and inhibitory systems has been implicated in multiple chronic pain conditions. However, few studies have investigated the relationship between levels of physical activity and descending pain modulatory function. Purpose This study’s purpose was to determine whether self-reported levels of physical activity in healthy adults predicted 1) pain sensitivity to heat and cold stimuli, 2) pain facilitatory function as tested by temporal summation of pain (TS), and 3) pain inhibitory function as tested by conditioned pain modulation (CPM) and offset analgesia. Methods Forty-eight healthy adults (age range 18–76) completed the International Physical Activity Questionnaire (IPAQ) and the following pain tests: heat pain thresholds (HPT), heat pain suprathresholds, cold pressor pain (CPP), temporal summation of heat pain, conditioned pain modulation, and offset analgesia. The IPAQ measured levels of walking, moderate, vigorous and total physical activity over the past seven days. Hierarchical linear regressions were conducted to determine the relationship between each pain test and self-reported levels of physical activity, while controlling for age, sex and psychological variables. Results Self-reported total and vigorous physical activity predicted TS and CPM (p’s pain and greater CPM. The IPAQ measures did not predict any of the other pain measures. Conclusion Thus, these results suggest that healthy older and younger adults who self-report greater levels of vigorous and total physical activity exhibit enhanced descending pain modulatory function. Improved descending pain modulation may be a mechanism through which exercise reduces or prevents chronic pain symptoms. PMID:23899890

FDG-PET/CT in the prediction of pulmonary function improvement in nonspecific interstitial pneumonia. A Pilot Study

Energy Technology Data Exchange (ETDEWEB)

Jacquelin, V. [AP-HP, Hosp. Avicenne, Department of Nuclear Medicine, Bobigny (France); Mekinian, A. [AP-HP, Hosp. Saint-Antoine, Department of Internal Medicine and Inflammation-Immunopathology-Biotherapy Department (DHU i2B), Paris (France); Brillet, P.Y. [AP-HP, Hosp. Avicenne, Department of Radiology, Bobigny (France); Univ. Paris 13, Sorbonne Paris Cité, Bobigny (France); Nunes, H. [AP-HP, Hosp. Avicenne, Department of Pneumology, Bobigny (France); Univ. Paris 13, Sorbonne Paris Cité, Bobigny (France); Fain, O. [AP-HP, Hosp. Saint-Antoine, Department of Internal Medicine and Inflammation-Immunopathology-Biotherapy Department (DHU i2B), Paris (France); Valeyre, D. [AP-HP, Hosp. Avicenne, Department of Pneumology, Bobigny (France); Univ. Paris 13, Sorbonne Paris Cité, Bobigny (France); Soussan, M., E-mail: michael.soussan@aphp.fr [AP-HP, Hosp. Avicenne, Department of Nuclear Medicine, Bobigny (France); Univ. Paris 13, Sorbonne Paris Cité, Bobigny (France)

2016-12-15

Purpose: Our study aimed to analyse the characteristics of nonspecific interstitial pneumonia (NSIP) using FDG-PET/CT (PET) and to evaluate its ability to predict the therapeutic response. Procedures: Eighteen NSIP patients were included. Maximum standardized uptake value (SUV{sub max}), FDG uptake extent (in percentage of lung volume), high resolution CT scan (HRCT) elementary lesions, and HRCT fibrosis score were recorded. The predictive value of the parameters for lung function improvement was evaluated using logistic regression and Receiver Operating Characteristic (ROC) curve analysis (n = 13/18). Results: All patients had an increased pulmonary FDG uptake (median SUV{sub max} = 3.1 [2–7.6]), with a median extent of 19% [6–67]. Consolidations, ground-glass opacities, honeycombing and reticulations showed uptake in 90%, 89%, 85% and 76%, respectively. FDG uptake extent was associated with improvement of pulmonary function under treatment (increase in forced vital capacity > 10%, p = 0.03), whereas SUV{sub max} and HRCT fibrosis score were not (p > 0.5). For FDG uptake extent, ROC analysis showed an area under the curve at 0.85 ± 0.11 and sensitivity/specificity was 88%/80% for a threshold fixed at 21%. Conclusions: Increased FDG uptake was observed in all NSIP patients, both in inflammatory and fibrotic HRCT lesions. The quantification of FDG uptake extent might be useful to predict functional improvement under treatment.

FDG-PET/CT in the prediction of pulmonary function improvement in nonspecific interstitial pneumonia. A Pilot Study

International Nuclear Information System (INIS)

Jacquelin, V.; Mekinian, A.; Brillet, P.Y.; Nunes, H.; Fain, O.; Valeyre, D.; Soussan, M.

2016-01-01

Purpose: Our study aimed to analyse the characteristics of nonspecific interstitial pneumonia (NSIP) using FDG-PET/CT (PET) and to evaluate its ability to predict the therapeutic response. Procedures: Eighteen NSIP patients were included. Maximum standardized uptake value (SUV max ), FDG uptake extent (in percentage of lung volume), high resolution CT scan (HRCT) elementary lesions, and HRCT fibrosis score were recorded. The predictive value of the parameters for lung function improvement was evaluated using logistic regression and Receiver Operating Characteristic (ROC) curve analysis (n = 13/18). Results: All patients had an increased pulmonary FDG uptake (median SUV max = 3.1 [2–7.6]), with a median extent of 19% [6–67]. Consolidations, ground-glass opacities, honeycombing and reticulations showed uptake in 90%, 89%, 85% and 76%, respectively. FDG uptake extent was associated with improvement of pulmonary function under treatment (increase in forced vital capacity > 10%, p = 0.03), whereas SUV max and HRCT fibrosis score were not (p > 0.5). For FDG uptake extent, ROC analysis showed an area under the curve at 0.85 ± 0.11 and sensitivity/specificity was 88%/80% for a threshold fixed at 21%. Conclusions: Increased FDG uptake was observed in all NSIP patients, both in inflammatory and fibrotic HRCT lesions. The quantification of FDG uptake extent might be useful to predict functional improvement under treatment.

Uncertainties associated with lacking data for predictions of solid-solution partitioning of metals in soil

International Nuclear Information System (INIS)

Le, T.T. Yen; Hendriks, A. Jan

2014-01-01

Soil properties, i.e., pH and contents of soil organic matter (SOM), dissolved organic carbon (DOC), clay, oxides, and reactive metals, are required inputs to both mechanistic and empirical modeling in assessing metal solid-solution partitioning. Several of these properties are rarely measured in site-specific risk assessment. We compared the uncertainties induced by lacking data on these soil properties in estimating metal soil solution concentrations. The predictions by the Orchestra framework were more sensitive to lacking soil property data than the predictions by the transfer functions. The deviations between soil solution concentrations of Cd, Ni, Zn, Ba, and Co estimated with measured SOM and those estimated with generic SOM by the Orchestra framework were about 10 times larger than the deviations in the predictions by the transfer functions. High uncertainties were induced by lacking data in assessing solid-solution partitioning of oxy-anions like As, Mo, Sb, Se, and V. Deviations associated with lacking data in predicting soil solution concentrations of these metals by the Orchestra framework reached three-to-six orders of magnitude. The solid-solution partitioning of metal cations was strongly influenced by pH and contents of organic matter, oxides, and reactive metals. Deviations of more than two orders of magnitude were frequently observed between the estimates of soil solution concentrations with the generic values of these properties and the estimates based on the measured data. Reliable information on these properties is preferred to be included in the assessment by either the Orchestra framework or transfer functions. - Highlights: • Estimates of metal solid-solution partitioning sensitive to soil property data. • Uncertainty mainly due to lacking reactive metal contents, pH, and organic matter. • Soil solution concentrations of oxy-anions highly influenced by oxide contents. • Clay contents had least effects on solid-solution partitioning

Uncertainties associated with lacking data for predictions of solid-solution partitioning of metals in soil

Energy Technology Data Exchange (ETDEWEB)

Le, T.T. Yen, E-mail: YenLe@science.ru.nl; Hendriks, A. Jan

2014-08-15

Soil properties, i.e., pH and contents of soil organic matter (SOM), dissolved organic carbon (DOC), clay, oxides, and reactive metals, are required inputs to both mechanistic and empirical modeling in assessing metal solid-solution partitioning. Several of these properties are rarely measured in site-specific risk assessment. We compared the uncertainties induced by lacking data on these soil properties in estimating metal soil solution concentrations. The predictions by the Orchestra framework were more sensitive to lacking soil property data than the predictions by the transfer functions. The deviations between soil solution concentrations of Cd, Ni, Zn, Ba, and Co estimated with measured SOM and those estimated with generic SOM by the Orchestra framework were about 10 times larger than the deviations in the predictions by the transfer functions. High uncertainties were induced by lacking data in assessing solid-solution partitioning of oxy-anions like As, Mo, Sb, Se, and V. Deviations associated with lacking data in predicting soil solution concentrations of these metals by the Orchestra framework reached three-to-six orders of magnitude. The solid-solution partitioning of metal cations was strongly influenced by pH and contents of organic matter, oxides, and reactive metals. Deviations of more than two orders of magnitude were frequently observed between the estimates of soil solution concentrations with the generic values of these properties and the estimates based on the measured data. Reliable information on these properties is preferred to be included in the assessment by either the Orchestra framework or transfer functions. - Highlights: • Estimates of metal solid-solution partitioning sensitive to soil property data. • Uncertainty mainly due to lacking reactive metal contents, pH, and organic matter. • Soil solution concentrations of oxy-anions highly influenced by oxide contents. • Clay contents had least effects on solid-solution partitioning

Functional imaging of implicit marijuana associations during performance on an Implicit Association Test (IAT)

NARCIS (Netherlands)

Ames, S.L.; Grenard, J.L.; Stacy, A.W.; Xiao, L.; He, Q.; Wong, S.W; Xue, G.; Wiers, R.W.; Bechara, A.

2013-01-01

This research evaluated the neural correlates of implicit associative memory processes (habit-based processes) through the imaging (fMRI) of a marijuana Implicit Association Test. Drug-related associative memory effects have been shown to consistently predict level of drug use. To observe

Parent emotional expressiveness and children's self-regulation: Associations with abused children's school functioning

Science.gov (United States)

Haskett, Mary E.; Stelter, Rebecca; Proffit, Katie; Nice, Rachel

2012-01-01

Objective Identifying factors associated with school functioning of abused children is important in prevention of long-term negative outcomes associated with school failure. The purpose of this study was to examine the degree to which parent emotional expressiveness and children's self-regulation predicted early school behavior of abused children. Methods The sample included 92 physically abused children ages 4-7 and one of their parents (95.7% mothers). Parents completed a measure of their own emotional expressiveness, and parents and teachers provided reports of children's self-regulatory skills. Children's school functioning was measured by observations of playground aggression and teacher reports of aggression and classroom behavior. Results Parents’ expression of positive and negative emotions was associated with various aspects of children's self-regulation and functioning in the school setting. Links between self-regulation and children's school adjustment were robust; poor self-regulation was associated with higher aggression and lower cooperation and self-directed behavior in the classroom. There was minimal support for a mediating role of children's self-regulation in links between parent expressiveness and children's behavior. Practice implications Findings point to the relevance of parent emotional expressivity and children's self-regulatory processes in understanding physically abused children's functioning at the transition to school. Although further research is needed, findings indicate that increasing parental expression of positive emotion should be a focus in treatment along with reduction in negativity of abusive parents. Further, addressing children's self-regulation could be important in efforts to reduce aggression and enhance children's classroom competence. PMID:22565040

Intrapersonal and interpersonal functions of non suicidal self-injury: associations with emotional and social functioning.

Science.gov (United States)

Turner, Brianna J; Chapman, Alexander L; Layden, Brianne K

2012-02-01

Understanding the functions of nonsuicidal self-injury (NSSI) has important implications for the development and refinement of theoretical models and treatments of NSSI. Emotional and social vulnerabilities associated with five common functions of NSSI-emotion relief (ER), feeling generation (FG), self-punishment (SP), interpersonal influence (II), and interpersonal communication (IC)-were investigated to clarify why individuals use this behavior in the service of different purposes. Female participants (n = 162) with a history of NSSI completed online measures of self-injury, emotion regulation strategies and abilities, trait affectivity, social problem-solving styles, and interpersonal problems. ER functions were associated with more intense affectivity, expressive suppression, and limited access to emotion regulation strategies. FG functions were associated with a lack of emotional clarity. Similar to ER functions, SP functions were associated with greater affective intensity and expressive suppression. II functions were negatively associated with expressive suppression and positively associated with domineering/controlling and intrusive/needy interpersonal styles. IC functions were negatively associated with expressive suppression and positively associated with a vindictive or self-centered interpersonal style. These findings highlight the specific affective traits, emotional and social skill deficits, and interpersonal styles that may render a person more likely to engage in NSSI to achieve specific goals. © 2012 The American Association of Suicidology.

Unique contributions of emotion regulation and executive functions in predicting the quality of parent-child interaction behaviors.

Science.gov (United States)

Shaffer, Anne; Obradović, Jelena

2017-03-01

Parenting is a cognitive, emotional, and behavioral endeavor, yet limited research investigates parents' executive functions and emotion regulation as predictors of how parents interact with their children. The current study is a multimethod investigation of parental self-regulation in relation to the quality of parenting behavior and parent-child interactions in a diverse sample of parents and kindergarten-age children. Using path analyses, we tested how parent executive functions (inhibitory control) and lack of emotion regulation strategies uniquely relate to both sensitive/responsive behaviors and positive/collaborative behaviors during observed interaction tasks. In our analyses, we accounted for parent education, financial stress, and social support as socioeconomic factors that likely relate to parent executive function and emotion regulation skills. In a diverse sample of primary caregivers (N = 102), we found that direct assessment of parent inhibitory control was positively associated with sensitive/responsive behaviors, whereas parent self-reported difficulties in using emotion regulation strategies were associated with lower levels of positive and collaborative dyadic behaviors. Parent education and financial stress predicted inhibitory control, and social support predicted emotion regulation difficulties; parent education was also a significant predictor of sensitive/responsive behaviors. Greater inhibitory control skills and fewer difficulties identifying effective emotion regulation strategies were not significantly related in our final path model. We discuss our findings in the context of current and emerging parenting interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Psychological distress as a mediator of the association between disease severity and occupational functioning among employed spouses of women recently diagnosed with breast cancer.

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Manne, Sharon L; Siegel, Scott; Heckman, Carolyn J; Kashy, Deborah A

2015-11-01

The purpose was to evaluate whether patient and spouse cancer-specific distress mediated the association between cancer severity and occupational functioning among employed spouses of women diagnosed with breast cancer. We examined whether sociodemographic characteristics, lower spouse-reported marital quality, and lower spouse self-rated health were associated with poorer spouse occupational functioning. One hundred forty-three currently employed spouses of women diagnosed with breast cancer were administered measures of socioeconomic status, occupational functioning (work absenteeism, low productivity, and poor performance), cancer-specific distress, marital quality, and self-rated health. Patients completed measures of cancer-related distress and functional impairment and cancer stage were collected from medical charts. In the model evaluating work absenteeism, greater patient functional impairment was associated with more absenteeism, but there was no evidence of a mediating effect for either partners' cancer-specific distress. Higher cancer stage and more functional impairment were associated with higher spouse cancer-specific distress, which in turn predicted poorer work productivity. Patient cancer-specific distress did not mediate the association between patient functional impairment or cancer stage and spouse work productivity. Finally, higher cancer stage was associated with more spouse cancer-specific distress, which in turn predicted poorer work performance. There were no direct or indirect effects of the patient's functional impairment on spouse work performance. Distressed spouses are more likely to have poorer work productivity after their partners' breast cancer diagnosis. These spouses may need assistance in managing their distress and the patient's functional impairment to ensure that their work productivity is not adversely affected. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct.

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Funk, Christopher S; Kahanda, Indika; Ben-Hur, Asa; Verspoor, Karin M

2015-01-01

Most computational methods that predict protein function do not take advantage of the large amount of information contained in the biomedical literature. In this work we evaluate both ontology term co-mention and bag-of-words features mined from the biomedical literature and analyze their impact in the context of a structured output support vector machine model, GOstruct. We find that even simple literature based features are useful for predicting human protein function (F-max: Molecular Function =0.408, Biological Process =0.461, Cellular Component =0.608). One advantage of using literature features is their ability to offer easy verification of automated predictions. We find through manual inspection of misclassifications that some false positive predictions could be biologically valid predictions based upon support extracted from the literature. Additionally, we present a "medium-throughput" pipeline that was used to annotate a large subset of co-mentions; we suggest that this strategy could help to speed up the rate at which proteins are curated.

Sex differences in the association of physical function and cognitive function with life satisfaction in older age: The Rancho Bernardo Study.

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Ratigan, Amanda; Kritz-Silverstein, Donna; Barrett-Connor, Elizabeth

2016-07-01

This study examines the cross-sectional associations of cognitive and physical function with life satisfaction in middle-class, community-dwelling adults aged 60 and older. Participants were 632 women and 410 men who had cognitive function tests (CFT) and physical function tasks (PFT) assessed at a clinic visit between 1988 and 1992, and who responded in 1992 to a mailed survey that included life satisfaction measures. Cognitive impairment was defined as ≤24 on MMSE, ≥132 on Trails B, ≤12 on Category Fluency, ≤13 on Buschke long-term recall, and ≤7 on Heaton immediate recall. Physical impairment was defined as participants' self-reported difficulty (yes/no) in performing 10 physical functions. Multiple linear regression examined associations between life satisfaction and impairment on ≥1 CFT or difficulty with ≥1 PFT. The Satisfaction with Life Scale (SWLS; range:0-26) and Life Satisfaction Index-Z (LSI-Z; range:5-35). Participants' average age was 73.4 years (range=60-94). Categorically defined cognitive impairment was present in 40% of men and 47% of women. Additionally, 30% of men and 43% of women reported difficulty performing any PFT. Adjusting for age and impairment on ≥1 CFT, difficulty performing ≥1 PFT was associated with lower LSI-Z and SWLS scores in men (β=-1.73, -1.26, respectively, page and difficulty with ≥1 PFT. Limited cognitive function was more common than limited physical function; however, limited physical function was more predictive of lower life satisfaction. Interventions to increase or maintain mobility among older adults may improve overall life satisfaction. Copyright © 2016. Published by Elsevier Ireland Ltd.

Confronting species distribution model predictions with species functional traits.

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Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

Serum 25-Hydroxyvitamin D Level Could Predict the Risk for Peritoneal Dialysis-Associated Peritonitis.

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Pi, Hai-Chen; Ren, Ye-Ping; Wang, Qin; Xu, Rong; Dong, Jie

2015-12-01

♦ As an immune system regulator, vitamin D is commonly deficient among patients on peritoneal dialysis (PD), which may contribute to their impaired immune function and increased risk for PD-related peritonitis. In this study, we aimed to investigate whether vitamin D deficiency could predict the risk of peritonitis in a prospective cohort of patients on PD. ♦ We collected 346 prevalent and incident PD patients from 2 hospitals. Baseline demographic data and clinical characteristics were recorded. Serum 25-hydroxyvitamin D (25[OH]D) was measured at baseline and prior to peritonitis. The mean doses of oral active vitamin D used during the study period were also recorded. The outcome was the occurrence of peritonitis. ♦ The mean age of patients and duration of PD were 58.95 ± 13.67 years and 28.45 (15.04 - 53.37) months, respectively. Baseline 25(OH)D level was 16.15 (12.13 - 21.16) nmol/L, which was closely associated with diabetic status, longer PD duration, malnutrition, and inflammation. Baseline serum 25(OH)D predicted the occurrence of peritonitis independently of active vitamin D supplementation with a hazard ratio (HR) of 0.94 (95% confidence interval [CI] 0.90 - 0.98) after adjusting for recognized confounders (age, gender, dialysis duration, diabetes, albumin, residual renal function, and history of peritonitis). Compared to the low tertile, middle and high 25(OH)D level tertiles were associated with a decreased risk for peritonitis with HRs of 0.54 (95% CI 0.31 - 0.94) and 0.39 (95% CI 0.20 - 0.75), respectively. ♦ Vitamin D deficiency evaluated by serum 25(OH)D rather than active vitamin D supplementation is closely associated with a higher risk of peritonitis. Copyright © 2015 International Society for Peritoneal Dialysis.

Modelling and prediction for chaotic fir laser attractor using rational function neural network.

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Cho, S

2001-02-01

Many real-world systems such as irregular ECG signal, volatility of currency exchange rate and heated fluid reaction exhibit highly complex nonlinear characteristic known as chaos. These chaotic systems cannot be retreated satisfactorily using linear system theory due to its high dimensionality and irregularity. This research focuses on prediction and modelling of chaotic FIR (Far InfraRed) laser system for which the underlying equations are not given. This paper proposed a method for prediction and modelling a chaotic FIR laser time series using rational function neural network. Three network architectures, TDNN (Time Delayed Neural Network), RBF (radial basis function) network and the RF (rational function) network, are also presented. Comparisons between these networks performance show the improvements introduced by the RF network in terms of a decrement in network complexity and better ability of predictability.

Predicting persistence of functional abdominal pain from childhood into young adulthood.

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Horst, Sara; Shelby, Grace; Anderson, Julia; Acra, Sari; Polk, D Brent; Saville, Benjamin R; Garber, Judy; Walker, Lynn S

2014-12-01

Pediatric functional abdominal pain has been linked to functional gastrointestinal disorders (FGIDs) in adulthood, but little is known about patient characteristics in childhood that increase the risk for FGID in young adulthood. We investigated the contribution of gastrointestinal symptoms, extraintestinal somatic symptoms, and depressive symptoms in pediatric patients with functional abdominal pain and whether these predicted FGIDs later in life. In a longitudinal study, consecutive new pediatric patients, diagnosed with functional abdominal pain in a subspecialty clinic, completed a comprehensive baseline evaluation of the severity of their physical and emotional symptoms. They were contacted 5 to 15 years later and evaluated, based on Rome III symptom criteria, for abdominal pain-related FGIDs, including irritable bowel syndrome, functional dyspepsia, functional abdominal pain syndrome, and abdominal migraine. Controlling for age, sex, baseline severity of abdominal pain, and time to follow-up evaluation, multivariable logistic regression was used to evaluate the association of baseline gastrointestinal, extraintestinal somatic, and depressive symptoms in childhood with FGID in adolescence and young adulthood. Of 392 patients interviewed an average of 9.2 years after their initial evaluation, 41% (n = 162) met symptom criteria for FGID; most met the criteria for irritable bowel syndrome. Extraintestinal somatic and depressive symptoms at the initial pediatric evaluation were significant predictors of FGID later in life, after controlling for initial levels of GI symptoms. Age, sex, and abdominal pain severity at initial presentation were not significant predictors of FGID later in life. In pediatric patients with functional abdominal pain, assessment of extraintestinal and depressive symptoms may be useful in identifying those at risk for FGID in adolescence and young adulthood. Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.

Modified Displacement Transfer Functions for Deformed Shape Predictions of Slender Curved Structures with Varying Curvatives

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Ko, William L.; Fleischer, Van Tran

2014-01-01

To eliminate the need to use finite-element modeling for structure shape predictions, a new method was invented. This method is to use the Displacement Transfer Functions to transform the measured surface strains into deflections for mapping out overall structural deformed shapes. The Displacement Transfer Functions are expressed in terms of rectilinearly distributed surface strains, and contain no material properties. This report is to apply the patented method to the shape predictions of non-symmetrically loaded slender curved structures with different curvatures up to a full circle. Because the measured surface strains are not available, finite-element analysis had to be used to analytically generate the surface strains. Previously formulated straight-beam Displacement Transfer Functions were modified by introducing the curvature-effect correction terms. Through single-point or dual-point collocations with finite-elementgenerated deflection curves, functional forms of the curvature-effect correction terms were empirically established. The resulting modified Displacement Transfer Functions can then provide quite accurate shape predictions. Also, the uniform straight-beam Displacement Transfer Function was applied to the shape predictions of a section-cut of a generic capsule (GC) outer curved sandwich wall. The resulting GC shape predictions are quite accurate in partial regions where the radius of curvature does not change sharply.

Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

Directory of Open Access Journals (Sweden)

McCarthy Fiona M

2007-11-01

Full Text Available Abstract Background The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned. Results We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology, we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines. Conclusion We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and

FGWAS: Functional genome wide association analysis.

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Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Longitudinal Associations Between Formal Volunteering and Cognitive Functioning.

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Proulx, Christine M; Curl, Angela L; Ermer, Ashley E

2018-03-02

The present study examines the association between formal volunteering and cognitive functioning over time. We also examine the moderating roles of race, sex, education, and time. Using 11,100 participants aged 51 years and older and nine waves of data from the Health and Retirement Survey, we simultaneously modeled the longitudinal associations between engaging in formal volunteering and changes in cognitive functioning using multilevel models. Formal volunteering was associated with higher levels of cognitive functioning over time, especially with aspects of cognitive functioning related to working memory and processing. This association was stronger for women than it was for men, and for those with below average levels of education. The positive association between formal volunteering and cognitive functioning weakened over time when cognitive functioning was conceptualized as memory, but strengthened over time when conceptualized as working memory and processing. Volunteering is a productive activity that is beneficial not just to society, but to volunteers' levels of cognitive functioning in older age. For women and those with lower levels of education, formal volunteering appears particularly beneficial to working memory and processing. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Progress and challenges in the computational prediction of gene function using networks [v1; ref status: indexed, http://f1000r.es/SqmJUM

Directory of Open Access Journals (Sweden)

Paul Pavlidis

2012-09-01

Full Text Available In this opinion piece, we attempt to unify recent arguments we have made that serious confounds affect the use of network data to predict and characterize gene function. The development of computational approaches to determine gene function is a major strand of computational genomics research. However, progress beyond using BLAST to transfer annotations has been surprisingly slow. We have previously argued that a large part of the reported success in using "guilt by association" in network data is due to the tendency of methods to simply assign new functions to already well-annotated genes. While such predictions will tend to be correct, they are generic; it is true, but not very helpful, that a gene with many functions is more likely to have any function. We have also presented evidence that much of the remaining performance in cross-validation cannot be usefully generalized to new predictions, making progressive improvement in analysis difficult to engineer. Here we summarize our findings about how these problems will affect network analysis, discuss some ongoing responses within the field to these issues, and consolidate some recommendations and speculation, which we hope will modestly increase the reliability and specificity of gene function prediction.

Diabetes Mellitus-Associated Functional Hypercortisolism Impairs Sexual Function in Male Late-Onset Hypogonadism.

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Tirabassi, G; Corona, G; Lamonica, G R; Lenzi, A; Maggi, M; Balercia, G

2016-01-01

Functional hypercortisolism is generated by conditions able to chronically activate hypothalamic-pituitary-adrenal axis and has been proven to have a negative role in several complications. However, no study has evaluated the possible influence of diabetes mellitus-associated functional hypercortisolism on male hypogonadism and sexual function. We aimed to identify any association of hypothalamic-pituitary-adrenal axis dysregulation measures with testosterone and sexual function in men simultaneously affected by diabetes mellitus and late-onset hypogonadism. Fifteen diabetes mellitus and late-onset hypogonadism subjects suffering from functional hypercortisolism and fifteen diabetes mellitus and late-onset hypogonadism subjects who were free of functional hypercortisolism were retrospectively reviewed. Clinical, hormonal, and sexual parameters were considered. Hypercortisolemic subjects showed higher values of body mass index, waist, and glycated hemoglobin and lower ones of testosterone compared to normocortisolemic ones. All sexual parameters, except for orgasmic function, were significantly worse in hypercortisolemic than in normocortisolemic subjects. Hypercortisolemic patients showed higher values of cortisol after dexamethasone and urinary free cortisol as well as a lesser ACTH response after corticotropin releasing hormone test (ACTH area under curve) compared to normocortisolemic ones. No significant association was found at Poisson regression analysis between hormonal and sexual variables in normocortisolemic patients. In hypercortisolemic subjects, negative and significant associations of cortisol response after corticotropin releasing hormone (cortisol area under curve) with erectile function (β: -0.0008; p: 0.015) and total international index of erectile function score (β: -0.0006; p: 0.001) were evident. This study suggests for the first time the impairing influence of the dysregulated hypothalamic-pituitary-adrenal axis on sexual function in

Cognitive function predicts 24-month weight loss success after bariatric surgery.

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Spitznagel, Mary Beth; Alosco, Michael; Strain, Gladys; Devlin, Michael; Cohen, Ronald; Paul, Robert; Crosby, Ross D; Mitchell, James E; Gunstad, John

2013-01-01

Clinically significant cognitive impairment, particularly in attention/executive and memory function, is found in many patients undergoing bariatric surgery. These difficulties have previously been linked to decreased weight loss 12 months after surgery, but more protracted examination of this relationship has not yet been conducted. The present study prospectively examined the independent contribution of cognitive function to weight loss 24 months after bariatric surgery. Given the rapid rate of cognitive improvement observed after surgery, postoperative cognitive function (i.e., cognition 12 weeks after surgery, controlling for baseline cognition) was expected to predict lower body mass index (BMI) and higher percent total weight loss (%WL) at 24-month follow-up. Data were collected by 3 sites of the Longitudinal Assessment of Bariatric Surgery (LABS) parent project. Fifty-seven individuals enrolled in the LABS project who were undergoing bariatric surgery completed cognitive evaluation at baseline, 12 weeks, and 24 months. BMI and %WL were calculated for 24-month postoperative follow-up. Better cognitive function 12 weeks after surgery predicted higher %WL and lower BMI at 24 months, and specific domains of attention/executive and memory function were robustly related to decreased BMI and greater %WL at 24 months. Results show that cognitive performance shortly after bariatric surgery predicts greater long-term %WL and lower BMI 24 months after bariatric surgery. Further work is needed to clarify the degree to which this relationship is mediated by adherence to postoperative guidelines. Copyright © 2013 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Motivational and neurocognitive deficits are central to the prediction of longitudinal functional outcome in schizophrenia.

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Fervaha, G; Foussias, G; Agid, O; Remington, G

2014-10-01

Functional impairment is characteristic of most individuals with schizophrenia; however, the key variables that undermine community functioning are not well understood. This study evaluated the association between selected clinical variables and one-year longitudinal functional outcomes in patients with schizophrenia. The sample included 754 patients with schizophrenia who completed both baseline and one-year follow-up visits in the CATIE study. Patients were evaluated with a comprehensive battery of assessments capturing symptom severity and cognitive performance among other variables. The primary outcome variable was functional status one-year postbaseline measured using the Heinrichs-Carpenter Quality of Life Scale. Factor analysis of negative symptom items revealed two factors reflecting diminished expression and amotivation. Multivariate regression modeling revealed several significant independent predictors of longitudinal functioning scores. The strongest predictors were baseline amotivation and neurocognition. Both amotivation and neurocognition also had independent predictive value for each of the domains of functioning assessed (e.g., vocational). Both motivational and neurocognitive deficits independently contribute to longitudinal functional outcomes assessed 1 year later among patients with schizophrenia. Both of these domains of psychopathology impede functional recovery; hence, it follows that treatments ameliorating each of these symptoms should promote community functioning among individuals with schizophrenia. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

Directory of Open Access Journals (Sweden)

Sungkyoung Choi

2016-12-01

Full Text Available The success of genome-wide association studies (GWASs has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR, least absolute shrinkage and selection operator (LASSO, and Elastic-Net (EN. We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

Do Children's Executive Functions Account for Associations Between Early Autonomy-Supportive Parenting and Achievement Through High School?

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Bindman, Samantha W; Pomerantz, Eva M; Roisman, Glenn I

2015-08-01

This study evaluated whether the positive association between early autonomy-supportive parenting and children's subsequent achievement is mediated by children's executive functions. Using observations of mothers' parenting from the NICHD Study of Early Child Care and Youth Development ( N = 1,306), analyses revealed that mothers' autonomy support over the first 3 years of life predicted enhanced executive functions (i.e., inhibition, delay of gratification, and sustained attention) during the year prior to kindergarten and academic achievement in elementary and high school even when mothers' warmth and cognitive stimulation, as well as other factors (e.g., children's early general cognitive skills and mothers' educational attainment) were covaried. Mediation analyses demonstrated that over and above other attributes (e.g., temperament), children's executive functions partially accounted for the association between early autonomy-supportive parenting and children's subsequent achievement.

The Density Functional Theory of Flies: Predicting distributions of interacting active organisms

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Kinkhabwala, Yunus; Valderrama, Juan; Cohen, Itai; Arias, Tomas

On October 2nd, 2016, 52 people were crushed in a stampede when a crowd panicked at a religious gathering in Ethiopia. The ability to predict the state of a crowd and whether it is susceptible to such transitions could help prevent such catastrophes. While current techniques such as agent based models can predict transitions in emergent behaviors of crowds, the assumptions used to describe the agents are often ad hoc and the simulations are computationally expensive making their application to real-time crowd prediction challenging. Here, we pursue an orthogonal approach and ask whether a reduced set of variables, such as the local densities, are sufficient to describe the state of a crowd. Inspired by the theoretical framework of Density Functional Theory, we have developed a system that uses only measurements of local densities to extract two independent crowd behavior functions: (1) preferences for locations and (2) interactions between individuals. With these two functions, we have accurately predicted how a model system of walking Drosophila melanogaster distributes itself in an arbitrary 2D environment. In addition, this density-based approach measures properties of the crowd from only observations of the crowd itself without any knowledge of the detailed interactions and thus it can make predictions about the resulting distributions of these flies in arbitrary environments, in real-time. This research was supported in part by ARO W911NF-16-1-0433.

Predictive features associated with thyrotoxic storm and management.

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Bacuzzi, Alessandro; Dionigi, Gianlorenzo; Guzzetti, Luca; De Martino, Alessandro Ivan; Severgnini, Paolo; Cuffari, Salvatore

2017-10-01

Thyroid storm (TS) is an endocrine emergency characterized by rapid deterioration, associated with high mortality rate therefore rapid diagnosis and emergent treatment is mandatory. In the past, thyroid surgery was the most common cause of TS, but recent preoperative medication creates a euthyroid state before performing surgery. An active approach during perioperative period could determine an effective clinical treatment of this life-threating diseases. Recently, the Japan Thyroid Association and Japan Endocrine Society developed diagnostic criteria for TS focusing on premature and prompt diagnosis avoiding inopportune e useless drugs. This review analyses predictive features associated with thyrotoxic storm highlighting recent literature to optimize the patient quality of care.

The association between alcohol drinking and self-reported mental and physical functioning: a prospective cohort study among City of Helsinki employees.

Science.gov (United States)

Salonsalmi, Aino; Rahkonen, Ossi; Lahelma, Eero; Laaksonen, Mikko

2017-05-04

Alcohol drinking is associated with ill health but less is known about its contribution to overall functioning. We aimed to examine whether alcohol drinking predicts self-reported mental and physical functioning 5-7 years later. A prospective cohort study. Helsinki, Finland. 40-year-old to 60-year-old employees of the City of Helsinki (5301 women and 1230 men) who participated in a postal survey in 2000-2002 and a follow-up survey in 2007. Mental and physical functioning measured by the Short Form 36 Health Survey. Alcohol drinking was differently associated with mental and physical functioning. Heavy average drinking, binge drinking and problem drinking were all associated with subsequent poor mental functioning except for heavy average drinking among men, whereas only problem drinking was associated with poor physical functioning. Also, non-drinking was associated with poor physical functioning. Problem drinking was the drinking habit showing most widespread and strongest associations with health functioning. The associations between problem drinking and poor mental functioning and with poor physical functioning among women remained after adjusting for baseline mental functioning, sociodemographic factors, working conditions and other health behaviours. Alcohol drinking is associated especially with poor mental functioning. Problem drinking was the drinking habit strongest associated with poor health functioning. The results call for early recognition and prevention of alcohol problems in order to improve health functioning among employees. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Prediction of Detailed Enzyme Functions and Identification of Specificity Determining Residues by Random Forests

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Nagao, Chioko; Nagano, Nozomi; Mizuguchi, Kenji

2014-01-01

Determining enzyme functions is essential for a thorough understanding of cellular processes. Although many prediction methods have been developed, it remains a significant challenge to predict enzyme functions at the fourth-digit level of the Enzyme Commission numbers. Functional specificity of enzymes often changes drastically by mutations of a small number of residues and therefore, information about these critical residues can potentially help discriminate detailed functions. However, because these residues must be identified by mutagenesis experiments, the available information is limited, and the lack of experimentally verified specificity determining residues (SDRs) has hindered the development of detailed function prediction methods and computational identification of SDRs. Here we present a novel method for predicting enzyme functions by random forests, EFPrf, along with a set of putative SDRs, the random forests derived SDRs (rf-SDRs). EFPrf consists of a set of binary predictors for enzymes in each CATH superfamily and the rf-SDRs are the residue positions corresponding to the most highly contributing attributes obtained from each predictor. EFPrf showed a precision of 0.98 and a recall of 0.89 in a cross-validated benchmark assessment. The rf-SDRs included many residues, whose importance for specificity had been validated experimentally. The analysis of the rf-SDRs revealed both a general tendency that functionally diverged superfamilies tend to include more active site residues in their rf-SDRs than in less diverged superfamilies, and superfamily-specific conservation patterns of each functional residue. EFPrf and the rf-SDRs will be an effective tool for annotating enzyme functions and for understanding how enzyme functions have diverged within each superfamily. PMID:24416252

Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

Energy Technology Data Exchange (ETDEWEB)

Triplett, T; Yurchak, D [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

1997-12-31

This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

Energy Technology Data Exchange (ETDEWEB)

Triplett, T.; Yurchak, D. [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

1996-12-31

This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

Lagged Associations of Metropolitan Statistical Area- and State-Level Income Inequality with Cognitive Function: The Health and Retirement Study.

Science.gov (United States)

Kim, Daniel; Griffin, Beth Ann; Kabeto, Mohammed; Escarce, José; Langa, Kenneth M; Shih, Regina A

2016-01-01

Much variation in individual-level cognitive function in late life remains unexplained, with little exploration of area-level/contextual factors to date. Income inequality is a contextual factor that may plausibly influence cognitive function. In a nationally-representative cohort of older Americans from the Health and Retirement Study, we examined state- and metropolitan statistical area (MSA)-level income inequality as predictors of individual-level cognitive function measured by the 27-point Telephone Interview for Cognitive Status (TICS-m) scale. We modeled latency periods of 8-20 years, and controlled for state-/metropolitan statistical area (MSA)-level and individual-level factors. Higher MSA-level income inequality predicted lower cognitive function 16-18 years later. Using a 16-year lag, living in a MSA in the highest income inequality quartile predicted a 0.9-point lower TICS-m score (β = -0.86; 95% CI = -1.41, -0.31), roughly equivalent to the magnitude associated with five years of aging. We observed no associations for state-level income inequality. The findings were robust to sensitivity analyses using propensity score methods. Among older Americans, MSA-level income inequality appears to influence cognitive function nearly two decades later. Policies reducing income inequality levels within cities may help address the growing burden of declining cognitive function among older populations within the United States.

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

Science.gov (United States)

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Misalignment Effect Function Measurement for Oblique Rotation Axes: Counterintuitive Predictions and Theoretical Extensions

Science.gov (United States)

Ellis, Stephen R.; Adelstein, Bernard D.; Yeom, Kiwon

2013-01-01

The Misalignment Effect Function (MEF) describes the decrement in manual performance associated with a rotation between operators' visual display frame of reference and that of their manual control. It now has been empirically determined for rotation axes oblique to canonical body axes and is compared with the MEF previously measured for rotations about canonical axes. A targeting rule, called the Secant Rule, based on these earlier measurements is derived from a hypothetical process and shown to describe some of the data from three previous experiments. It explains the motion trajectories determined for rotations less than 65deg in purely kinematic terms without the need to appeal to a mental rotation process. Further analysis of this rule in three dimensions applied to oblique rotation axes leads to a somewhat surprising expectation that the difficulty posed by rotational misalignment should get harder as the required movement is shorter. This prediction is confirmed. Geometry underlying this rule also suggests analytic extensions for predicting more generally the difficulty of making movements in arbitrary directions subject to arbitrary misalignments.

Prediction of human protein function according to Gene Ontology categories

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Stærfeldt, Hans Henrik

2003-01-01

developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors...

Prediction of functional sites in proteins using conserved functional group analysis.

Science.gov (United States)

Innis, C Axel; Anand, A Prem; Sowdhamini, R

2004-04-02

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

Science.gov (United States)

Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

2017-03-19

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Cognitive functioning differentially predicts different dimensions of older drivers' on-road safety.

Science.gov (United States)

Aksan, Nazan; Anderson, Steve W; Dawson, Jeffrey; Uc, Ergun; Rizzo, Matthew

2015-02-01

The extent to which deficits in specific cognitive domains contribute to older drivers' safety risk in complex real-world driving tasks is not well understood. We selected 148 drivers older than 70 years of age both with and without neurodegenerative diseases (Alzheimer disease-AD and Parkinson disease-PD) from an existing driving database of older adults. Participant assessments included on-road driving safety and cognitive functioning in visuospatial construction, speed of processing, memory, and executive functioning. The standardized on-road drive test was designed to examine multiple facets of older driver safety including navigation performance (e.g., following a route, identifying landmarks), safety errors while concurrently performing secondary navigation tasks ("on-task" safety errors), and safety errors in the absence of any secondary navigation tasks ("baseline" safety errors). The inter-correlations of these outcome measures were fair to moderate supporting their distinctiveness. Participants with diseases performed worse than the healthy aging group on all driving measures and differences between those with AD and PD were minimal. In multivariate analyses, different domains of cognitive functioning predicted distinct facets of driver safety on road. Memory and set-shifting predicted performance in navigation-related secondary tasks, speed of processing predicted on-task safety errors, and visuospatial construction predicted baseline safety errors. These findings support broad assessments of cognitive functioning to inform decisions regarding older driver safety on the road and suggest navigation performance may be useful in evaluating older driver fitness and restrictions in licensing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease*

Science.gov (United States)

Dewhurst, Henry; Sundararaman, Niveda

2016-01-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease.

Science.gov (United States)

Torres, Matthew P; Dewhurst, Henry; Sundararaman, Niveda

2016-11-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

Association of High-Dose Ibuprofen Use, Lung Function Decline, and Long-Term Survival in Children with Cystic Fibrosis.

Science.gov (United States)

Konstan, Michael W; VanDevanter, Donald R; Sawicki, Gregory S; Pasta, David J; Foreman, Aimee J; Neiman, Evgueni A; Morgan, Wayne J

2018-04-01

Cystic fibrosis deaths result primarily from lung function loss, so chronic respiratory therapies, intended to preserve lung function, are cornerstones of cystic fibrosis care. Although treatment-associated reduction in rate of lung function loss should ultimately improve cystic fibrosis survival, no such relationship has been described for any chronic cystic fibrosis therapy. In part, this is because the ages of most rapid lung function decline-early adolescence-precede the median age of cystic fibrosis deaths by more than a decade. To study associations of high-dose ibuprofen treatment with the rate of forced expiratory volume in 1 second decline and mortality among children followed in the Epidemiologic Study of Cystic Fibrosis and subsequently in the U.S. Cystic Fibrosis Foundation Patient Registry. We performed a matched cohort study using data from Epidemiologic Study of Cystic Fibrosis. Exposure was defined as high-dose ibuprofen use reported at ≥80% of encounters over 2 years. Unexposed children were matched to exposed children 5:1 using propensity scores on the basis of demographic, clinical, and treatment covariates. The rate of decline of percent predicted forced expiratory volume in 1 second during the 2-year follow-up period was estimated by mixed-effects modeling with random slopes and intercepts. Survival over 16 follow-up years in the U.S. Cystic Fibrosis Foundation Patient Registry was compared between treatment groups by using proportional hazards modeling controlling for matching and covariates. We included 775 high-dose ibuprofen users and 3,665 nonusers who were well matched on demographic, clinical, and treatment variables. High-dose ibuprofen users declined on average 1.10 percent predicted forced expiratory volume in 1 second/yr (95% confidence interval; 0.51, 1.69) during the 2-year treatment period, whereas nonusers declined at a rate of 1.76% percent predicted forced expiratory volume in 1 second/yr (95% confidence interval; 1.48, 2

Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

Science.gov (United States)

Choi, Ickwon; Chung, Amy W; Suscovich, Todd J; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J; Francis, Donald; Robb, Merlin L; Michael, Nelson L; Kim, Jerome H; Alter, Galit; Ackerman, Margaret E; Bailey-Kellogg, Chris

2015-04-01

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

Directory of Open Access Journals (Sweden)

Ickwon Choi

2015-04-01

Full Text Available The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release. We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

Diuretic renography in hydronephrosis: renal tissue tracer transit predicts functional course and thereby need for surgery

Energy Technology Data Exchange (ETDEWEB)

Schlotmann, Andreas [University Hospital Freiburg, Department of Nuclear Medicine and Department of Radiation Oncology, Freiburg (Germany); Clorius, John H. [German Cancer Research Center, Heidelberg (Germany); Clorius, Sandra N. [University Hospital Basel, Department of Internal Medicine, Basel (Switzerland)

2009-10-15

The recognition of those hydronephrotic kidneys which require therapy to preserve renal function remains difficult. We retrospectively compared the 'tissue tracer transit' (TTT) of {sup 99m}Tc-mercaptoacetyltriglycine ({sup 99m}Tc-MAG{sub 3}) with 'response to furosemide stimulation' (RFS) and with 'single kidney function < 40%' (SKF < 40%) to predict functional course and thereby need for surgery. Fifty patients with suspected unilateral obstruction and normal contralateral kidney had 115 paired (baseline/follow-up) {sup 99m}Tc-MAG{sub 3} scintirenographies. Three predictions of the functional development were derived from each baseline examination: the first based on TTT (visually assessed), the second on RFS and the third on SKF < 40%. Each prediction also considered whether the patient had surgery. Possible predictions were 'better', 'worse' or 'stable' function. A comparison of SKF at baseline and follow-up verified the predictions. The frequency of correct predictions for functional improvement following surgery was 8 of 10 kidneys with delayed TTT, 9 of 22 kidneys with obstructive RFS and 9 of 21 kidneys with SKF < 40%; for functional deterioration without surgery it was 2 of 3 kidneys with delayed TTT, 3 of 20 kidneys with obstructive RFS and 3 of 23 kidneys with SKF < 40%. Without surgery 67 of 70 kidneys with timely TTT maintained function. Without surgery 0 of 9 kidneys with timely TTT but obstructive RFS and only 1 of 16 kidneys with timely TTT but SKF < 40% lost function. Delayed TTT appears to identify the need for therapy to preserve function of hydronephrotic kidneys, while timely TTT may exclude risk even in the presence of an obstructive RFS or SKF < 40%. (orig.)

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

Science.gov (United States)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Less-structured time in children's daily lives predicts self-directed executive functioning.

Science.gov (United States)

Barker, Jane E; Semenov, Andrei D; Michaelson, Laura; Provan, Lindsay S; Snyder, Hannah R; Munakata, Yuko

2014-01-01

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up.

Functional imaging of semantic memory predicts postoperative episodic memory functions in chronic temporal lobe epilepsy.

Science.gov (United States)

Köylü, Bülent; Walser, Gerald; Ischebeck, Anja; Ortler, Martin; Benke, Thomas

2008-08-05

Medial temporal (MTL) structures have crucial functions in episodic (EM), but also in semantic memory (SM) processing. Preoperative functional magnetic resonance imaging (fMRI) activity within the MTL is increasingly used to predict post-surgical memory capacities. Based on the hypothesis that EM and SM memory functions are both hosted by the MTL the present study wanted to explore the relationship between SM related activations in the MTL as assessed before and the capacity of EM functions after surgery. Patients with chronic unilateral left (n=14) and right (n=12) temporal lobe epilepsy (TLE) performed a standard word list learning test pre- and postoperatively, and a fMRI procedure before the operation using a semantic decision task. SM processing caused significant bilateral MTL activations in both patient groups. While right TLE patients showed asymmetry of fMRI activation with more activation in the left MTL, left TLE patients had almost equal activation in both MTL regions. Contrasting left TLE versus right TLE patients revealed greater activity within the right MTL, whereas no significant difference was observed for the reverse contrast. Greater effect size in the MTL region ipsilateral to the seizure focus was significantly and positively correlated with preoperative EM abilities. Greater effect size in the contralateral MTL was correlated with better postoperative verbal EM, especially in left TLE patients. These results suggest that functional imaging of SM tasks may be useful to predict postoperative verbal memory in TLE. They also advocate a common neuroanatomical basis for SM and EM processes in the MTL.

In silico prediction of novel therapeutic targets using gene-disease association data.

Science.gov (United States)

Ferrero, Enrico; Dunham, Ian; Sanseau, Philippe

2017-08-29

Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is sufficient to predict therapeutic targets that are actively being pursued by pharmaceutical companies or are already on the market. To test our hypothesis, we train four different classifiers (a random forest, a support vector machine, a neural network and a gradient boosting machine) on partially labelled data and evaluate their performance using nested cross-validation and testing on an independent set. We then select the best performing model and use it to make predictions on more than 15,000 genes. Finally, we validate our predictions by mining the scientific literature for proposed therapeutic targets. We observe that the data types with the best predictive power are animal models showing a disease-relevant phenotype, differential expression in diseased tissue and genetic association with the disease under investigation. On a test set, the neural network classifier achieves over 71% accuracy with an AUC of 0.76 when predicting therapeutic targets in a semi-supervised learning setting. We use this model to gain insights into current and failed programmes and to predict 1431 novel targets, of which a highly significant proportion has been independently proposed in the literature. Our in silico approach shows that data linking genes and diseases is sufficient to predict novel therapeutic targets effectively and confirms that this type of evidence is essential for formulating or strengthening hypotheses in the target discovery process. Ultimately, more rapid and automated target

Conditional mode regression: Application to functional time series prediction

OpenAIRE

Dabo-Niang, Sophie; Laksaci, Ali

2008-01-01

We consider $\\alpha$-mixing observations and deal with the estimation of the conditional mode of a scalar response variable $Y$ given a random variable $X$ taking values in a semi-metric space. We provide a convergence rate in $L^p$ norm of the estimator. A useful and typical application to functional times series prediction is given.

Functional imaging of the cerebellum and basal ganglia during predictive motor timing in early Parkinson's disease.

Science.gov (United States)

Husárová, Ivica; Lungu, Ovidiu V; Mareček, Radek; Mikl, Michal; Gescheidt, Tomáš; Krupa, Petr; Bareš, Martin

2014-01-01

The basal ganglia and the cerebellum have both emerged as important structures involved in the processing of temporal information. We examined the roles of the cerebellum and striatum in predictive motor timing during a target interception task in healthy individuals (HC group; n = 21) and in patients with early Parkinson's disease (early stage PD group; n = 20) using functional magnetic resonance imaging. Despite having similar hit ratios, the PD failed more often than the HC to postpone their actions until the right moment and to adapt their behavior from one trial to the next. We found more activation in the right cerebellar lobule VI in HC than in early stage PD during successful trials. Successful trial-by-trial adjustments were associated with higher activity in the right putamen and lobule VI of the cerebellum in HC. We conclude that both the cerebellum and striatum are involved in predictive motor timing tasks. The cerebellar activity is associated exclusively with the postponement of action until the right moment, whereas both the cerebellum and striatum are needed for successful adaptation of motor actions from one trial to the next. We found a general ''hypoactivation'' of basal ganglia and cerebellum in early stage PD relative to HC, indicating that even in early stages of the PD there could be functional perturbations in the motor system beyond striatum. Copyright © 2011 by the American Society of Neuroimaging.

Functional leaf attributes predict litter decomposition rate in herbaceous plants

NARCIS (Netherlands)

Cornelissen, J. H C; Thompson, K.

1997-01-01

We tested the hypothesis that functional attributes of living leaves provide a basis for predicting the decomposition rate of leaf litter. The data were obtained from standardized screening tests on 38 British herbaceous species. Graminoid monocots had physically tougher leaves with higher silicon

Genetic variants associated with lung function

DEFF Research Database (Denmark)

Thyagarajan, Bharat; Wojczynski, Mary; Minster, Ryan L

2014-01-01

with exceptional longevity have not been identified. METHOD: We conducted a genome wide association study (GWAS) to identify novel genetic variants associated with lung function in the Long Life Family Study (LLFS) (n = 3,899). Replication was performed using data from the CHARGE/SpiroMeta consortia...

Developing a risk prediction model for the functional outcome after hip arthroscopy.

Science.gov (United States)

Stephan, Patrick; Röling, Maarten A; Mathijssen, Nina M C; Hannink, Gerjon; Bloem, Rolf M

2018-04-19

Hip arthroscopic treatment is not equally beneficial for every patient undergoing this procedure. Therefore, the purpose of this study was to develop a clinical prediction model for functional outcome after surgery based on preoperative factors. Prospective data was collected on a cohort of 205 patients having undergone hip arthroscopy between 2011 and 2015. Demographic and clinical variables and patient reported outcome (PRO) scores were collected, and considered as potential predictors. Successful outcome was defined as either a Hip Outcome Score (HOS)-ADL score of over 80% or improvement of 23%, defined by the minimal clinical important difference, 1 year after surgery. The prediction model was developed using backward logistic regression. Regression coefficients were converted into an easy to use prediction rule. The analysis included 203 patients, of which 74% had a successful outcome. Female gender (OR: 0.37 (95% CI 0.17-0.83); p = 0.02), pincer impingement (OR: 0.47 (95% CI 0.21-1.09); p = 0.08), labral tear (OR: 0.46 (95% CI 0.20-1.06); p = 0.07), HOS-ADL score (IQR OR: 2.01 (95% CI 0.99-4.08); p = 0.05), WHOQOL physical (IQR OR: 0.43 (95% CI 0.22-0.87); p = 0.02) and WHOQOL psychological (IQR OR: 2.40 (95% CI 1.38-4.18); p = prediction model of successful functional outcome 1 year after hip arthroscopy. The model's discriminating accuracy turned out to be fair, as 71% (95% CI: 64-80%) of the patients were classified correctly. The developed prediction model can predict the functional outcome of patients that are considered for a hip arthroscopic intervention, containing six easy accessible preoperative risk factors. The model can be further improved trough external validation and/or adding additional potential predictors.

Accurate prediction of the functional significance of single nucleotide polymorphisms and mutations in the ABCA1 gene.

Directory of Open Access Journals (Sweden)

Liam R Brunham

2005-12-01

Full Text Available The human genome contains an estimated 100,000 to 300,000 DNA variants that alter an amino acid in an encoded protein. However, our ability to predict which of these variants are functionally significant is limited. We used a bioinformatics approach to define the functional significance of genetic variation in the ABCA1 gene, a cholesterol transporter crucial for the metabolism of high density lipoprotein cholesterol. To predict the functional consequence of each coding single nucleotide polymorphism and mutation in this gene, we calculated a substitution position-specific evolutionary conservation score for each variant, which considers site-specific variation among evolutionarily related proteins. To test the bioinformatics predictions experimentally, we evaluated the biochemical consequence of these sequence variants by examining the ability of cell lines stably transfected with the ABCA1 alleles to elicit cholesterol efflux. Our bioinformatics approach correctly predicted the functional impact of greater than 94% of the naturally occurring variants we assessed. The bioinformatics predictions were significantly correlated with the degree of functional impairment of ABCA1 mutations (r2 = 0.62, p = 0.0008. These results have allowed us to define the impact of genetic variation on ABCA1 function and to suggest that the in silico evolutionary approach we used may be a useful tool in general for predicting the effects of DNA variation on gene function. In addition, our data suggest that considering patterns of positive selection, along with patterns of negative selection such as evolutionary conservation, may improve our ability to predict the functional effects of amino acid variation.

Stability of the DSM-5 Section III pathological personality traits and their longitudinal associations with psychosocial functioning in personality disordered individuals.

Science.gov (United States)

Wright, Aidan G C; Calabrese, William R; Rudick, Monica M; Yam, Wern How; Zelazny, Kerry; Williams, Trevor F; Rotterman, Jane H; Simms, Leonard J

2015-02-01

This study was conducted to establish (a) the stability of the DSM-5 Section III personality disorder (PD) traits, (b) whether these traits predict future psychosocial functioning, and (c) whether changes in traits track with changes in psychosocial functioning across time. Ninety-three outpatients (61% female) diagnosed with at least 1 PD completed patient-report measures at 2 time-points (M time between assessments = 1.44 years), including the Personality Inventory for the DSM-5 and several measures of psychosocial functioning. Effect sizes of rank-order and mean-level change were calculated. In addition, Time 1 traits were used to predict functioning measures at Time 2. Finally, latent change score models were estimated for DSM-5 Section III traits and functioning measures, and correlations among latent change scores were calculated to establish the relationship between change in traits and functional outcomes. Findings demonstrated that the DSM-5 Section III traits were highly stable in terms of normative (i.e., mean-level) change and rank-order stability over the course of the study. Furthermore, traits prospectively predicted psychosocial functioning. However, at the individual level traits and functioning were not entirely static over the study, and change in individuals' functioning tracked with changes in trait levels. These findings demonstrate that the DSM-5 Section III traits are highly stable consistent with the definition of PD, prospectively predictive of psychosocial functioning, and are dynamically associated with functioning over time. This study provides important evidence in support of the DSM-5 Section III PD model. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels

Directory of Open Access Journals (Sweden)

Chika Sumiyoshi

2015-09-01

Full Text Available Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1 to identify which outcome factors predict occupational functioning, quantified as work hours, and 2 to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB, the UCSD Performance-based Skills Assessment-Brief (UPSA-B, and the Social Functioning Scale Individuals’ version modified for the MATRICS-PASS (Modified SFS for PASS, respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly and a multiple logistic regression analyses (predicting dichotomized work status based on work hours. ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60–70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Impairment of executive function and attention predicts onset of affective disorder in healthy high-risk twins

DEFF Research Database (Denmark)

Vinberg, Maj; Miskowiak, Kamilla W; Kessing, Lars Vedel

2013-01-01

To investigate whether measures of cognitive function can predict onset of affective disorder in individuals at heritable risk.......To investigate whether measures of cognitive function can predict onset of affective disorder in individuals at heritable risk....

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

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Cao, Renzhi; Freitas, Colton; Chan, Leong; Sun, Miao; Jiang, Haiqing; Chen, Zhangxin

2017-10-17

With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological experimental techniques. Protein function prediction has been a long standing challenge to fill the gap between the huge amount of protein sequences and the known function. In this paper, we propose a novel method to convert the protein function problem into a language translation problem by the new proposed protein sequence language "ProLan" to the protein function language "GOLan", and build a neural machine translation model based on recurrent neural networks to translate "ProLan" language to "GOLan" language. We blindly tested our method by attending the latest third Critical Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the performance of our methods on selected proteins whose function was released after CAFA competition. The good performance on the training and testing datasets demonstrates that our new proposed method is a promising direction for protein function prediction. In summary, we first time propose a method which converts the protein function prediction problem to a language translation problem and applies a neural machine translation model for protein function prediction.

Pressure Prediction of Coal Slurry Transportation Pipeline Based on Particle Swarm Optimization Kernel Function Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Xue-cun Yang

2015-01-01

Full Text Available For coal slurry pipeline blockage prediction problem, through the analysis of actual scene, it is determined that the pressure prediction from each measuring point is the premise of pipeline blockage prediction. Kernel function of support vector machine is introduced into extreme learning machine, the parameters are optimized by particle swarm algorithm, and blockage prediction method based on particle swarm optimization kernel function extreme learning machine (PSOKELM is put forward. The actual test data from HuangLing coal gangue power plant are used for simulation experiments and compared with support vector machine prediction model optimized by particle swarm algorithm (PSOSVM and kernel function extreme learning machine prediction model (KELM. The results prove that mean square error (MSE for the prediction model based on PSOKELM is 0.0038 and the correlation coefficient is 0.9955, which is superior to prediction model based on PSOSVM in speed and accuracy and superior to KELM prediction model in accuracy.

Prediction and Assignment of Function for a Divergent N-succinyl Amino Acid Racemase

Energy Technology Data Exchange (ETDEWEB)

Song,L.; Kalyanaraman, C.; Fedorov, A.; Fedorov, E.; Glasner, M.; Brown, S.; Imker, H.; Babbitt, P.; Almo, S.; et al.

2007-01-01

The protein databases contain many proteins with unknown function. A computational approach for predicting ligand specificity that requires only the sequence of the unknown protein would be valuable for directing experiment-based assignment of function. We focused on a family of unknown proteins in the mechanistically diverse enolase superfamily and used two approaches to assign function: (i) enzymatic assays using libraries of potential substrates, and (ii) in silico docking of the same libraries using a homology model based on the most similar (35% sequence identity) characterized protein. The results matched closely; an experimentally determined structure confirmed the predicted structure of the substrate-liganded complex. We assigned the N-succinyl arginine/lysine racemase function to the family, correcting the annotation (L-Ala-D/L-Glu epimerase) based on the function of the most similar characterized homolog. These studies establish that ligand docking to a homology model can facilitate functional assignment of unknown proteins by restricting the identities of the possible substrates that must be experimentally tested.

Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

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Sers Christine T

2010-12-01

Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

Towards virtual surgery in oral cancer to predict postoperative oral functions preoperatively

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van Alphen, M.J.A.; Kreeft, A.M.; van der Heijden, Ferdinand; Smeele, L.E.; Balm, A.J.M.; Balm, Alfonsus Jacobus Maria

2013-01-01

Our aim was to develop a dynamic virtual model of the oral cavity and oropharynx so that we could incorporate patient-specific factors into the prediction of functional loss after advanced resections for oral cancer. After a virtual resection, functional consequences can be assessed, and a more

Prediction of postoperative pulmonary function following thoracic operations. Value of ventilation-perfusion scanning

International Nuclear Information System (INIS)

Bria, W.F.; Kanarek, D.J.; Kazemi, H.

1983-01-01

Surgical resection of lung cancer is frequently required in patients with severely impaired lung function resulting from chronic obstructive pulmonary disease. Twenty patients with obstructive lung disease and cancer (mean preoperative forced expiratory volume in 1 second [FEV1] . 1.73 L) were studied preoperatively and postoperatively by spirometry and radionuclide perfusion, single-breath ventilation, and washout techniques to test the ability of these methods to predict preoperatively the partial loss of lung function by the resection. Postoperative FEV1 and forced vital capacity (FVC) were accurately predicted by the formula: postoperative FEV1 (or FVC) . preoperative FEV1 X percent function of regions of lung not to be resected (r . 0.88 and 0.95, respectively). Ventilation and perfusion scans are equally effective in prediction. Washout data add to the sophistication of the method by permitting the qualitative evaluation of ventilation during tidal breathing. Criteria for patients requiring the study are suggested

FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions

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Hui Li

2018-04-01

Full Text Available smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

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Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Does neurocognitive function affect cognitive bias toward an emotional stimulus? Association between general attentional ability and attentional bias toward threat

OpenAIRE

Hakamata, Yuko; Matsui, Mie; Tagaya, Hirokuni

2014-01-01

Background: Although poorer cognitive performance has been found to be associated with anxiety, it remains unclear whether neurocognitive function affects biased cognitive processing toward emotional information. We investigated whether general cognitive function evaluated with a standard neuropsychological test predicts biased cognition, focusing on attentional bias toward threat. Methods: One hundred and five healthy young adults completed a dot-probe task measuring attentional bias and ...

Association Between Variants of PRDM1 and NDP52 and Crohn's Disease, Based on Exome Sequencing and Functional Studies

DEFF Research Database (Denmark)

Ellinghaus, David; Zhang, Hu; Zeissig, Sebastian

2013-01-01

BACKGROUND & AIMS: Genome-wide association studies (GWAS) have identified 140 Crohn's disease (CD) susceptibility loci. For most loci, the variants that cause disease are not known and the genes affected by these variants have not been identified. We aimed to identify variants that cause CD through...... detailed sequencing, genetic association, expression, and functional studies. METHODS: We sequenced whole exomes of 42 unrelated subjects with CD and 5 healthy subjects (controls) and then filtered single nucleotide variants by incorporating association results from meta-analyses of CD GWAS and in silico...... mutation effect prediction algorithms. We then genotyped 9348 subjects with CD, 2868 subjects with ulcerative colitis, and 14,567 control subjects and associated variants analyzed in functional studies using materials from subjects and controls and in vitro model systems. RESULTS: We identified rare...

Using quantitative breath sound measurements to predict lung function following resection

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Keus Leendert

2010-10-01

Full Text Available Abstract Background Predicting postoperative lung function is important for estimating the risk of complications and long-term disability after pulmonary resection. We investigated the capability of vibration response imaging (VRI as an alternative to lung scintigraphy for prediction of postoperative lung function in patients with intrathoracic malignancies. Methods Eighty-five patients with intrathoracic malignancies, considered candidates for lung resection, were prospectively studied. The projected postoperative (ppo lung function was calculated using: perfusion scintigraphy, ventilation scintigraphy, and VRI. Two sets of assessments made: one for lobectomy and one for pneumonectomy. Clinical concordance was defined as both methods agreeing that either a patient was or was not a surgical candidate based on a ppoFEV1% and ppoDLCO% > 40%. Results Limits of agreement between scintigraphy and VRI for ppo following lobectomy were -16.47% to 15.08% (mean difference = -0.70%;95%CI = -2.51% to 1.12% and for pneumonectomy were -23.79% to 19.04% (mean difference = -2.38%;95%CI = -4.69% to -0.07%. Clinical concordance between VRI and scintigraphy was 73% for pneumonectomy and 98% for lobectomy. For patients who had surgery and postoperative lung function testing (n = 31, ppoFEV1% using scintigraphic methods correlated with measured postoperative values better than projections using VRI, (adjusted R2 = 0.32 scintigraphy; 0.20 VRI, however the difference between methods failed to reach statistical significance. Limits of agreement between measured FEV1% postoperatively and ppoFEV1% based on perfusion scintigraphy were -16.86% to 23.73% (mean difference = 3.44%;95%CI = -0.29% to 7.16%; based on VRI were -19.56% to 28.99% (mean difference = 4.72%;95%CI = 0.27% to 9.17%. Conclusions Further investigation of VRI as an alternative to lung scintigraphy for prediction of postoperative lung function is warranted.

Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

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Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

2018-05-22

To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

Similar patterns of neural activity predict memory function during encoding and retrieval.

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Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

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

International Nuclear Information System (INIS)

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

2013-01-01

Purpose: 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. Methods: 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. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl 2 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

Are economic recessions at the time of leaving school associated with worse physical functioning in later life?

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Hessel, Philipp; Avendano, Mauricio

2013-11-01

To examine whether economic conditions at the time of leaving school or college are associated with physical functioning in later life among cohorts in 11 European countries. Data came from 10,338 participants in the Survey of Health, Ageing and Retirement in Europe (SHARE) aged 50-74 who left school or college between 1956 and 1986. Data on functional limitations, as well as employment, marriage, and fertility retrospective histories were linked to national unemployment rates during the year individuals left school. Models included country-fixed effects and controls for early-life circumstances. Greater unemployment rates during the school-leaving year were associated with fewer functional limitations at ages 50-74 among men (rate ratio 0.63, 95% confidence interval 0.47-0.83), but more physical functioning limitations among women (rate ratio 1.30, 95% confidence interval 1.13-1.50), particularly among those with (post-)secondary education. Economic conditions at the age of leaving school were associated with several labor market, marriage, fertility, and health behavior outcomes, but controlling for these factors did not attenuate associations. Results were similar in models that controlled for selection into higher education due to measured covariates. Worse economic conditions during the school-leaving year predicted better health at later life among men but worse health among women. Both selection and causation mechanisms may explain this association. Copyright © 2013 Elsevier Inc. All rights reserved.

In-depth performance evaluation of PFP and ESG sequence-based function prediction methods in CAFA 2011 experiment

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Chitale Meghana

2013-02-01

Full Text Available Abstract Background Many Automatic Function Prediction (AFP methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the development of AFP methods, it is essential to have community wide experiments for evaluating performance of existing AFP methods. Critical Assessment of Function Annotation (CAFA is one such community experiment. The meeting of CAFA was held as a Special Interest Group (SIG meeting at the Intelligent Systems in Molecular Biology (ISMB conference in 2011. Here, we perform a detailed analysis of two sequence-based function prediction methods, PFP and ESG, which were developed in our lab, using the predictions submitted to CAFA. Results We evaluate PFP and ESG using four different measures in comparison with BLAST, Prior, and GOtcha. In addition to the predictions submitted to CAFA, we further investigate performance of a different scoring function to rank order predictions by PFP as well as PFP/ESG predictions enriched with Priors that simply adds frequently occurring Gene Ontology terms as a part of predictions. Prediction accuracies of each method were also evaluated separately for different functional categories. Successful and unsuccessful predictions by PFP and ESG are also discussed in comparison with BLAST. Conclusion The in-depth analysis discussed here will complement the overall assessment by the CAFA organizers. Since PFP and ESG are based on sequence database search results, our analyses are not only useful for PFP and ESG users but will also shed light on the relationship of the sequence similarity space and functions that can be inferred from the sequences.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

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Jian Ou

2017-03-01

Full Text Available The extensive applications of multi-function radars (MFRs have presented a great challenge to the technologies of radar countermeasures (RCMs and electronic intelligence (ELINT. The recently proposed cognitive electronic warfare (CEW provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR. With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

Sexual abuse predicts functional somatic symptoms : An adolescent population study

NARCIS (Netherlands)

Bonvanie, Irma J.; van Gils, Anne; Janssens, Karin A. M.; Rosmalen, Judith G. M.

The main aim of this study was to investigate the effect of childhood sexual abuse on medically not well explained or functional somatic symptoms (FSSs) in adolescents. We hypothesized that sexual abuse predicts higher levels of FSSs and that anxiety and depression contribute to this relationship.

Ecological prediction with nonlinear multivariate time-frequency functional data models

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Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

2013-01-01

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities

International Nuclear Information System (INIS)

Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

2016-01-01

Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM_1_0) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM_1_0-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM_1_0-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM_1_0 concentration and green space per capita could best explain the heterogeneity in PM_1_0-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. - Highlights: • The heterogeneity was examined in PM_1_0-mortality associations among Chinese cities. • Temperature, PM_1_0 and green space could best explain the heterogeneity. • PM_1_0-mortality associations were predicted for 73 Chinese cities. - This study provides a practical way to assess exposure-response associations and evaluate the burden of mortality in areas with insufficient data.

Which method of posttraumatic stress disorder classification best predicts psychosocial function in children with traumatic brain injury?

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Iselin, Greg; Le Brocque, Robyne; Kenardy, Justin; Anderson, Vicki; McKinlay, Lynne

2010-10-01

Controversy surrounds the classification of posttraumatic stress disorder (PTSD), particularly in children and adolescents with traumatic brain injury (TBI). In these populations, it is difficult to differentiate TBI-related organic memory loss from dissociative amnesia. Several alternative PTSD classification algorithms have been proposed for use with children. This paper investigates DSM-IV-TR and alternative PTSD classification algorithms, including and excluding the dissociative amnesia item, in terms of their ability to predict psychosocial function following pediatric TBI. A sample of 184 children aged 6-14 years were recruited following emergency department presentation and/or hospital admission for TBI. PTSD was assessed via semi-structured clinical interview (CAPS-CA) with the child at 3 months post-injury. Psychosocial function was assessed using the parent report CHQ-PF50. Two alternative classification algorithms, the PTSD-AA and 2 of 3 algorithms, reached statistical significance. While the inclusion of the dissociative amnesia item increased prevalence rates across algorithms, it generally resulted in weaker associations with psychosocial function. The PTSD-AA algorithm appears to have the strongest association with psychosocial function following TBI in children and adolescents. Removing the dissociative amnesia item from the diagnostic algorithm generally results in improved validity. Copyright 2010 Elsevier Ltd. All rights reserved.

Functional networks in parallel with cortical development associate with executive functions in children.

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Zhong, Jidan; Rifkin-Graboi, Anne; Ta, Anh Tuan; Yap, Kar Lai; Chuang, Kai-Hsiang; Meaney, Michael J; Qiu, Anqi

2014-07-01

Children begin performing similarly to adults on tasks requiring executive functions in late childhood, a transition that is probably due to neuroanatomical fine-tuning processes, including myelination and synaptic pruning. In parallel to such structural changes in neuroanatomical organization, development of functional organization may also be associated with cognitive behaviors in children. We examined 6- to 10-year-old children's cortical thickness, functional organization, and cognitive performance. We used structural magnetic resonance imaging (MRI) to identify areas with cortical thinning, resting-state fMRI to identify functional organization in parallel to cortical development, and working memory/response inhibition tasks to assess executive functioning. We found that neuroanatomical changes in the form of cortical thinning spread over bilateral frontal, parietal, and occipital regions. These regions were engaged in 3 functional networks: sensorimotor and auditory, executive control, and default mode network. Furthermore, we found that working memory and response inhibition only associated with regional functional connectivity, but not topological organization (i.e., local and global efficiency of information transfer) of these functional networks. Interestingly, functional connections associated with "bottom-up" as opposed to "top-down" processing were more clearly related to children's performance on working memory and response inhibition, implying an important role for brain systems involved in late childhood. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Measurement of lung volume by lung perfusion scanning using SPECT and prediction of postoperative respiratory function

International Nuclear Information System (INIS)

Andou, Akio; Shimizu, Nobuyosi; Maruyama, Shuichiro

1992-01-01

Measurement of lung volume by lung perfusion scanning using single photon emission computed tomography (SPECT) and its usefulness for the prediction of respiratory function after lung resection were investigated. The lung volumes calculated in 5 patients by SPECT (threshold level 20%) using 99m Tc-macroaggregated albumin (MAA), related very closely to the actually measured lung volumes. This results prompted us to calculate the total lung volume and the volume of the lobe to be resected in 18 patients with lung cancer by SPECT. Based on the data obtained, postoperative respiratory function was predicted. The predicted values of forced vital capacity (FVC), forced expiratory volume (FEV 1.0 ), and maximum vital volume (MVV) showed closer correlations with the actually measured postoperative values (FVC, FEV 1.0 , MVV : r=0.944, r=0.917, r=0.795 respectively), than the values predicted by the ordinary lung perfusion scanning. This method facilitates more detailed evaluation of local lung function on a lobe-by-lobe basis, and can be applied clinically to predict postoperative respiratory function. (author)

Stroke-induced immunodepression and dysphagia independently predict stroke-associated pneumonia - The PREDICT study.

Science.gov (United States)

Hoffmann, Sarah; Harms, Hendrik; Ulm, Lena; Nabavi, Darius G; Mackert, Bruno-Marcel; Schmehl, Ingo; Jungehulsing, Gerhard J; Montaner, Joan; Bustamante, Alejandro; Hermans, Marcella; Hamilton, Frank; Göhler, Jos; Malzahn, Uwe; Malsch, Carolin; Heuschmann, Peter U; Meisel, Christian; Meisel, Andreas

2017-12-01

Stroke-associated pneumonia is a frequent complication after stroke associated with poor outcome. Dysphagia is a known risk factor for stroke-associated pneumonia but accumulating evidence suggests that stroke induces an immunodepressive state increasing susceptibility for stroke-associated pneumonia. We aimed to confirm that stroke-induced immunodepression syndrome is associated with stroke-associated pneumonia independently from dysphagia by investigating the predictive properties of monocytic HLA-DR expression as a marker of immunodepression as well as biomarkers for inflammation (interleukin-6) and infection (lipopolysaccharide-binding protein). This was a prospective, multicenter study with 11 study sites in Germany and Spain, including 486 patients with acute ischemic stroke. Daily screening for stroke-associated pneumonia, dysphagia and biomarkers was performed. Frequency of stroke-associated pneumonia was 5.2%. Dysphagia and decreased monocytic HLA-DR were independent predictors for stroke-associated pneumonia in multivariable regression analysis. Proportion of pneumonia ranged between 0.9% in the higher monocytic HLA-DR quartile (≥21,876 mAb/cell) and 8.5% in the lower quartile (≤12,369 mAb/cell). In the presence of dysphagia, proportion of pneumonia increased to 5.9% and 18.8%, respectively. Patients without dysphagia and normal monocytic HLA-DR expression had no stroke-associated pneumonia risk. We demonstrate that dysphagia and stroke-induced immunodepression syndrome are independent risk factors for stroke-associated pneumonia. Screening for immunodepression and dysphagia might be useful for identifying patients at high risk for stroke-associated pneumonia.

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

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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.

A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data

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Ruzzo Walter L

2006-03-01

Full Text Available Abstract Background As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. Methods In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. Results We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly. Conclusion Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

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Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Predicting the functions and specificity of triterpenoid synthases: a mechanism-based multi-intermediate docking approach.

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Bo-Xue Tian

2014-10-01

Full Text Available Terpenoid synthases construct the carbon skeletons of tens of thousands of natural products. To predict functions and specificity of triterpenoid synthases, a mechanism-based, multi-intermediate docking approach is proposed. In addition to enzyme function prediction, other potential applications of the current approach, such as enzyme mechanistic studies and enzyme redesign by mutagenesis, are discussed.

Predictions of Actions and Their Justifications in False-Belief Tasks: The Role of Executive Function

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Putko Adam

2014-12-01

Full Text Available The main objective of this study was to examine whether children’s ability to justify their action predictions in terms of mental states is related, in a similar way as the ability to predict actions, to such aspects of executive function (EF as executive control and working memory. An additional objective was to check whether the frequency of different types of justifications made by children in false-belief tasks is associated with aforementioned aspects of EF, as well as language. The study included 59 children aged 3-4 years. The ability to predict actions and to justify these predictions was measured with false-belief tasks. Luria’s hand-game was used to assess executive control, and the Counting and Labelling dual-task was used to assess working memory capacity. Language development was controlled using an embedded syntax test. It was found that executive control was a significant predictor of the children’s ability to justify their action predictions in terms of mental states, even when age and language were taken into account. Results also indicated a relationship between the type of justification in the false-belief task and language development. With the development of language children gradually cease to justify their action predictions in terms of current location, and they tend to construct irrelevant justifications before they begin to refer to beliefs. Data suggest that executive control, in contrast to language, is a factor which affects the development of the children’s ability to justify their action predictions only in its later phase, during a shift from irrelevant to correct justifications.

Prediction of Declining Renal Function and Albuminuria in Patients With Type 2 Diabetes by Metabolomics.

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Solini, Anna; Manca, Maria Laura; Penno, Giuseppe; Pugliese, Giuseppe; Cobb, Jeff E; Ferrannini, Ele

2016-02-01

Renal disease in type 2 diabetes mellitus (T2DM) is associated with excess morbidity/mortality. Although estimated glomerular filtration rate (eGFR) and albuminuria are routine for assessing renal impairment, novel biomarkers could improve risk stratification and prediction. To identify specific biomarkers of progression of renal dysfunction. Prospective observational. Academic diabetes clinics. A total of 286 T2DM patients (age, 62 ± 8 y; glycosylated hemoglobin, 7.2 ± 0.9%; eGFR, 85 ± 20 mL · min(-1) · 1.73 m(2)). None. Progression of eGFR and albuminuria. We performed screening metabolomics in serum and urine samples by gas chromatography/mass spectroscopy (MS) and ultra-high performance liquid chromatography/MS/MS. Biomarker identification was performed by random forest using an eGFR cutoff of fasting glucose, and baseline eGFR) predicted outcome, with receiver operator characteristics curve (ROC) = 0.671. The five serum metabolites best correlated with either eGFR < 60 or ACR ≥ 30 at baseline were tested for their ability to improve clinical prediction. The sum of C-glycosyl tryptophan, pseudouridine, and N-acetylthreonine (MetIndex) raised the ROC to 0.739 (P < .0001). eGFR decline was predicted by the top MetIndex quartile (odds ratio = 5.48 [95% confidence interval, 2.23-14.47]). MetIndex also predicted an ACR increase with an odds ratio of 2.82 [1.20-7.03] and a ROC of 0.750. Top urine metabolites did not add significant predictivity. A limited number of circulating intermediates of amino acid and nucleotide pathways carry clinically significant predictivity for deterioration of renal function in well-controlled T2DM.

Associations among arbuscular mycorrhizal fungi and seedlings are predicted to change with tree successional status.

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Bachelot, Benedicte; Uriarte, María; Muscarella, Robert; Forero-Montaña, Jimena; Thompson, Jill; McGuire, Krista; Zimmerman, Jess; Swenson, Nathan G; Clark, James S

2018-03-01

Arbuscular mycorrhizal (AM) fungi in the soil may influence tropical tree dynamics and forest succession. The mechanisms are poorly understood, because the functional characteristics and abundances of tree species and AM fungi are likely to be codependent. We used generalized joint attribute modeling to evaluate if AM fungi are associated with three forest community metrics for a sub-tropical montane forest in Puerto Rico. The metrics chosen to reflect changes during forest succession are the abundance of seedlings of different successional status, the amount of foliar damage on seedlings of different successional status, and community-weighted mean functional trait values (adult specific leaf area [SLA], adult wood density, and seed mass). We used high-throughput DNA sequencing to identify fungal operational taxonomic units (OTUs) in the soil. Model predictions showed that seedlings of mid- and late-successional species had less leaf damage when the 12 most common AM fungi were abundant compared to when these fungi were absent. We also found that seedlings of mid-successional species were predicted to be more abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. In contrast, early-successional tree seedlings were predicted to be less abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. Finally, we showed that, among the 12 most common AM fungi, different AM fungi were correlated with functional trait characteristics of early- or late-successional species. Together, these results suggest that early-successional species might not rely as much as mid- and late-successional species on AM fungi, and AM fungi might accelerate forest succession. © 2017 by the Ecological Society of America.

Associations between executive functioning, coping, and psychosocial functioning after acquired brain injury.

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Wolters Gregório, Gisela; Ponds, Rudolf W H M; Smeets, Sanne M J; Jonker, Frank; Pouwels, Climmy G J G; Verhey, Frans R; van Heugten, Caroline M

2015-09-01

To examine the relationships between executive functioning, coping, depressive symptoms, and quality of life in individuals with neuropsychiatric symptoms after acquired brain injury (ABI). Cross-sectional study. Individuals (n = 93) in the post-acute and chronic phase (>3 months) after ABI and their significant others (N = 58) were recruited from outpatient clinics of four mental health centres in the Netherlands. Outcome measures were the Trail Making Test, Stroop Colour Word Test, Frontal Systems Behavioural Scale, Utrecht Coping List, Patient Health Questionnaire, and Life Satisfaction Questionnaire. Data were analysed with multiple regression analyses. Self-reported executive dysfunction was associated with greater use of passive coping styles (β = .37, p executive functioning (β = -.94, p executive functioning tests were not associated with coping, depressive symptoms, or quality of life. For clinicians, these data indicate that individuals who report greater difficulties with executive functioning after ABI are inclined to use maladaptive passive coping styles, which should be targeted in treatment. In comparison, individuals who report greater difficulties with executive functioning should not be prompted to use problem-focused coping styles. These individuals may benefit from other coping styles, such as the use of seeking social support or acceptance of problems. Coping influences the association between executive functioning and quality of life. Individuals who report difficulties with executive functioning after ABI may be inclined to use passive coping styles, which are maladaptive. Problem-focused coping strategies may be more useful for individuals who have strong executive abilities. This study was a cross-sectional study; thus, a cause-and-effect relationship could not be established between executive functioning, coping, and psychosocial functioning. As this research was part of standard clinical care, non-traditional tests for executive

Do causal concentration-response functions exist? A critical review of associational and causal relations between fine particulate matter and mortality.

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Cox, Louis Anthony Tony

2017-08-01

Concentration-response (C-R) functions relating concentrations of pollutants in ambient air to mortality risks or other adverse health effects provide the basis for many public health risk assessments, benefits estimates for clean air regulations, and recommendations for revisions to existing air quality standards. The assumption that C-R functions relating levels of exposure and levels of response estimated from historical data usefully predict how future changes in concentrations would change risks has seldom been carefully tested. This paper critically reviews literature on C-R functions for fine particulate matter (PM2.5) and mortality risks. We find that most of them describe historical associations rather than valid causal models for predicting effects of interventions that change concentrations. The few papers that explicitly attempt to model causality rely on unverified modeling assumptions, casting doubt on their predictions about effects of interventions. A large literature on modern causal inference algorithms for observational data has been little used in C-R modeling. Applying these methods to publicly available data from Boston and the South Coast Air Quality Management District around Los Angeles shows that C-R functions estimated for one do not hold for the other. Changes in month-specific PM2.5 concentrations from one year to the next do not help to predict corresponding changes in average elderly mortality rates in either location. Thus, the assumption that estimated C-R relations predict effects of pollution-reducing interventions may not be true. Better causal modeling methods are needed to better predict how reducing air pollution would affect public health.

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices.

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Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

2015-02-22

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Prediction of the residual strength of clay using functional networks

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S.Z. Khan

2016-01-01

Full Text Available Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks (FN using data available in the literature. The performance of FN was compared with support vector machine (SVM and artificial neural network (ANN based on statistical parameters like correlation coefficient (R, Nash--Sutcliff coefficient of efficiency (E, absolute average error (AAE, maximum average error (MAE and root mean square error (RMSE. Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output.

Executive functioning independently predicts self-rated health and improvement in self-rated health over time among community-dwelling older adults.

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McHugh, Joanna Edel; Lawlor, Brian A

2016-01-01

Self-rated health, as distinct from objective measures of health, is a clinically informative metric among older adults. The purpose of our study was to examine the cognitive and psychosocial factors associated with self-rated health. 624 participants over the age of 60 were assessed at baseline, and of these, 510 were contacted for a follow-up two years later. Measures of executive function and self-rated health were assessed at baseline, and self-rated health was assessed at follow-up. We employed multiple linear regression analyses to investigate the relationship between executive functioning and self-rated health, while controlling for demographic, psychosocial and biological variables. Controlling for other relevant variables, executive functioning independently and solely predicted self-rated health, both at a cross-sectional level, and also over time. Loneliness was also found to cross-sectionally predict self-rated health, although this relationship was not present at a longitudinal level. Older adults' self-rated health may be related to their executive functioning and to their loneliness. Self-rated health appeared to improve over time, and the extent of this improvement was also related to executive functioning at baseline. Self-rated health may be a judgement made of one's functioning, especially executive functioning, which changes with age and therefore may be particularly salient in the reflections of older adults.

Upset Prediction in Friction Welding Using Radial Basis Function Neural Network

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Wei Liu

2013-01-01

Full Text Available This paper addresses the upset prediction problem of friction welded joints. Based on finite element simulations of inertia friction welding (IFW, a radial basis function (RBF neural network was developed initially to predict the final upset for a number of welding parameters. The predicted joint upset by the RBF neural network was compared to validated finite element simulations, producing an error of less than 8.16% which is reasonable. Furthermore, the effects of initial rotational speed and axial pressure on the upset were investigated in relation to energy conversion with the RBF neural network. The developed RBF neural network was also applied to linear friction welding (LFW and continuous drive friction welding (CDFW. The correlation coefficients of RBF prediction for LFW and CDFW were 0.963 and 0.998, respectively, which further suggest that an RBF neural network is an effective method for upset prediction of friction welded joints.

The role of neurocognition and social context in predicting community functioning among formerly homeless seriously mentally ill persons.

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Schutt, Russell K; Seidman, Larry J; Caplan, Brina; Martsinkiv, Anna; Goldfinger, Stephen M

2007-11-01

To test the influence of neurocognitive functioning on community functioning among formerly homeless persons with serious mental illness and to determine whether that influence varies with social context, independent of individual characteristics. In metropolitan Boston, 112 persons in Department of Mental Health shelters were administered a neuropsychological test battery and other measures and then randomly assigned to empowerment-oriented group homes or independent apartments, as part of a longitudinal study of the effects of housing on multiple outcomes. Subjects' case managers completed Rosen's 5-dimensional Life Skills Inventory at 3, 6, 12, and 18 months and subjects reported on their social contacts at baseline, 6, 12, and 18 months. Subject characteristics are controlled in the analysis. Three dimensions of neurocognitive functioning--executive function, verbal declarative memory, and vigilance--each predicted community functioning. Better executive function predicted improved self-care and less turbulent behavior among persons living alone, better memory predicted more positive social contacts for those living in a group home, and higher levels of vigilance predicted improved communication in both housing types. Neurocognition predicts community functioning among homeless persons with severe mental illness, but in a way that varies with the social context in which community functioning occurs.

Association of plasma angiotensin-(1-7 level and left ventricular function in patients with type 2 diabetes mellitus.

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Pan-Pan Hao

Full Text Available We recently found that overexpression of angiotensin (Ang-converting enzyme 2, which metabolizes Ang-II to Ang-(1-7 and Ang-I to Ang-(1-9, may prevent diabetes-induced left ventricular remodeling and dysfunction in rats. Our objective was to evaluate the association of plasma Ang-(1-7 level and left ventricular function in patients with type 2 diabetes mellitus.We measured the left ventricular ejection fraction (EF, ratio of early to late left ventricular filling velocity (E/A and ratio of early diastolic mitral inflow to annular velocity (E/Ea by ultrasonography in 110 patients with type 2 diabetes mellitus for more than 5 years. Anthropometric and fasting blood values were obtained from medical records. The plasma Ang-(1-7 level in patients with a poor EF (15 was significantly lower than that in patients with E/Ea ≤15. Ang-(1-7 level was negatively correlated with E/Ea and Log-N-terminal pro-B-type natriuretic peptide and positively with EF and E/A. Stepwise multiple regression analysis revealed that Ang-(1-7, hemoglobin A1c and Ang-II levels as well as duration of diabetes predicted EF; Ang-(1-7 level, fasting blood glucose, low-density lipoprotein cholesterol level and duration of diabetes predicted E/A; and Ang-(1-7 and hemoglobin A1c levels predicted E/Ea.Plasma Ang-(1-7 level is independently associated with left ventricular function in patients with type 2 diabetes mellitus and may be a biomarker for assessing cardiac function in such patients.

Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information.

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Tang, Zaixiang; Shen, Yueping; Li, Yan; Zhang, Xinyan; Wen, Jia; Qian, Chen'ao; Zhuang, Wenzhuo; Shi, Xinghua; Yi, Nengjun

2018-03-15

Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). nyi@uab.edu. Supplementary data are available at Bioinformatics online.

Prediction of rat behavior outcomes in memory tasks using functional connections among neurons.

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Hu Lu

Full Text Available BACKGROUND: Analyzing the neuronal organizational structures and studying the changes in the behavior of the organism is key to understanding cognitive functions of the brain. Although some studies have indicated that spatiotemporal firing patterns of neuronal populations have a certain relationship with the behavioral responses, the issues of whether there are any relationships between the functional networks comprised of these cortical neurons and behavioral tasks and whether it is possible to take advantage of these networks to predict correct and incorrect outcomes of single trials of animals are still unresolved. METHODOLOGY/PRINCIPAL FINDINGS: This paper presents a new method of analyzing the structures of whole-recorded neuronal functional networks (WNFNs and local neuronal circuit groups (LNCGs. The activity of these neurons was recorded in several rats. The rats performed two different behavioral tasks, the Y-maze task and the U-maze task. Using the results of the assessment of the WNFNs and LNCGs, this paper describes a realization procedure for predicting the behavioral outcomes of single trials. The methodology consists of four main parts: construction of WNFNs from recorded neuronal spike trains, partitioning the WNFNs into the optimal LNCGs using social community analysis, unsupervised clustering of all trials from each dataset into two different clusters, and predicting the behavioral outcomes of single trials. The results show that WNFNs and LNCGs correlate with the behavior of the animal. The U-maze datasets show higher accuracy for unsupervised clustering results than those from the Y-maze task, and these datasets can be used to predict behavioral responses effectively. CONCLUSIONS/SIGNIFICANCE: The results of the present study suggest that a methodology proposed in this paper is suitable for analysis of the characteristics of neuronal functional networks and the prediction of rat behavior. These types of structures in cortical

The association between substantiated childhood maltreatment, asthma and lung function: A prospective investigation.

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Abajobir, Amanuel Alemu; Kisely, Steve; Williams, Gail; Strathearn, Lane; Suresh, Sadasivam; Najman, Jake Moses

2017-10-01

Asthma reflects multiple and likely complex causal pathways. We investigate the possibility that childhood maltreatment is one such causal pathway. Childhood maltreatment can be interpreted as a form of early life adversity and like other life adversities may predict a range of negative health outcomes, including asthma. A total of 3762 young adults (52.63% female) from the Mater Hospital-University of Queensland Study of Pregnancy (MUSP) participated in this study. MUSP is a prospective Australian birth cohort study of mothers consecutively recruited during their first antenatal clinic visit at Brisbane's Mater Hospital from 1981 to 1983. The study followed both mother-child dyads to the age of 21years after birth. Participants reported whether they had been diagnosed by a physician with asthma by the 21-year follow-up. Trained research assistants also performed gender- and height-standardized lung function tests using a Spirobank G spirometer system attached to a laptop computer. We linked this dataset with data obtained from the child protection services and which comprised all substantiated cases of childhood maltreatment in the MUSP cohort. Substantiations of childhood maltreatment included children in an age range of 0-14years. The experience of any childhood maltreatment, particularly emotional abuse, was independently associated with self-reported physician-diagnosed asthma by the 21-year follow-up. The association was no longer significant after adjustment for a range of confounders and covariates in neglected children. Childhood maltreatment, including multiple events, was not associated with lung function in adjusted models. Childhood maltreatment, including emotional abuse, was associated with lifetime ever asthma. This was in contrast to the absence of an association with objective measures of lung function. More research is indicated on the effect of childhood maltreatment on lung function using objective measures. In the meantime, there should be a

Inferring the Functions of Proteins from the Interrelationships between Functional Categories.

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Taha, Kamal

2018-01-01

This study proposes a new method to determine the functions of an unannotated protein. The proteins and amino acid residues mentioned in biomedical texts associated with an unannotated protein can be considered as characteristics terms for , which are highly predictive of the potential functions of . Similarly, proteins and amino acid residues mentioned in biomedical texts associated with proteins annotated with a functional category can be considered as characteristics terms of . We introduce in this paper an information extraction system called IFP_IFC that predicts the functions of an unannotated protein by representing and each functional category by a vector of weights. Each weight reflects the degree of association between a characteristic term and (or a characteristic term and ). First, IFP_IFC constructs a network, whose nodes represent the different functional categories, and its edges the interrelationships between the nodes. Then, it determines the functions of by employing random walks with restarts on the mentioned network. The walker is the vector of . Finally, is assigned to the functional categories of the nodes in the network that are visited most by the walker. We evaluated the quality of IFP_IFC by comparing it experimentally with two other systems. Results showed marked improvement.

An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome.

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

2017-10-06

Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.

Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities.

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Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

2016-01-01

Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reveal genes functionally associated with ACADS by a network study.

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Chen, Yulong; Su, Zhiguang

2015-09-15

Establishing a systematic network is aimed at finding essential human gene-gene/gene-disease pathway by means of network inter-connecting patterns and functional annotation analysis. In the present study, we have analyzed functional gene interactions of short-chain acyl-coenzyme A dehydrogenase gene (ACADS). ACADS plays a vital role in free fatty acid β-oxidation and regulates energy homeostasis. Modules of highly inter-connected genes in disease-specific ACADS network are derived by integrating gene function and protein interaction data. Among the 8 genes in ACADS web retrieved from both STRING and GeneMANIA, ACADS is effectively conjoined with 4 genes including HAHDA, HADHB, ECHS1 and ACAT1. The functional analysis is done via ontological briefing and candidate disease identification. We observed that the highly efficient-interlinked genes connected with ACADS are HAHDA, HADHB, ECHS1 and ACAT1. Interestingly, the ontological aspect of genes in the ACADS network reveals that ACADS, HAHDA and HADHB play equally vital roles in fatty acid metabolism. The gene ACAT1 together with ACADS indulges in ketone metabolism. Our computational gene web analysis also predicts potential candidate disease recognition, thus indicating the involvement of ACADS, HAHDA, HADHB, ECHS1 and ACAT1 not only with lipid metabolism but also with infant death syndrome, skeletal myopathy, acute hepatic encephalopathy, Reye-like syndrome, episodic ketosis, and metabolic acidosis. The current study presents a comprehensible layout of ACADS network, its functional strategies and candidate disease approach associated with ACADS network. Copyright © 2015 Elsevier B.V. All rights reserved.

Improved fuzzy PID controller design using predictive functional control structure.

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Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

2017-11-01

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.