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Sample records for predicts functional association

  1. Functional association prediction by community profiling.

    PubMed

    Jiao, Dazhi; Han, Wontack; Ye, Yuzhen

    2017-04-26

    Recent years have witnessed unprecedented accumulation of DNA sequences and therefore protein sequences (predicted from DNA sequences), due to the advances of sequencing technology. One of the major sources of the hypothetical proteins is the metagenomics research. Current annotation of metagenomes (collections of short metagenomic sequences or assemblies) relies on similarity searches against known gene/protein families, based on which functional profiles of microbial communities can be built. This practice, however, leaves out the hypothetical proteins, which may outnumber the known proteins for many microbial communities. On the other hand, we may ask: what can we gain from the large number of metagenomes made available by the metagenomic studies, for the annotation of metagenomic sequences as well as functional annotation of hypothetical proteins in general? Here we propose a community profiling approach for predicting functional associations between proteins: two proteins are predicted to be associated if they share similar presence and absence profiles (called community profiles) across microbial communities. Community profiling is conceptually similar to the phylogenetic profiling approach to functional prediction, however with fundamental differences. We tested different profile construction methods, the selection of reference metagenomes, and correlation metrics, among others, to optimize the performance of this new approach. We demonstrated that the community profiling approach alone slightly outperforms the phylogenetic profiling approach for associating proteins in species that are well represented by sequenced genomes, and combining phylogenetic and community profiling further improves (though only marginally) the prediction of functional association. Further we showed that community profiling method significantly outperforms phylogenetic profiling, revealing more functional associations, when applied to a more recently sequenced bacterial genome

  2. STRING: a database of predicted functional associations between proteins.

    PubMed

    von Mering, Christian; Huynen, Martijn; Jaeggi, Daniel; Schmidt, Steffen; Bork, Peer; Snel, Berend

    2003-01-01

    Functional links between proteins can often be inferred from genomic associations between the genes that encode them: groups of genes that are required for the same function tend to show similar species coverage, are often located in close proximity on the genome (in prokaryotes), and tend to be involved in gene-fusion events. The database STRING is a precomputed global resource for the exploration and analysis of these associations. Since the three types of evidence differ conceptually, and the number of predicted interactions is very large, it is essential to be able to assess and compare the significance of individual predictions. Thus, STRING contains a unique scoring-framework based on benchmarks of the different types of associations against a common reference set, integrated in a single confidence score per prediction. The graphical representation of the network of inferred, weighted protein interactions provides a high-level view of functional linkage, facilitating the analysis of modularity in biological processes. STRING is updated continuously, and currently contains 261 033 orthologs in 89 fully sequenced genomes. The database predicts functional interactions at an expected level of accuracy of at least 80% for more than half of the genes; it is online at http://www.bork.embl-heidelberg.de/STRING/.

  3. Protein function prediction using guilty by association from interaction networks.

    PubMed

    Piovesan, Damiano; Giollo, Manuel; Ferrari, Carlo; Tosatto, Silvio C E

    2015-12-01

    Protein function prediction from sequence using the Gene Ontology (GO) classification is useful in many biological problems. It has recently attracted increasing interest, thanks in part to the Critical Assessment of Function Annotation (CAFA) challenge. In this paper, we introduce Guilty by Association on STRING (GAS), a tool to predict protein function exploiting protein-protein interaction networks without sequence similarity. The assumption is that whenever a protein interacts with other proteins, it is part of the same biological process and located in the same cellular compartment. GAS retrieves interaction partners of a query protein from the STRING database and measures enrichment of the associated functional annotations to generate a sorted list of putative functions. A performance evaluation based on CAFA metrics and a fair comparison with optimized BLAST similarity searches is provided. The consensus of GAS and BLAST is shown to improve overall performance. The PPI approach is shown to outperform similarity searches for biological process and cellular compartment GO predictions. Moreover, an analysis of the best practices to exploit protein-protein interaction networks is also provided.

  4. Predicting protein function by frequent functional association pattern mining in protein interaction networks.

    PubMed

    Cho, Young-Rae; Zhang, Aidong

    2010-01-01

    Predicting protein function from protein interaction networks has been challenging because of the complexity of functional relationships among proteins. Most previous function prediction methods depend on the neighborhood of or the connected paths to known proteins. However, their accuracy has been limited due to the functional inconsistency of interacting proteins. In this paper, we propose a novel approach for function prediction by identifying frequent patterns of functional associations in a protein interaction network. A set of functions that a protein performs is assigned into the corresponding node as a label. A functional association pattern is then represented as a labeled subgraph. Our frequent labeled subgraph mining algorithm efficiently searches the functional association patterns that occur frequently in the network. It iteratively increases the size of frequent patterns by one node at a time by selective joining, and simplifies the network by a priori pruning. Using the yeast protein interaction network, our algorithm found more than 1400 frequent functional association patterns. The function prediction is performed by matching the subgraph, including the unknown protein, with the frequent patterns analogous to it. By leave-one-out cross validation, we show that our approach has better performance than previous link-based methods in terms of prediction accuracy. The frequent functional association patterns generated in this study might become the foundations of advanced analysis for functional behaviors of proteins in a system level.

  5. Communication abnormalities predict functional outcomes in chronic schizophrenia: differential associations with social and adaptive functions.

    PubMed

    Bowie, Christopher R; Harvey, Philip D

    2008-08-01

    Communication abnormalities are hallmark features of schizophrenia. Despite the prevalence and persistence of these symptoms, little is known about their functional implications. In this study, we examined, in a sample of chronically institutionalized schizophrenia patients (N=317), whether two types of communication abnormalities (i.e., verbal underproductivity and disconnected speech) had differential relationships with social and adaptive outcomes. Baseline ratings of verbal underproductivity, disconnected speech, global cognitive performance, and clinical symptoms, were entered into stepwise regression analyses to examine their relationship with 2.5 year social and adaptive outcomes. At baseline, disconnected speech was significantly associated with socially impolite behavior, while verbal underproductivity was associated with social disengagement and impaired friendships. Both types of communication abnormalities were significantly associated with other types of social skills. Verbal underproductivity predicted follow-up social skills, social engagement, and friendships, accounting for more variance than. cognition or symptoms. In contrast to social outcomes, adaptive outcomes were predicted by baseline neurocognition and clinical symptoms, but not communication abnormalities. These findings provide evidence for specific relationships of communication disorder subtypes with diverse impairments in social functions. In this chronically institutionalized sample, communication disorder was a stronger predictor of social, but not adaptive, outcomes than neurocognition or clinical symptoms.

  6. Communication Abnormalities Predict Functional Outcomes in Chronic Schizophrenia: Differential Associations with Social and Adaptive Functions

    PubMed Central

    Bowie, Christopher R.; Harvey, Philip D.

    2014-01-01

    Communication abnormalities are hallmark features of schizophrenia. Despite the prevalence and persistence of these symptoms, little is known about their functional implications. In this study, we examined, in a sample of chronically institutionalized schizophrenia patients (N=317), whether two types of communication abnormalities (i.e., verbal underproductivity and disconnected speech) had differential relationships with social and adaptive outcomes. Baseline ratings of verbal underproductivity, disconnected speech, global cognitive performance, and clinical symptoms, were entered into stepwise regression analyses to examine their relationship with 2.5 year social and adaptive outcomes. At baseline, disconnected speech was significantly associated with socially impolite behavior, while verbal underproductivity was associated with social disengagement and impaired friendships. Both types of communication abnormalities were significantly associated with other types of social skills. Verbal underproductivity predicted follow-up social skills, social engagement, and friendships, accounting for more variance than cognition or symptoms. In contrast to social outcomes, adaptive outcomes were predicted by baseline neurocognition and clinical symptoms, but not communication abnormalities. These findings provide evidence for specific relationships of communication disorder subtypes with diverse impairments in social functions. In this chronically institutionalized sample, communication disorder was a stronger predictor of social, but not adaptive, outcomes than neurocognition or clinical symptoms. PMID:18571378

  7. Biological interpretation of genome-wide association studies using predicted gene functions.

    PubMed

    Pers, Tune H; Karjalainen, Juha M; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R; Yang, Jian; Lui, Julian C; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S N; Hirschhorn, Joel N; Franke, Lude

    2015-01-19

    The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

  8. Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

    ERIC Educational Resources Information Center

    Marshall, Seth

    2016-01-01

    More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

  9. Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

    ERIC Educational Resources Information Center

    Marshall, Seth

    2016-01-01

    More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

  10. Integrated protein function prediction by mining function associations, sequences, and protein-protein and gene-gene interaction networks.

    PubMed

    Cao, Renzhi; Cheng, Jianlin

    2016-01-15

    Protein function prediction is an important and challenging problem in bioinformatics and computational biology. Functionally relevant biological information such as protein sequences, gene expression, and protein-protein interactions has been used mostly separately for protein function prediction. One of the major challenges is how to effectively integrate multiple sources of both traditional and new information such as spatial gene-gene interaction networks generated from chromosomal conformation data together to improve protein function prediction. In this work, we developed three different probabilistic scores (MIS, SEQ, and NET score) to combine protein sequence, function associations, and protein-protein interaction and spatial gene-gene interaction networks for protein function prediction. The MIS score is mainly generated from homologous proteins found by PSI-BLAST search, and also association rules between Gene Ontology terms, which are learned by mining the Swiss-Prot database. The SEQ score is generated from protein sequences. The NET score is generated from protein-protein interaction and spatial gene-gene interaction networks. These three scores were combined in a new Statistical Multiple Integrative Scoring System (SMISS) to predict protein function. We tested SMISS on the data set of 2011 Critical Assessment of Function Annotation (CAFA). The method performed substantially better than three base-line methods and an advanced method based on protein profile-sequence comparison, profile-profile comparison, and domain co-occurrence networks according to the maximum F-measure. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Predicting functional associations from metabolism using bi-partite network algorithms.

    PubMed

    Veeramani, Balaji; Bader, Joel S

    2010-07-14

    Metabolic reconstructions contain detailed information about metabolic enzymes and their reactants and products. These networks can be used to infer functional associations between metabolic enzymes. Many methods are based on the number of metabolites shared by two enzymes, or the shortest path between two enzymes. Metabolite sharing can miss associations between non-consecutive enzymes in a serial pathway, and shortest-path algorithms are sensitive to high-degree metabolites such as water and ATP that create connections between enzymes with little functional similarity. We present new, fast methods to infer functional associations in metabolic networks. A local method, the degree-corrected Poisson score, is based only on the metabolites shared by two enzymes, but uses the known metabolite degree distribution. A global method, based on graph diffusion kernels, predicts associations between enzymes that do not share metabolites. Both methods are robust to high-degree metabolites. They out-perform previous methods in predicting shared Gene Ontology (GO) annotations and in predicting experimentally observed synthetic lethal genetic interactions. Including cellular compartment information improves GO annotation predictions but degrades synthetic lethal interaction prediction. These new methods perform nearly as well as computationally demanding methods based on flux balance analysis. We present fast, accurate methods to predict functional associations from metabolic networks. Biological significance is demonstrated by identifying enzymes whose strong metabolic correlations are missed by conventional annotations in GO, most often enzymes involved in transport vs. synthesis of the same metabolite or other enzyme pairs that share a metabolite but are separated by conventional pathway boundaries. More generally, the methods described here may be valuable for analyzing other types of networks with long-tailed degree distributions and high-degree hubs.

  12. Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

    PubMed Central

    2011-01-01

    Background Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network. PMID:21486441

  13. IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association.

    PubMed

    Peguero-Sanchez, Esteban; Pardo-Lopez, Liliana; Merino, Enrique

    2015-12-15

    The initiation of translation via cellular internal ribosome entry sites plays an important role in the stress response and certain physiological conditions in which canonical cap-dependent translation initiation is compromised. Currently, only a limited number of these regulatory elements have been experimentally identified. Notably, cellular internal ribosome entry sites lack conservation of both the primary sequence and mRNA secondary structure, rendering their identification difficult. Despite their biological importance, the currently available computational strategies to predict them have had limited success. We developed a bioinformatic method based on a support vector machine for the prediction of internal ribosome entry sites in fungi using the 5'-UTR sequences of 20 non-redundant fungal organisms. Additionally, we performed a comparative analysis and characterization of the functional relationships among the gene products predicted to be translated by this cap-independent mechanism. Using our method, we predicted 6,532 internal ribosome entry sites in 20 non-redundant fungal organisms. Some orthologous groups were enriched with our positive predictions. This is the case of the HSP70 chaperone family, which remarkably has two verified internal ribosome entry sites, one in humans and the other in flies. A second example is the orthologous group of the eIF4G repression protein Sbp1p, which has two homologous genes known to be translated by this cap-independent mechanism, one in mice and the other in yeast. These examples emphasize the wide conservation of these regulatory elements as a result of selective pressure. In addition, we performed a protein-protein interaction network characterization of the gene products of our positive predictions using Saccharomyces cerevisiae as a model, which revealed a highly connected and modular topology, suggesting a functional association. A remarkable example of this functional association is our prediction of internal

  14. Plasma neutrophil gelatinase-associated lipocalin in kidney transplantation and early renal function prediction.

    PubMed

    Bataille, Aurélien; Abbas, Samia; Semoun, Oren; Bourgeois, Éric; Marie, Olivier; Bonnet, Francine; Resche-Rigon, Matthieu; Abboud, Imad; Losser, Marie-Reine; Jacob, Laurent

    2011-11-15

    This prospective observational study aimed to assess the relevance of serial postoperative plasma neutrophil gelatinase-associated lipocalin (NGAL) measurements on prediction of early renal transplant function. Plasma NGAL (pNGAL) was measured (Triage NGAL Test; Biosite Inc., Inverness Medical) in 41 patients scheduled for kidney transplantation from deceased or living donors, immediately before and after surgery, and at 12 hr, day 1, day 3, and day 7. A delayed graft function (DGF) was defined as the need for dialysis during the first week. The results were expressed as median (Q1, Q3). Of the 41 consecutive patients enrolled, all had a high preoperative pNGAL level: 453 ng/mL (382, 595). Fifteen (36.6%) presented a DGF. In patients with DGF, pNGAL was significantly higher at 12 hr (571 [467, 634] vs. 242 [158, 299] ng/mL, P<0.0001) and at day 1 (466 [356, 627] vs. 165 [91, 248] ng/mL, P<0.0001). A pNGAL higher than 400 ng/mL 12 hr after transplantation predicted DGF with a sensitivity of 93.3%, a specificity of 88.5%, and an odds ratio of 63.2 (P=0.0004). This predictive performance was higher than for plasma creatinine. pNGAL level early and accurately predicted DGF after renal transplantation. pNGAL measurements allowed monitoring of the renal function in this striking situation of ischemia-reperfusion aggression. Early identification of patients at risk of DGF, before graft lesions are consolidated, opens the field of a precise monitoring of renal injury and the impact of future protective therapeutics.

  15. Associative Encoding and Retrieval Are Predicted by Functional Connectivity in Distinct Hippocampal Area CA1 Pathways

    PubMed Central

    Duncan, Katherine; Tompary, Alexa

    2014-01-01

    Determining how the hippocampus supports the unique demands of memory encoding and retrieval is fundamental for understanding the biological basis of episodic memory. One possibility proposed by theoretical models is that the distinct computational demands of encoding and retrieval are accommodated by shifts in the functional interaction between the hippocampal CA1 subregion and its input structures. However, empirical tests of this hypothesis are lacking. To test this in humans, we used high-resolution fMRI to measure functional connectivity between hippocampal area CA1 and regions of the medial temporal lobe and midbrain during extended blocks of associative encoding and retrieval tasks. We found evidence for a double dissociation between the pathways supporting successful encoding and retrieval. Specifically, during the associative encoding task, but not the retrieval task, functional connectivity only between area CA1 and the ventral tegmental area predicted associative long-term memory. In contrast, connectivity between area CA1 and DG/CA3 was greater, on average, during the retrieval task compared with the encoding task, and, importantly, the strength of this connectivity significantly correlated with retrieval success. Together, these findings serve as an important first step toward understanding how the demands of fundamental memory processes may be met by changes in the relative strength of connectivity within hippocampal pathways. PMID:25143600

  16. Riparian Processes Associated with Buffer Edges and Longitudinal Channel Variation and Implications for Predicting Functional Response

    NASA Astrophysics Data System (ADS)

    Liquori, M. K.

    2001-12-01

    Managing riparian zones to provide aquatic ecosystem functions has become a fundamental component of forest stewardship. Yet, two key areas have received little attention: a) variations associated with buffers as compared to forests and b) variations associated with longitudinal geomorphic processes. In this discussion, I borrow from several available datasets to challenge some widely held misperceptions of riparian buffer function in these areas. We often seek to inform riparian management through our understanding of native forests. Yet, few studies fully recognize that ecological and geomorphic behavior in buffered systems can be quite different than in fully forested conditions. A comparison of large woody debris recruitment processes suggests that recruitment patterns shift away from the channel under buffered conditions, likely in response to changes in the dominant tree recruitment process associated with buffer edges. While tree fall rates vary by species and recruitment process, tree fall directions follow a strong non-random preference toward a perpendicular orientation to the channel in both buffered and forested conditions. These shifts in recruitment process may result in large long-term shifts in available riparian function in response to changing stand growth trajectories. In low-order forested channels, pool depth ceases to be a function of large woody debris diameter, shear stress relationships are reversed, and total wood loading is a fraction of that observed in mid-order channels (3rd-5th order). These types of important longitudinal differences have yet to be incorporated widely in forest riparian management. Site-based riparian zone designs that recognize that step-pool channels process wood, water, nutrients and sediment far different than pool-riffle, plane-bed or cascade channels is a key step toward a capacity to predict impacts to channeled environments.

  17. ARE EXECUTIVE FUNCTIONING DEFICITS CONCURRENTLY AND PREDICTIVELY ASSOCIATED WITH DEPRESSIVE AND ANXIETY SYMPTOMS IN ADOLESCENTS?

    PubMed Central

    Han, Georges; Helm, Jonathan; Iucha, Cornelia; Zahn-Waxler, Carolyn; Hastings, Paul D.; Klimes-Dougan, Bonnie

    2015-01-01

    Background The central objective of the current study was to evaluate how executive functions (EF), and specifically cognitive flexibility, were concurrently and predictively associated with anxiety and depressive symptoms in adolescence. Method Adolescents (N = 220) and their parents participated in this longitudinal investigation. Adolescents’ EF was assessed by the Wisconsin Card Sorting Test (WCST) during the initial assessment, and symptoms of depressive and anxiety disorders were reported by mothers and youths concurrently and two years later. Results Correlational analyses suggested that youths who made more total errors (TE), including both perseverative errors (PE) and non-perseverative errors (NPE), concurrently exhibited significantly more depressive symptoms. Adolescents who made more TE and those who made more NPE tended to have more anxiety symptoms two years later. SEM analyses accounting for key explanatory variables (e.g., IQ, disruptive behavior disorders, and attention deficit hyperactive disorder) showed that TE was concurrently associated with parent reports of adolescent depressive symptoms. Discussion The results suggest internalizing psychopathology is associated with global (TE) and nonspecific (NPE) EF difficulties, but not robustly associated with cognitive inflexibility (PE). Future research with the WCST should consider different sources of errors which are posited to reflect divergent underlying neural mechanisms, conferring differential vulnerability for emerging mental health problems. PMID:26042358

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

    PubMed

    Cleary, Daniel F R; Becking, Leontine E; Polónia, Ana R M; Freitas, Rossana M; Gomes, Newton C M

    2015-03-01

    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 composition and function. Marine lakes are small landlocked bodies of seawater isolated to varying degrees from the open sea environment. They contain numerous endemic taxa and represent natural laboratories of speciation. Our primary goals were to (1) use BLAST search to identify closely related organisms to dominant bacterial OTUs in our mussel dataset and (2) to compare bacterial communities and enrichment in the predicted bacterial metagenome among lakes. Our sequencing effort yielded 3553 OTUs belonging to 44 phyla, 99 classes and 121 orders. Mussels in the largest marine lake (Kakaban) and the coastal mangrove habitat were dominated by bacteria belonging to the phylum Proteobacteria whereas smaller lakes, located on the island of Maratua, were dominated by bacteria belonging to the phyla Firmicutes and Tenericutes. The single most abundant OTU overall was assigned to the genus Mycoplasma. There were several significant differences among locations with respect to metabolic pathways. These included enrichment of xenobiotic biodegradation pathways in the largest marine lake and coastal mangrove. These locations were also the most enriched with respect to nitrogen metabolism. The presence of genes related to isoquinoline alkaloids, polyketides, hydrolases, mono and dioxygenases in the predicted analysis of functional pathways is an indication that the bacterial communities of Brachidontes mussels may be potentially important sources of new marine medicines and enzymes of industrial interest. Future work should focus on measuring how mussel microbial communities influence nutrient dynamics within the marine lake environment and isolating microbes with potential biotechnological

  19. Identification and functional prediction of mitochondrial complex III and IV mutations associated with glioblastoma

    PubMed Central

    Lloyd, Rhiannon E.; Keatley, Kathleen; Littlewood, D. Timothy J.; Meunier, Brigitte; Holt, William V.; An, Qian; Higgins, Samantha C.; Polyzoidis, Stavros; Stephenson, Katie F.; Ashkan, Keyoumars; Fillmore, Helen L.; Pilkington, Geoffrey J.; McGeehan, John E.

    2015-01-01

    Background Glioblastoma (GBM) is the most common primary brain tumor in adults, with a dismal prognosis. Treatment is hampered by GBM's unique biology, including differential cell response to therapy. Although several mitochondrial abnormalities have been identified, how mitochondrial DNA (mtDNA) mutations contribute to GBM biology and therapeutic response remains poorly described. We sought to determine the spectrum of functional complex III and IV mtDNA mutations in GBM. Methods The complete mitochondrial genomes of 10 GBM cell lines were obtained using next-generation sequencing and combined with another set obtained from 32 GBM tissues. Three-dimensional structural mapping and analysis of all the nonsynonymous mutations identified in complex III and IV proteins was then performed to investigate functional importance. Results Over 200 mutations were identified in the mtDNAs, including a significant proportion with very low mutational loads. Twenty-five were nonsynonymous mutations in complex III and IV, 9 of which were predicted to be functional and affect mitochondrial respiratory chain activity. Most of the functional candidates were GBM specific and not found in the general population, and 2 were present in the germ-line. Patient-specific maps reveal that 43% of tumors carry at least one functional candidate. Conclusions We reveal that the spectrum of GBM-associated mtDNA mutations is wider than previously thought, as well as novel structural-functional links between specific mtDNA mutations, abnormal mitochondria, and the biology of GBM. These results could provide tangible new prognostic indicators as well as targets with which to guide the development of patient-specific mitochondrially mediated chemotherapeutic approaches. PMID:25731774

  20. Predicting the functional consequences of cancer-associated amino acid substitutions

    PubMed Central

    Shihab, Hashem A.; Gough, Julian; Cooper, David N.; Day, Ian N. M.; Gaunt, Tom R.

    2013-01-01

    Motivation: The number of missense mutations being identified in cancer genomes has greatly increased as a consequence of technological advances and the reduced cost of whole-genome/whole-exome sequencing methods. However, a high proportion of the amino acid substitutions detected in cancer genomes have little or no effect on tumour progression (passenger mutations). Therefore, accurate automated methods capable of discriminating between driver (cancer-promoting) and passenger mutations are becoming increasingly important. In our previous work, we developed the Functional Analysis through Hidden Markov Models (FATHMM) software and, using a model weighted for inherited disease mutations, observed improved performances over alternative computational prediction algorithms. Here, we describe an adaptation of our original algorithm that incorporates a cancer-specific model to potentiate the functional analysis of driver mutations. Results: The performance of our algorithm was evaluated using two separate benchmarks. In our analysis, we observed improved performances when distinguishing between driver mutations and other germ line variants (both disease-causing and putatively neutral mutations). In addition, when discriminating between somatic driver and passenger mutations, we observed performances comparable with the leading computational prediction algorithms: SPF-Cancer and TransFIC. Availability and implementation: A web-based implementation of our cancer-specific model, including a downloadable stand-alone package, is available at http://fathmm.biocompute.org.uk. Contact: fathmm@biocompute.org.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23620363

  1. New York Heart Association functional class predicts exercise parameters in the current era.

    PubMed

    Russell, Stuart D; Saval, Matthew A; Robbins, Jennifer L; Ellestad, Myrvin H; Gottlieb, Stephen S; Handberg, Eileen M; Zhou, Yi; Chandler, Bleakley

    2009-10-01

    The New York Heart Association (NYHA) functional class is a subjective estimate of a patient's functional ability based on symptoms that do not always correlate with the objective estimate of functional capacity, peak oxygen consumption (peak V(O2)). In addition, relationships between these 2 measurements have not been examined in the current medical era when patients are using beta-blockers, aldosterone antagonists, and cardiac resynchronization therapy (CRT). Using baseline data from the HF-ACTION (Heart Failure and A Controlled Trial Investigating Outcomes of Exercise TraiNing) study, we examined this relationship. One thousand seven hundred fifty-eight patients underwent a symptom-limited metabolic stress test and stopped exercise due to dyspnea or fatigue. The relationship between NYHA functional class and peak V(O2) was examined. In addition, the effects of beta-blockers, aldosterone antagonists, and CRT therapy on these relationships were compared. The NYHA II patients have a significantly higher peak Vo(2) (16.1 +/- 4.6 vs 13.0 +/- 4.2 mL/kg per minute), a lower ventilation (Ve)/V(CO2) slope (32.8 +/- 7.7 vs 36.8 +/- 10.4), and a longer duration of exercise (11.0 +/- 3.9 vs 8.0 +/- 3.4 minutes) than NYHA III/IV patients. Within each functional class, there was no difference in any of the exercise parameters between patients on or off of beta-blockers, aldosterone antagonists, or CRT therapy. Finally, with increasing age, a significant difference in peak Vo(2), Ve/V(CO2) slope, and exercise time was found. For patients being treated with current medical therapy, there still is a difference in true functional capacity between NYHA functional class II and III/IV patients. However, within each NYHA functional class, the presence or absence or contemporary heart failure therapies does not alter exercise parameters.

  2. Predicting Social Functioning in Schizotypy

    PubMed Central

    McCleery, Amanda; Divilbiss, Marielle; St-Hilaire, Annie; Aakre, Jennifer M.; Seghers, James P.; Bell, Emily K.; Docherty, Nancy M.

    2015-01-01

    Theory of mind (ToM) is an aspect of social cognition that refers to the ability to make inferences about the thoughts, feelings, and intentions of other people. It is believed to be related to social functioning. Previous investigations of ToM in schizotypy have yielded mixed results. Using a correlational approach, the present study explored the relationship between schizotypal traits, ToM, neurocognition, depressed mood, and social functioning in a sample of 50 undergraduate students. Schizotypy was related to poor social functioning. Contrary to predictions, schizotypal traits were not associated with impaired ToM. In fact, schizotypal traits were associated with enhanced performance on a ToM task that involved detection of ironic statements. However, strong relationships emerged among schizotypy, depressed mood, and social functioning, highlighting the need to also examine depression when assessing the relations between elevated schizotypy and poor social functioning. PMID:22297312

  3. Short-Term Pulmonary Function Trends Are Predictive of Mortality in Interstitial Lung Disease Associated With Systemic Sclerosis.

    PubMed

    Goh, Nicole S; Hoyles, Rachel K; Denton, Christopher P; Hansell, David M; Renzoni, Elisabetta A; Maher, Toby M; Nicholson, Andrew G; Wells, Athol U

    2017-08-01

    To determine the prognostic value of pulmonary function test (PFT) trends at 1 and 2 years in interstitial lung disease (ILD) associated with systemic sclerosis (SSc). The prognostic significance of PFT trends at 1 year (n = 162) and 2 years (n = 140) was examined against 15-year survival in patients with SSc-associated ILD. PFT trends, expressed as continuous change and as categorical change in separate analyses, were examined against mortality in univariate and multivariate models. SSc-associated ILD was defined at presentation as either limited lung fibrosis or extensive lung fibrosis, using the United Kingdom Raynaud's and Scleroderma Association severity staging system. One-year PFT trends were predictive of mortality only in patients with extensive lung fibrosis: categorical change in the forced vital capacity (FVC), alone or in combination with categorical change in the diffusing capacity for carbon monoxide (DLco), had greater prognostic significance than continuous change in the FVC or trends in other PFT variables. Taking into account both prognostic value and sensitivity to change, the optimal definition of progression for trial purposes was an FVC and DLco composite end point, consisting of either an FVC decline from baseline of ≥10% or an FVC decline of 5-9% in association with a DLco decline of ≥15%. At 2 years, gas transfer trends had the greatest prognostic significance, in the whole cohort and in those with limited lung fibrosis. However, in patients with extensive lung fibrosis, the above-defined FVC and DLco composite end point was the strongest prognostic determinant. Larger changes in the FVC:DLco ratio than in the carbon monoxide transfer coefficient were required to achieve prognostic significance. Based on linkages to long-term outcomes, these findings provide support for use of routine spirometry and gas transfer monitoring in patients with SSc-associated ILD, with further evaluation of a composite FVC and DLco end point

  4. Serum neutrophil gelatinase associated lipocalin during the early postoperative period predicts the recovery of graft function after kidney transplantation from donors after cardiac death.

    PubMed

    Kusaka, Mamoru; Iwamatsu, Fumi; Kuroyanagi, Yoko; Nakaya, Miho; Ichino, Manabu; Marubashi, Shigeru; Nagano, Hiroaki; Shiroki, Ryoichi; Kurahashi, Hiroki; Hoshinaga, Kiyotaka

    2012-06-01

    Kidneys procured from donors after cardiac death hold great potential to expand the donor pool. However, they have not yet been fully used, in part due to the high incidence of delayed graft function. Although urine neutrophil gelatinase-associated lipocalin is a well-known early biomarker for renal injury after kidney transplantation, its usefulness is limited in cases with delayed graft function because of the unavailability of a urine sample. We evaluated serum neutrophil gelatinase-associated lipocalin as a potential biomarker to predict the functional recovery of kidneys transplanted from donors after cardiac death. Consecutive patients transplanted with a kidney from a living related (39), brain dead (1) or post-cardiac death (27) donor were retrospectively enrolled in the study. Serum samples were collected serially before and after kidney transplantation. Serum neutrophil gelatinase-associated lipocalin was measured using the ARCHITECT® assay. Average serum neutrophil gelatinase-associated lipocalin was markedly high during the pre transplantation period. It decreased rapidly after transplantation. The slope of the decrease correlated well with the recovery period. By analyzing ROC curves we determined cutoffs to predict immediate, slow or delayed graft function requiring hemodialysis for longer than 1 week with high sensitivity and specificity. These data suggest that serial monitoring of serum neutrophil gelatinase-associated lipocalin may allow us to predict graft recovery and the need for hemodialysis after kidney transplantation from a donor after cardiac death. Copyright © 2012 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  5. Locating overlapping dense subgraphs in gene (protein) association networks and predicting novel protein functional groups among these subgraphs

    NASA Astrophysics Data System (ADS)

    Palla, Gergely; Derenyi, Imre; Farkas, Illes J.; Vicsek, Tamas

    2006-03-01

    Most tasks in a cell are performed not by individual proteins, but by functional groups of proteins (either physically interacting with each other or associated in other ways). In gene (protein) association networks these groups show up as sets of densely connected nodes. In the yeast, Saccharomyces cerevisiae, known physically interacting groups of proteins (called protein complexes) strongly overlap: the total number of proteins contained by these complexes by far underestimates the sum of their sizes (2750 vs. 8932). Thus, most functional groups of proteins, both physically interacting and other, are likely to share many of their members with other groups. However, current algorithms searching for dense groups of nodes in networks usually exclude overlaps. With the aim to discover both novel functions of individual proteins and novel protein functional groups we combine in protein association networks (i) a search for overlapping dense subgraphs based on the Clique Percolation Method (CPM) (Palla, G., et.al. Nature 435, 814-818 (2005), http://angel.elte.hu/clustering), which explicitly allows for overlaps among the groups, and (ii) a verification and characterization of the identified groups of nodes (proteins) with the help of standard annotation databases listing known functions.

  6. Within and between population variation in plant traits predicts ecosystem functions associated with a dominant plant species

    PubMed Central

    Breza, Lauren C; Souza, Lara; Sanders, Nathan J; Classen, Aimée T

    2012-01-01

    Linking intraspecific variation in plant traits to ecosystem carbon uptake may allow us to better predict how shift in populations shape ecosystem function. We investigated whether plant populations of a dominant old-field plant species (Solidago altissima) differed in carbon dynamics and if variation in plant traits among genotypes and between populations predicted carbon dynamics. We established a common garden experiment with 35 genotypes from three populations of S. altissima from either Tennessee (southern populations) or Connecticut (northern populations) to ask whether: (1) southern and northern Solidago populations will differ in aboveground productivity, leaf area, flowering time and duration, and whole ecosystem carbon uptake, (2) intraspecific trait variation (growth and reproduction) will be related to intraspecific variation in gross ecosystem CO2 exchange (GEE) and net ecosystem CO2 exchange (NEE) within and between northern and southern populations. GEE and NEE were 4.8× and 2× greater in southern relative to northern populations. Moreover, southern populations produced 13× more aboveground biomass and 1.4× more inflorescence mass than did northern populations. Flowering dynamics (first- and last-day flowering and flowering duration) varied significantly among genotypes in both the southern and northern populations, but plant performance and ecosystem function did not. Both productivity and inflorescence mass predicted NEE and GEE between S. altissima southern and northern populations. Taken together, our data demonstrate that variation between S. altissima populations in performance and flowering traits are strong predictors of ecosystem function in a dominant old-field species and suggest that populations of the same species might differ substantially in their response to environmental perturbations. PMID:22833791

  7. Protein Function Prediction: Problems and Pitfalls.

    PubMed

    Pearson, William R

    2015-09-03

    The characterization of new genomes based on their protein sets has been revolutionized by new sequencing technologies, but biologists seeking to exploit new sequence information are often frustrated by the challenges associated with accurately assigning biological functions to newly identified proteins. Here, we highlight some of the challenges in functional inference from sequence similarity. Investigators can improve the accuracy of function prediction by (1) being conservative about the evolutionary distance to a protein of known function; (2) considering the ambiguous meaning of "functional similarity," and (3) being aware of the limitations of annotations in functional databases. Protein function prediction does not offer "one-size-fits-all" solutions. Prediction strategies work better when the idiosyncrasies of function and functional annotation are better understood.

  8. Prediction of optimal gene functions for osteosarcoma using network-based- guilt by association method based on gene oncology and microarray profile.

    PubMed

    Chen, Xinrang

    2017-06-01

    In the current study, we planned to predict the optimal gene functions for osteosarcoma (OS) by integrating network-based method with guilt by association (GBA) principle (called as network-based gene function inference approach) based on gene oncology (GO) data and gene expression profile. To begin with, differentially expressed genes (DEGs) were extracted using linear models for microarray data (LIMMA) package. Then, construction of differential co-expression network (DCN) relying on DEGs was implemented, and sub-DCN was identified using Spearman correlation coefficient (SCC). Subsequently, GO annotations for OS were collected according to known confirmed database and DEGs. Ultimately, gene functions were predicted by means of GBA principle based on the area under the curve (AUC) for GO terms, and we determined GO terms with AUC >0.7 as the optimal gene functions for OS. Totally, 123 DEGs and 137 GO terms were obtained for further analysis. A DCN was constructed, which included 123 DEGs and 7503 interactions. A total of 105 GO terms were identified when the threshold was set as AUC >0.5, which had a good classification performance. Among these 105 GO terms, 2 functions had the AUC >0.7 and were determined as the optimal gene functions including angiogenesis (AUC =0.767) and regulation of immune system process (AUC =0.710). These gene functions appear to have potential for early detection and clinical treatment of OS in the future.

  9. Plasma neutrophil gelatinase-associated lipocalin as a marker for the prediction of worsening renal function in children hospitalized for acute heart failure.

    PubMed

    Elsharawy, Sahar; Raslan, Lila; Morsy, Saed; Hassan, Basheir; Khalifa, Naglaa

    2016-01-01

    Acute heart failure (AHF) is frequently associated with worsening renal function in adult patients. Neutrophil gelatinase-associated lipocalin (NGAL) serves as an early marker for acute renal tubular injury. To assess the role of plasma NGAL in predicting worsening renal function (WRF) in children with AHF, we studied 30 children hospitalized for AHF; children with history of chronic renal disease or on nephrotoxic drugs were excluded. Twenty age- and sex-matched healthy children were included in the study as a control group. Echocardiographic examination was performed on admission. Blood urea nitrogen (BUN), serum creatinine, estimated glomerular filtration rate (eGFR) and plasma NGAL levels were measured on admission and 72 h later. Seventeen (56.6%) patients developed WRF within the three-day follow-up period. At presentation, plasma NGAL level was significantly elevated in children who developed WRF. Admission plasma NGAL level correlated with renal parameters (BUN, creatinine and eGFR) as well as with left ventricular systolic parameters (ejection fraction and fractional shortening). For prediction of WRF, admission plasma, NGAL level>27.5 μg/L had sensitivity and specificity of 90% and 68%, respectively. The area under the receiver-operator curve was higher for NGAL (0.869) than for BUN (0.569) or eGFR (0.684). We conclude that admission plasma NGAL level can predict WRF in children hospitalized for AHF.

  10. Genetic Ancestry in Lung-Function Predictions

    PubMed Central

    Kumar, Rajesh; Seibold, Max A.; Aldrich, Melinda C.; Williams, L. Keoki; Reiner, Alex P.; Colangelo, Laura; Galanter, Joshua; Gignoux, Christopher; Hu, Donglei; Sen, Saunak; Choudhry, Shweta; Peterson, Edward L.; Rodriguez-Santana, Jose; Rodriguez-Cintron, William; Nalls, Michael A.; Leak, Tennille S.; O’Meara, Ellen; Meibohm, Bernd; Kritchevsky, Stephen B.; Li, Rongling; Harris, Tamara B.; Nickerson, Deborah A.; Fornage, Myriam; Enright, Paul; Ziv, Elad; Smith, Lewis J.; Liu, Kiang; Burchard, Esteban González

    2010-01-01

    BACKGROUND Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. METHODS We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. RESULTS African ancestry was inversely related to forced expiratory volume in 1 second (FEV1) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV1) in 4 to 5% of participants. CONCLUSIONS Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National

  11. Predicting disease associations via biological network analysis.

    PubMed

    Sun, Kai; Gonçalves, Joana P; Larminie, Chris; Przulj, Nataša

    2014-09-17

    Understanding the relationship between diseases based on the underlying biological mechanisms is one of the greatest challenges in modern biology and medicine. Exploring disease-disease associations by using system-level biological data is expected to improve our current knowledge of disease relationships, which may lead to further improvements in disease diagnosis, prognosis and treatment. We took advantage of diverse biological data including disease-gene associations and a large-scale molecular network to gain novel insights into disease relationships. We analysed and compared four publicly available disease-gene association datasets, then applied three disease similarity measures, namely annotation-based measure, function-based measure and topology-based measure, to estimate the similarity scores between diseases. We systematically evaluated disease associations obtained by these measures against a statistical measure of comorbidity which was derived from a large number of medical patient records. Our results show that the correlation between our similarity measures and comorbidity scores is substantially higher than expected at random, confirming that our similarity measures are able to recover comorbidity associations. We also demonstrated that our predicted disease associations correlated with disease associations generated from genome-wide association studies significantly higher than expected at random. Furthermore, we evaluated our predicted disease associations via mining the literature on PubMed, and presented case studies to demonstrate how these novel disease associations can be used to enhance our current knowledge of disease relationships. We present three similarity measures for predicting disease associations. The strong correlation between our predictions and known disease associations demonstrates the ability of our measures to provide novel insights into disease relationships.

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

    PubMed

    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.

  13. Predicting Musculoskeletal Injury in National Collegiate Athletic Association Division II Athletes From Asymmetries and Individual-Test Versus Composite Functional Movement Screen Scores

    PubMed Central

    Mokha, Monique; Sprague, Peter A.; Gatens, Dustin R.

    2016-01-01

    Context:  Functional Movement Screen (FMS) scores of ≤14 have been used to predict injury in athletic populations. Movement asymmetries and poor-quality movement patterns in other functional tests have been shown to predict musculoskeletal injury (MSI). Therefore, movement asymmetry or poor-quality movement patterns on the FMS may have more utility in predicting MSI than the composite score. Objective:  To determine if an asymmetry or score of 1 on an individual FMS test would predict MSI in collegiate athletes. Design:  Cohort study. Setting:  National Collegiate Athletic Association Division II university athletic program. Patients or Other Participants:  A total of 84 Division II rowers, volleyball players, and soccer players (men: n = 20, age = 20.4 ± 1.3 years, height = 1.77 ± 0.04 m, mass = 73.5 ± 4.8 kg; women: n = 64, age = 19.1 ± 1.2 years, height = 1.69 ± 0.09 m, mass = 64.8 ± 9.4 kg). Main Outcome Measure(s):  The FMS was administered during preseason preparticipation examinations. Injury-incidence data were tracked for an academic year by each team's certified athletic trainer via computer software. An MSI was defined as physical damage to the body secondary to athletic activity or an event for which the athlete sought medical care, and resulted in modified training or required protective splitting or taping. Composite FMS scores were categorized as low (≤14) or high (>14). Pearson χ2 analyses were used to determine if MSI could be predicted by the composite FMS score or an asymmetry or score of 1 on an individual FMS test (P < .05). Results:  Athletes with FMS scores of ≤14 were not more likely to sustain an injury than those with higher scores (relative risk = 0.68, 95% confidence interval = 0.39, 1.19; P = .15). However, athletes with an asymmetry or individual score of 1 were 2.73 times more likely to sustain an injury than those without (relative risk = 2.73, 95% confidence interval = 1.36, 5.4; P = .001). Conclusions

  14. Predicting Musculoskeletal Injury in National Collegiate Athletic Association Division II Athletes From Asymmetries and Individual-Test Versus Composite Functional Movement Screen Scores.

    PubMed

    Mokha, Monique; Sprague, Peter A; Gatens, Dustin R

    2016-04-01

    Functional Movement Screen (FMS) scores of ≤14 have been used to predict injury in athletic populations. Movement asymmetries and poor-quality movement patterns in other functional tests have been shown to predict musculoskeletal injury (MSI). Therefore, movement asymmetry or poor-quality movement patterns on the FMS may have more utility in predicting MSI than the composite score. To determine if an asymmetry or score of 1 on an individual FMS test would predict MSI in collegiate athletes. Cohort study. National Collegiate Athletic Association Division II university athletic program. A total of 84 Division II rowers, volleyball players, and soccer players (men: n = 20, age = 20.4 ± 1.3 years, height = 1.77 ± 0.04 m, mass = 73.5 ± 4.8 kg; women: n = 64, age = 19.1 ± 1.2 years, height = 1.69 ± 0.09 m, mass = 64.8 ± 9.4 kg). The FMS was administered during preseason preparticipation examinations. Injury-incidence data were tracked for an academic year by each team's certified athletic trainer via computer software. An MSI was defined as physical damage to the body secondary to athletic activity or an event for which the athlete sought medical care, and resulted in modified training or required protective splitting or taping. Composite FMS scores were categorized as low (≤14) or high (>14). Pearson χ(2) analyses were used to determine if MSI could be predicted by the composite FMS score or an asymmetry or score of 1 on an individual FMS test (P < .05). Athletes with FMS scores of ≤14 were not more likely to sustain an injury than those with higher scores (relative risk = 0.68, 95% confidence interval = 0.39, 1.19; P = .15). However, athletes with an asymmetry or individual score of 1 were 2.73 times more likely to sustain an injury than those without (relative risk = 2.73, 95% confidence interval = 1.36, 5.4; P = .001). Asymmetry or a low FMS individual test score was a better predictor of MSI than the composite FMS score.

  15. An iterative approach of protein function prediction

    PubMed Central

    2011-01-01

    Background Current approaches of predicting protein functions from a protein-protein interaction (PPI) dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins) will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins). Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms. Results In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions. Conclusions The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting functions iteratively. The

  16. Prediction of the repeat domain structures and impact of parkinsonism-associated variations on structure and function of all functional domains of leucine-rich repeat kinase 2 (LRRK2).

    PubMed

    Mills, Ryan D; Mulhern, Terrence D; Liu, Fei; Culvenor, Janetta G; Cheng, Heung-Chin

    2014-04-01

    Genetic variations of leucine-rich repeat kinase 2 (LRRK2) are the major cause of dominantly inherited Parkinson disease (PD). LRRK2 protein contains seven predicted domains: a tandem Ras-like GTPase (ROC) domain and C-terminal of Roc (COR) domain, a protein kinase domain, and four repeat domains. PD-causative variations arise in all domains, suggesting that aberrant functioning of any domain can contribute to neurotoxic mechanisms of LRRK2. Determination of the three-dimensional structure of LRRK2 is one of the best avenues to decipher its neurotoxic mechanism. However, with the exception of the Roc domain, the three-dimensional structures of the functional domains of LRRK2 have yet to be determined. Based on the known three-dimensional structures of repeat domains of other proteins, the tandem Roc-COR domains of the Chlorobium tepidum Rab family protein, and the kinase domain of the Dictyostelium discoideum Roco4 protein, we predicted (1) the motifs essential for protein-protein interactions in all domains, (2) the motifs critical for catalysis and substrate recognition in the tandem Roc-COR and kinase domains, and (3) the effects of some PD-associated missense variations on the neurotoxic action of LRRK2. Results of our analysis provide a conceptual framework for future investigation into the regulation and the neurotoxic mechanism of LRRK2.

  17. PREDICTION OF NONLINEAR SPATIAL FUNCTIONALS. (R827257)

    EPA Science Inventory

    Spatial statistical methodology can be useful in the arena of environmental regulation. Some regulatory questions may be addressed by predicting linear functionals of the underlying signal, but other questions may require the prediction of nonlinear functionals of the signal. ...

  18. Ecological transition predictably associated with gene degeneration.

    PubMed

    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.

  19. Hierarchical Ensemble Methods for Protein Function Prediction

    PubMed Central

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

  20. Hierarchical ensemble methods for protein function prediction.

    PubMed

    Valentini, Giorgio

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware "flat" prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a "consensus" ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research.

  1. Interspecies gene function prediction using semantic similarity.

    PubMed

    Yu, Guoxian; Luo, Wei; Fu, Guangyuan; Wang, Jun

    2016-12-23

    Gene Ontology (GO) is a collaborative project that maintains and develops controlled vocabulary (or terms) to describe the molecular function, biological roles and cellular location of gene products in a hierarchical ontology. GO also provides GO annotations that associate genes with GO terms. GO consortium independently and collaboratively annotate terms to gene products, mainly from model organisms (or species) they are interested in. Due to experiment ethics, research interests of biologists and resources limitations, homologous genes from different species currently are annotated with different terms. These differences can be more attributed to incomplete annotations of genes than to functional difference between them. Semantic similarity between genes is derived from GO hierarchy and annotations of genes. It is positively correlated with the similarity derived from various types of biological data and has been applied to predict gene function. In this paper, we investigate whether it is possible to replenish annotations of incompletely annotated genes by using semantic similarity between genes from two species with homology. For this investigation, we utilize three representative semantic similarity metrics to compute similarity between genes from two species. Next, we determine the k nearest neighborhood genes from the two species based on the chosen metric and then use terms annotated to k neighbors of a gene to replenish annotations of that gene. We perform experiments on archived (from Jan-2014 to Jan-2016) GO annotations of four species (Human, Mouse, Danio rerio and Arabidopsis thaliana) to assess the contribution of semantic similarity between genes from different species. The experimental results demonstrate that: (1) semantic similarity between genes from homologous species contributes much more on the improved accuracy (by 53.22%) than genes from single species alone, and genes from two species with low homology; (2) GO annotations of genes from

  2. Predicting network functions with nested patterns

    NASA Astrophysics Data System (ADS)

    Ganter, Mathias; Kaltenbach, Hans-Michael; Stelling, Jörg

    2014-01-01

    Identifying suitable patterns in complex biological interaction networks helps understanding network functions and allows for predictions at the pattern level: by recognizing a known pattern, one can assign its previously established function. However, current approaches fail for previously unseen patterns, when patterns overlap and when they are embedded into a new network context. Here we show how to conceptually extend pattern-based approaches. We define metabolite patterns in metabolic networks that formalize co-occurrences of metabolites. Our probabilistic framework decodes the implicit information in the networks’ metabolite patterns to predict metabolic functions. We demonstrate the predictive power by identifying ‘indicator patterns’, for instance, for enzyme classification, by predicting directions of novel reactions and of known reactions in new network contexts, and by ranking candidate network extensions for gap filling. Beyond their use in improving genome annotations and metabolic network models, we expect that the concepts transfer to other network types.

  3. Structure prediction of magnetosome-associated proteins

    PubMed Central

    Nudelman, Hila; Zarivach, Raz

    2014-01-01

    Magnetotactic bacteria (MTB) are Gram-negative bacteria that can navigate along geomagnetic fields. This ability is a result of a unique intracellular organelle, the magnetosome. These organelles are composed of membrane-enclosed magnetite (Fe3O4) or greigite (Fe3S4) crystals ordered into chains along the cell. Magnetosome formation, assembly, and magnetic nano-crystal biomineralization are controlled by magnetosome-associated proteins (MAPs). Most MAP-encoding genes are located in a conserved genomic region – the magnetosome island (MAI). The MAI appears to be conserved in all MTB that were analyzed so far, although the MAI size and organization differs between species. It was shown that MAI deletion leads to a non-magnetic phenotype, further highlighting its important role in magnetosome formation. Today, about 28 proteins are known to be involved in magnetosome formation, but the structures and functions of most MAPs are unknown. To reveal the structure–function relationship of MAPs we used bioinformatics tools in order to build homology models as a way to understand their possible role in magnetosome formation. Here we present a predicted 3D structural models’ overview for all known Magnetospirillum gryphiswaldense strain MSR-1 MAPs. PMID:24523717

  4. Year 2 Report: Protein Function Prediction Platform

    SciTech Connect

    Zhou, C E

    2012-04-27

    Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

  5. Improved network community structure improves function prediction

    PubMed Central

    Lee, Juyong; Gross, Steven P.; Lee, Jooyoung

    2013-01-01

    We are overwhelmed by experimental data, and need better ways to understand large interaction datasets. While clustering related nodes in such networks—known as community detection—appears a promising approach, detecting such communities is computationally difficult. Further, how to best use such community information has not been determined. Here, within the context of protein function prediction, we address both issues. First, we apply a novel method that generates improved modularity solutions than the current state of the art. Second, we develop a better method to use this community information to predict proteins' functions. We discuss when and why this community information is important. Our results should be useful for two distinct scientific communities: first, those using various cost functions to detect community structure, where our new optimization approach will improve solutions, and second, those working to extract novel functional information about individual nodes from large interaction datasets. PMID:23852097

  6. Resting state functional connectivity predicts neurofeedback response

    PubMed Central

    Scheinost, Dustin; Stoica, Teodora; Wasylink, Suzanne; Gruner, Patricia; Saksa, John; Pittenger, Christopher; Hampson, Michelle

    2014-01-01

    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. PMID:25309375

  7. Protein function prediction based on data fusion and functional interrelationship.

    PubMed

    Meng, Jun; Wekesa, Jael-Sanyanda; Shi, Guan-Li; Luan, Yu-Shi

    2016-04-01

    One of the challenging tasks of bioinformatics is to predict more accurate and confident protein functions from genomics and proteomics datasets. Computational approaches use a variety of high throughput experimental data, such as protein-protein interaction (PPI), protein sequences and phylogenetic profiles, to predict protein functions. This paper presents a method that uses transductive multi-label learning algorithm by integrating multiple data sources for classification. Multiple proteomics datasets are integrated to make inferences about functions of unknown proteins and use a directed bi-relational graph to assign labels to unannotated proteins. Our method, bi-relational graph based transductive multi-label function annotation (Bi-TMF) uses functional correlation and topological PPI network properties on both the training and testing datasets to predict protein functions through data fusion of the individual kernel result. The main purpose of our proposed method is to enhance the performance of classifier integration for protein function prediction algorithms. Experimental results demonstrate the effectiveness and efficiency of Bi-TMF on multi-sources datasets in yeast, human and mouse benchmarks. Bi-TMF outperforms other recently proposed methods.

  8. Prediction of Chemical Function: Model Development and ...

    EPA Pesticide Factsheets

    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

  9. Prediction of Chemical Function: Model Development and ...

    EPA Pesticide Factsheets

    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

  10. Predicting healthcare associated infections using patients' experiences

    NASA Astrophysics Data System (ADS)

    Pratt, Michael A.; Chu, Henry

    2016-05-01

    Healthcare associated infections (HAI) are a major threat to patient safety and are costly to health systems. Our goal is to predict the HAI performance of a hospital using the patients' experience responses as input. We use four classifiers, viz. random forest, naive Bayes, artificial feedforward neural networks, and the support vector machine, to perform the prediction of six types of HAI. The six types include blood stream, urinary tract, surgical site, and intestinal infections. Experiments show that the random forest and support vector machine perform well across the six types of HAI.

  11. Roles for text mining in protein function prediction.

    PubMed

    Verspoor, Karin M

    2014-01-01

    The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

  12. A Survey of Computational Intelligence Techniques in Protein Function Prediction

    PubMed Central

    Tiwari, Arvind Kumar; Srivastava, Rajeev

    2014-01-01

    During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction. PMID:25574395

  13. A survey of computational intelligence techniques in protein function prediction.

    PubMed

    Tiwari, Arvind Kumar; Srivastava, Rajeev

    2014-01-01

    During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction.

  14. Beyond genotype: serotonin transporter epigenetic modification predicts human brain function.

    PubMed

    Nikolova, Yuliya S; Koenen, Karestan C; Galea, Sandro; Wang, Chiou-Miin; Seney, Marianne L; Sibille, Etienne; Williamson, Douglas E; Hariri, Ahmad R

    2014-09-01

    We examined epigenetic regulation in regards to behaviorally and clinically relevant human brain function. Specifically, we found that increased promoter methylation of the serotonin transporter gene predicted increased threat-related amygdala reactivity and decreased mRNA expression in postmortem amygdala tissue. These patterns were independent of functional genetic variation in the same region. Furthermore, the association with amygdala reactivity was replicated in a second cohort and was robust to both sampling methods and age.

  15. Optimizing nondecomposable loss functions in structured prediction.

    PubMed

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N; Li, Ze-Nian; Mori, Greg

    2013-04-01

    We develop an algorithm for structured prediction with nondecomposable performance measures. The algorithm learns parameters of Markov Random Fields (MRFs) and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines), and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a Quadratic Program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset.

  16. Parental education predicts corticostriatal functionality in adulthood.

    PubMed

    Gianaros, Peter J; Manuck, Stephen B; Sheu, Lei K; Kuan, Dora C H; Votruba-Drzal, Elizabeth; Craig, Anna E; Hariri, Ahmad R

    2011-04-01

    Socioeconomic disadvantage experienced in early development predicts ill health in adulthood. However, the neurobiological pathways linking early disadvantage to adult health remain unclear. Lower parental education-a presumptive indicator of early socioeconomic disadvantage-predicts health-impairing adult behaviors, including tobacco and alcohol dependencies. These behaviors depend, in part, on the functionality of corticostriatal brain systems that 1) show developmental plasticity and early vulnerability, 2) process reward-related information, and 3) regulate impulsive decisions and actions. Hence, corticostriatal functionality in adulthood may covary directly with indicators of early socioeconomic disadvantage, particularly lower parental education. Here, we tested the covariation between parental education and corticostriatal activation and connectivity in 76 adults without confounding clinical syndromes. Corticostriatal activation and connectivity were assessed during the processing of stimuli signaling monetary gains (positive feedback [PF]) and losses (negative feedback). After accounting for participants' own education and other explanatory factors, lower parental education predicted reduced activation in anterior cingulate and dorsomedial prefrontal cortices during PF, along with reduced connectivity between these cortices and orbitofrontal and striatal areas implicated in reward processing and impulse regulation. In speculation, adult alterations in corticostriatal functionality may represent facets of a neurobiological endophenotype linked to socioeconomic conditions of early development.

  17. Parental Education Predicts Corticostriatal Functionality in Adulthood

    PubMed Central

    Manuck, Stephen B.; Sheu, Lei K.; Kuan, Dora C. H.; Votruba-Drzal, Elizabeth; Craig, Anna E.; Hariri, Ahmad R.

    2011-01-01

    Socioeconomic disadvantage experienced in early development predicts ill health in adulthood. However, the neurobiological pathways linking early disadvantage to adult health remain unclear. Lower parental education—a presumptive indicator of early socioeconomic disadvantage—predicts health-impairing adult behaviors, including tobacco and alcohol dependencies. These behaviors depend, in part, on the functionality of corticostriatal brain systems that 1) show developmental plasticity and early vulnerability, 2) process reward-related information, and 3) regulate impulsive decisions and actions. Hence, corticostriatal functionality in adulthood may covary directly with indicators of early socioeconomic disadvantage, particularly lower parental education. Here, we tested the covariation between parental education and corticostriatal activation and connectivity in 76 adults without confounding clinical syndromes. Corticostriatal activation and connectivity were assessed during the processing of stimuli signaling monetary gains (positive feedback [PF]) and losses (negative feedback). After accounting for participants’ own education and other explanatory factors, lower parental education predicted reduced activation in anterior cingulate and dorsomedial prefrontal cortices during PF, along with reduced connectivity between these cortices and orbitofrontal and striatal areas implicated in reward processing and impulse regulation. In speculation, adult alterations in corticostriatal functionality may represent facets of a neurobiological endophenotype linked to socioeconomic conditions of early development. PMID:20810623

  18. Mining phenotypes for gene function prediction

    PubMed Central

    Groth, Philip; Weiss, Bertram; Pohlenz, Hans-Dieter; Leser, Ulf

    2008-01-01

    Background Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In the past years, many technologies to systematically generate phenotypes in a high-throughput manner, such as RNA interference or gene knock-out, have been developed and used to decipher functions for genes. However, there have been relatively few efforts to make use of phenotype data beyond the single genotype-phenotype relationships. Results We present results on a study where we use a large set of phenotype data – in textual form – to predict gene annotation. To this end, we use text clustering to group genes based on their phenotype descriptions. We show that these clusters correlate well with several indicators for biological coherence in gene groups, such as functional annotations from the Gene Ontology (GO) and protein-protein interactions. We exploit these clusters for predicting gene function by carrying over annotations from well-annotated genes to other, less-characterized genes in the same cluster. For a subset of groups selected by applying objective criteria, we can predict GO-term annotations from the biological process sub-ontology with up to 72.6% precision and 16.7% recall, as evaluated by cross-validation. We manually verified some of these clusters and found them to exhibit high biological coherence, e.g. a group containing all available antennal Drosophila odorant receptors despite inconsistent GO-annotations. Conclusion The intrinsic nature of phenotypes to visibly reflect genetic activity underlines their usefulness in inferring new gene functions. Thus, systematically analyzing these data on a large scale offers many possibilities for inferring functional annotation of genes. We show that text clustering can play an important role in this process. PMID:18315868

  19. An overview of in silico protein function prediction.

    PubMed

    Sleator, Roy D; Walsh, Paul

    2010-03-01

    As the protein databases continue to expand at an exponential rate, fed by daily uploads from multiple large scale genomic and metagenomic projects, the problem of assigning a function to each new protein has become the focus of significant research interest in recent times. Herein, we review the most recent advances in the field of automated function prediction (AFP). We begin by defining what is meant by biological "function" and the means of describing such functions using standardised machine readable ontologies. We then focus on the various function-prediction programs available, both sequence and structure based, and outline their associated strengths and weaknesses. Finally, we conclude with a brief overview of the future challenges and outstanding questions in the field, which still remain unanswered.

  20. Characterization and Prediction of Chemical Functions and ...

    EPA Pesticide Factsheets

    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

  1. Functional brain network efficiency predicts intelligence.

    PubMed

    Langer, Nicolas; Pedroni, Andreas; Gianotti, Lorena R R; Hänggi, Jürgen; Knoch, Daria; Jäncke, Lutz

    2012-06-01

    The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

  2. Graph pyramids for protein function prediction

    PubMed Central

    2015-01-01

    Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

  3. Graph pyramids for protein function prediction.

    PubMed

    Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

    2015-01-01

    Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

  4. Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer

    PubMed Central

    Chandrasekaran, Gopalakrishnan; Hwang, Eu Chang; Kang, Taek Won; Kwon, Dong Deuk; Park, Kwangsung; Lee, Je-Jung; Lakshmanan, Vinoth-Kumar

    2017-01-01

    The human HOXB13 gene encodes a 284 amino acid transcription factor belonging to the homeobox gene family containing a homeobox and a HoxA13 N-terminal domain. It is highly linked to hereditary prostate cancer, the majority of which is manifested as a result of a Single Nucleotide Polymorphism (SNP). In silico analysis of 95 missense SNP’s corresponding to the non-homeobox region of HOXB13 predicted 21 nsSNP’s to be potentially deleterious. Among 123 UTR SNPs analysed by UTRScan, rs543028086, rs550968159, rs563065128 were found to affect the UNR_BS, GY-BOX and MBE UTR signals, respectively. Subsequent analysis by PolymiRTS revealed 23 UTR SNPs altering the miRNA binding site. The complete HOXB13_M26 protein structure was modelled using MODELLER v9.17. Computational analysis of the 21 nsSNP’s mapped into the HOXB13_M26 protein revealed seven nsSNP’s (rs761914407, rs8556, rs138213197, rs772962401, rs778843798, rs770620686 and rs587780165) seriously resulting in a damaging and deleterious effect on the protein. G84E, G135E, and A128V resulted in increased, while, R215C, C66R, Y80C and S122R resulted in decreased protein stability, ultimately predicted to result in the altered binding patterns of HOXB13. While the genotype-phenotype based effects of nsSNP’s were assessed, the exact biological and biochemical mechanism driven by the above predicted SNPs still needs to be extensively evaluated by in vivo and GWAS studies. PMID:28272408

  5. Predicting individual brain functional connectivity using a Bayesian hierarchical model.

    PubMed

    Dai, Tian; Guo, Ying

    2017-02-15

    Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual

  6. White matter predicts functional connectivity in premanifest Huntington's disease.

    PubMed

    McColgan, Peter; Gregory, Sarah; Razi, Adeel; Seunarine, Kiran K; Gargouri, Fatma; Durr, Alexandra; Roos, Raymund A C; Leavitt, Blair R; Scahill, Rachael I; Clark, Chris A; Tabrizi, Sarah J; Rees, Geraint; Coleman, A; Decolongon, J; Fan, M; Petkau, T; Jauffret, C; Justo, D; Lehericy, S; Nigaud, K; Valabrègue, R; Choonderbeek, A; Hart, E P T; Hensman Moss, D J; Crawford, H; Johnson, E; Papoutsi, M; Berna, C; Reilmann, R; Weber, N; Stout, J; Labuschagne, I; Landwehrmeyer, B; Orth, M; Johnson, H

    2017-02-01

    The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's. Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease. We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases. Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero-posterior dissociation that is in keeping with the caudo-rostral gradient of striatal pathology in HD.

  7. Predicting transfer performance: a comparison of competing function learning models.

    PubMed

    McDaniel, Mark A; Dimperio, Eric; Griego, Jacqueline A; Busemeyer, Jerome R

    2009-01-01

    The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input values with their paired output values. Transfer incorporates a linear rule-based response mechanism (McDaniel & Busemeyer, 2005). Learners were trained on a functional relationship defined by 2 linear-function segments with mirror slopes. In Experiment 1, 1 segment was densely trained and 1 was sparsely trained; in Experiment 2, both segments were trained equally, but the 2 segments were widely separated. Transfer to new input values was tested. For each model, training performance for each individual participant was fit, and transfer predictions were generated. POLE generally better fit the training data than did EXAM, but EXAM was more accurate at predicting (and fitting) transfer behaviors. It was especially telling that in Experiment 2 the transfer pattern was more consistent with EXAM's but not POLE's predictions, even though the presentation of salient linear segments during training dovetailed with POLE's approach.

  8. Prediction of Erectile Function Following Treatment for Prostate Cancer

    PubMed Central

    Alemozaffar, Mehrdad; Regan, Meredith M.; Cooperberg, Matthew R.; Wei, John T.; Michalski, Jeff M.; Sandler, Howard M.; Hembroff, Larry; Sadetsky, Natalia; Saigal, Christopher S.; Litwin, Mark S.; Klein, Eric; Kibel, Adam S.; Hamstra, Daniel A.; Pisters, Louis L.; Kuban, Deborah A.; Kaplan, Irving D.; Wood, David P.; Ciezki, Jay; Dunn, Rodney L.; Carroll, Peter R.; Sanda, Martin G.

    2013-01-01

    Context Sexual function is the health-related quality of life (HRQOL) domain most commonly impaired after prostate cancer treatment; however, validated tools to enable personalized prediction of erectile dysfunction after prostate cancer treatment are lacking. Objective To predict long-term erectile function following prostate cancer treatment based on individual patient and treatment characteristics. Design Pretreatment patient characteristics, sexual HRQOL, and treatment details measured in a longitudinal academic multicenter cohort (Prostate Cancer Outcomes and Satisfaction With Treatment Quality Assessment; enrolled from 2003 through 2006), were used to develop models predicting erectile function 2 years after treatment. A community-based cohort (community-based Cancer of the Prostate Strategic Urologic Research Endeavor [CaPSURE]; enrolled 1995 through 2007) externally validated model performance. Patients in US academic and community-based practices whose HRQOL was measured pretreatment (N = 1201) underwent follow-up after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. Sexual outcomes among men completing 2 years’ follow-up (n = 1027) were used to develop models predicting erectile function that were externally validated among 1913 patients in a community-based cohort. Main Outcome Measures Patient-reported functional erections suitable for intercourse 2 years following prostate cancer treatment. Results Two years after prostate cancer treatment, 368 (37% [95% CI, 34%–40%]) of all patients and 335 (48% [95% CI, 45%–52%]) of those with functional erections prior to treatment reported functional erections; 531 (53% [95% CI, 50%–56%]) of patients without penile prostheses reported use of medications or other devices for erectile dysfunction. Pretreatment sexual HRQOL score, age, serum prostate-specific antigen level, race/ethnicity, body mass index, and intended treatment details were associated with functional erections 2

  9. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

    PubMed Central

    Hwang, Sohyun; Rhee, Seung Y; Marcotte, Edward M; Lee, Insuk

    2012-01-01

    AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests. PMID:21886106

  10. Executive functions predict conceptual learning of science.

    PubMed

    Rhodes, Sinéad M; Booth, Josephine N; Palmer, Lorna Elise; Blythe, Richard A; Delibegovic, Mirela; Wheate, Nial J

    2016-06-01

    We examined the relationship between executive functions and both factual and conceptual learning of science, specifically chemistry, in early adolescence. Sixty-three pupils in their second year of secondary school (aged 12-13 years) participated. Pupils completed tasks of working memory (Spatial Working Memory), inhibition (Stop-Signal), attention set-shifting (ID/ED), and planning (Stockings of Cambridge), from the CANTAB. They also participated in a chemistry teaching session, practical, and assessment on the topic of acids and alkalis designed specifically for this study. Executive function data were related to (1) the chemistry assessment which included aspects of factual and conceptual learning and (2) a recent school science exam. Correlational analyses between executive functions and both the chemistry assessment and science grades revealed that science achievements were significantly correlated with working memory. Linear regression analysis revealed that visuospatial working memory ability was predictive of chemistry performance. Interestingly, this relationship was observed solely in relation to the conceptual learning condition of the assessment highlighting the role of executive functions in understanding and applying knowledge about what is learned within science teaching.

  11. Executive function processes predict mobility outcomes in older adults.

    PubMed

    Gothe, Neha P; Fanning, Jason; Awick, Elizabeth; Chung, David; Wójcicki, Thomas R; Olson, Erin A; Mullen, Sean P; Voss, Michelle; Erickson, Kirk I; Kramer, Arthur F; McAuley, Edward

    2014-02-01

    To examine the relationship between performance on executive function measures and subsequent mobility outcomes in community-dwelling older adults. Randomized controlled clinical trial. Champaign-Urbana, Illinois. Community-dwelling older adults (N = 179; mean age 66.4). A 12-month exercise trial with two arms: an aerobic exercise group and a stretching and strengthening group. Established cognitive tests of executive function (flanker task, task switching, and a dual-task paradigm) and the Wisconsin card sort test. Mobility was assessed using the timed 8-foot up and go test and times to climb up and down a flight of stairs. Participants completed the cognitive tests at baseline and the mobility measures at baseline and after 12 months of the intervention. Multiple regression analyses were conducted to determine whether baseline executive function predicted postintervention functional performance after controlling for age, sex, education, cardiorespiratory fitness, and baseline mobility levels. Selective baseline executive function measurements, particularly performance on the flanker task (β = 0.15-0.17) and the Wisconsin card sort test (β = 0.11-0.16) consistently predicted mobility outcomes at 12 months. The estimates were in the expected direction, such that better baseline performance on the executive function measures predicted better performance on the timed mobility tests independent of intervention. Executive functions of inhibitory control, mental set shifting, and attentional flexibility were predictive of functional mobility. Given the literature associating mobility limitations with disability, morbidity, and mortality, these results are important for understanding the antecedents to poor mobility function that well-designed interventions to improve cognitive performance can attenuate. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

  12. Predicting human brain activity associated with the meanings of nouns.

    PubMed

    Mitchell, Tom M; Shinkareva, Svetlana V; Carlson, Andrew; Chang, Kai-Min; Malave, Vicente L; Mason, Robert A; Just, Marcel Adam

    2008-05-30

    The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.

  13. Ontology-Based Prediction and Prioritization of Gene Functional Annotations.

    PubMed

    Chicco, Davide; Masseroli, Marco

    2016-01-01

    Genes and their protein products are essential molecular units of a living organism. The knowledge of their functions is key for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. The association of a gene or protein with its functions, described by controlled terms of biomolecular terminologies or ontologies, is named gene functional annotation. Very many and valuable gene annotations expressed through terminologies and ontologies are available. Nevertheless, they might include some erroneous information, since only a subset of annotations are reviewed by curators. Furthermore, they are incomplete by definition, given the rapidly evolving pace of biomolecular knowledge. In this scenario, computational methods that are able to quicken the annotation curation process and reliably suggest new annotations are very important. Here, we first propose a computational pipeline that uses different semantic and machine learning methods to predict novel ontology-based gene functional annotations; then, we introduce a new semantic prioritization rule to categorize the predicted annotations by their likelihood of being correct. Our tests and validations proved the effectiveness of our pipeline and prioritization of predicted annotations, by selecting as most likely manifold predicted annotations that were later confirmed.

  14. Postpartum Sexual Functioning and Its Predicting Factors among Iranian Women

    PubMed Central

    Rezaei, Nazanin; Azadi, Arman; Sayehmiri, Kourosh; Valizadeh, Reza

    2017-01-01

    Background Many women experience sexual dysfunction following childbirth but this has not been well investigated in Iran. The aim of this study was to evaluate women’s sexual function in the postpartum period in Iran. It also sought to determine predicting factors associated with their sexual function. Methods This was a cross-sectional study among 380 postpartum women attending 10 urban health centers in Ilam province in southwestern Iran. Participants were selected using random cluster sampling. Data was collected using the female sexual function index (FSFI) and a checklist of socio-demographic and maternal status for each of the women. Sexual dysfunction was classified according to an FSFI score of ≤ 28. Data were analysed using SPSS version 22. Results The majority of participants (76.3%) had sexual dysfunction. Primiparity (adjusted odds ratio (aOR): 1.78 (95% Confidence Interval (CI): 1.11, 2.94); P = 0.006) and exclusive breastfeeding (aOR: 2.47 (95% CI: 1.21, 5.03); P = 0.012) were associated with increased odds of experiencing sexual dysfunction in the postpartum period. Other factors such as age, type of delivery, education, time since delivery and family income did not predict women’s postpartum sexual function. Conclusion This study confirmed findings of previous studies on factors that may have an adverse effect on new mothers’ sexual function in the postpartum period. However the effect of type of delivery on postpartum sexual function remains unclear. PMID:28381932

  15. Brain natriuretic peptide predicts functional outcome in ischemic stroke

    PubMed Central

    Rost, Natalia S; Biffi, Alessandro; Cloonan, Lisa; Chorba, John; Kelly, Peter; Greer, David; Ellinor, Patrick; Furie, Karen L

    2011-01-01

    Background Elevated serum levels of brain natriuretic peptide (BNP) have been associated with cardioembolic (CE) stroke and increased post-stroke mortality. We sought to determine whether BNP levels were associated with functional outcome after ischemic stroke. Methods We measured BNP in consecutive patients aged ≥18 years admitted to our Stroke Unit between 2002–2005. BNP quintiles were used for analysis. Stroke subtypes were assigned using TOAST criteria. Outcomes were measured as 6-month modified Rankin Scale score (“good outcome” = 0–2 vs. “poor”) as well as mortality. Multivariate logistic regression was used to assess association between the quintiles of BNP and outcomes. Predictive performance of BNP as compared to clinical model alone was assessed by comparing ROC curves. Results Of 569 ischemic stroke patients, 46% were female; mean age was 67.9 ± 15 years. In age- and gender-adjusted analysis, elevated BNP was associated with lower ejection fraction (p<0.0001) and left atrial dilatation (p<0.001). In multivariate analysis, elevated BNP decreased the odds of good functional outcome (OR 0.64, 95%CI 0.41–0.98) and increased the odds of death (OR 1.75, 95%CI 1.36–2.24) in these patients. Addition of BNP to multivariate models increased their predictive performance for functional outcome (p=0.013) and mortality (p<0.03) after CE stroke. Conclusions Serum BNP levels are strongly associated with CE stroke and functional outcome at 6 months after ischemic stroke. Inclusion of BNP improved prediction of mortality in patients with CE stroke. PMID:22116811

  16. Accurate sperm morphology assessment predicts sperm function.

    PubMed

    Abu Hassan Abu, D; Franken, D R; Hoffman, B; Henkel, R

    2012-05-01

    Sperm morphology has been associated with in vitro as well as in vivo fertilisation. The study aimed to evaluate the possible relation between the percentage of spermatozoa with normal morphology and the following sperm functional assays: (i) zona-induced acrosome reaction (ZIAR); (ii) DNA integrity; (iii) chromatin condensation; (iv) sperm apoptosis; and (v) fertilisation rates. Regression analysis was employed to calculate the association between morphology and different functional tests. Normal sperm morphology correlated significantly with the percentages of live acrosome-reacted spermatozoa in the ZIAR (r = 0.518; P < 0.0001; n = 92), DNA integrity (r = -0.515; P = 0.0018; n = 34), CMA(3) -positive spermatozoa (r = -0.745; P < 0.0001; n = 92), sperm apoptosis (r = -0.395; P = 0.0206; n = 34) and necrosis (r = -0.545; P = 0.0009; n = 34). Negative correlations existed between for the acrosome reaction, and DNA integrity, while negative associations were recorded with the percentages of CMA(3) -positive spermatozoa, apoptotic and necrotic spermatozoa. Sperm morphology is related to sperm dysfunction such as poor chromatin condensation, acrosome reaction and DNA integrity. Negative and significant correlations existed between normal sperm morphology and chromatin condensation, the percentage of spermatozoa with abnormal DNA and spermatozoa with apoptotic activity. The authors do not regard sperm morphology as the only test for the diagnosis of male fertility, but sperm morphology can serve as a valuable indicator of underlying dysfunction.

  17. Predicting Protein Function via Semantic Integration of Multiple Networks.

    PubMed

    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.

  18. Spinal meningiomas: clinicoradiological factors predicting recurrence and functional outcome.

    PubMed

    Maiti, Tanmoy K; Bir, Shyamal C; Patra, Devi Prasad; Kalakoti, Piyush; Guthikonda, Bharat; Nanda, Anil

    2016-08-01

    OBJECTIVE Spinal meningiomas are benign tumors with a wide spectrum of clinical and radiological features at presentation. The authors analyzed multiple clinicoradiological factors to predict recurrence and functional outcome in a cohort with a mean follow-up of more than 4 years. The authors also discuss the results of clinical studies regarding spinal meningiomas in the last 15 years. METHODS The authors retrospectively reviewed the clinical and radiological details of patients who underwent surgery for spinal tumors between 2001 and 2015 that were histopathologically confirmed as meningiomas. Demographic parameters, such as age, sex, race, and association with neurofibromatosis Type 2, were considered. Radiological parameters, such as tumor size, signal changes of spinal cord, spinal level, number of levels, location of tumor attachment, shape of tumor, and presence of dural tail/calcification, were noted. These factors were analyzed to predict recurrence and functional outcome. Furthermore, a pooled analysis was performed from 13 reports of spinal meningiomas in the last 15 years. RESULTS A total of 38 patients were included in this study. Male sex and tumors with radiological evidence of a dural tail were associated with an increased risk of recurrence at a mean follow-up of 51.2 months. Ventral or ventrolateral location, large tumors, T2 cord signal changes, and poor preoperative functional status were associated with poor functional outcome at 1-year follow-up. CONCLUSIONS Spine surgeons must be aware of the natural history and risk factors of spinal meningiomas to establish a prognosis for their patients.

  19. 47 CFR 69.603 - Association functions.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Association functions. 69.603 Section 69.603... Exchange Carrier Association § 69.603 Association functions. (a) The Association shall not engage in any... functions pursuant to § 69.603 (c)-(g), and those expenses that pertain to Commission proceedings...

  20. Community-Wide Evaluation of Computational Function Prediction.

    PubMed

    Friedberg, Iddo; Radivojac, Predrag

    2017-01-01

    A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, to gain insights into the activity of these molecules and guide experiments, we must rely on computational means to functionally annotate the majority of sequence data. To understand how well these algorithms perform, we have established a challenge involving a broad scientific community in which we evaluate different annotation methods according to their ability to predict the associations between previously unannotated protein sequences and Gene Ontology terms. Here we discuss the rationale, benefits, and issues associated with evaluating computational methods in an ongoing community-wide challenge.

  1. A review of protein function prediction under machine learning perspective.

    PubMed

    Bernardes, Juliana S; Pedreira, Carlos E

    2013-08-01

    Protein function prediction is one of the most challenging problems in the post-genomic era. The number of newly identified proteins has been exponentially increasing with the advances of the high-throughput techniques. However, the functional characterization of these new proteins was not incremented in the same proportion. To fill this gap, a large number of computational methods have been proposed in the literature. Early approaches have explored homology relationships to associate known functions to the newly discovered proteins. Nevertheless, these approaches tend to fail when a new protein is considerably different (divergent) from previously known ones. Accordingly, more accurate approaches, that use expressive data representation and explore sophisticate computational techniques are required. Regarding these points, this review provides a comprehensible description of machine learning approaches that are currently applied to protein function prediction problems. We start by defining several problems enrolled in understanding protein function aspects, and describing how machine learning can be applied to these problems. We aim to expose, in a systematical framework, the role of these techniques in protein function inference, sometimes difficult to follow up due to the rapid evolvement of the field. With this purpose in mind, we highlight the most representative contributions, the recent advancements, and provide an insightful categorization and classification of machine learning methods in functional proteomics.

  2. Predictable convergence in hemoglobin function has unpredictable molecular underpinnings.

    PubMed

    Natarajan, Chandrasekhar; Hoffmann, Federico G; Weber, Roy E; Fago, Angela; Witt, Christopher C; Storz, Jay F

    2016-10-21

    To investigate the predictability of genetic adaptation, we examined the molecular basis of convergence in hemoglobin function in comparisons involving 56 avian taxa that have contrasting altitudinal range limits. Convergent increases in hemoglobin-oxygen affinity were pervasive among high-altitude taxa, but few such changes were attributable to parallel amino acid substitutions at key residues. Thus, predictable changes in biochemical phenotype do not have a predictable molecular basis. Experiments involving resurrected ancestral proteins revealed that historical substitutions have context-dependent effects, indicating that possible adaptive solutions are contingent on prior history. Mutations that produce an adaptive change in one species may represent precluded possibilities in other species because of differences in genetic background. Copyright © 2016, American Association for the Advancement of Science.

  3. Quantitative assessment of protein function prediction from metagenomics shotgun sequences.

    PubMed

    Harrington, E D; Singh, A H; Doerks, T; Letunic, I; von Mering, C; Jensen, L J; Raes, J; Bork, P

    2007-08-28

    To assess the potential of protein function prediction in environmental genomics data, we analyzed shotgun sequences from four diverse and complex habitats. Using homology searches as well as customized gene neighborhood methods that incorporate intergenic and evolutionary distances, we inferred specific functions for 76% of the 1.4 million predicted ORFs in these samples (83% when nonspecific functions are considered). Surprisingly, these fractions are only slightly smaller than the corresponding ones in completely sequenced genomes (83% and 86%, respectively, by using the same methodology) and considerably higher than previously thought. For as many as 75,448 ORFs (5% of the total), only neighborhood methods can assign functions, illustrated here by a previously undescribed gene associated with the well characterized heme biosynthesis operon and a potential transcription factor that might regulate a coupling between fatty acid biosynthesis and degradation. Our results further suggest that, although functions can be inferred for most proteins on earth, many functions remain to be discovered in numerous small, rare protein families.

  4. The Prediction of Scattered Broadband Shock-Associated Noise

    NASA Technical Reports Server (NTRS)

    Miller, Steven A. E.

    2015-01-01

    A mathematical model is developed for the prediction of scattered broadband shock-associated noise. Model arguments are dependent on the vector Green's function of the linearized Euler equations, steady Reynolds-averaged Navier-Stokes solutions, and the two-point cross-correlation of the equivalent source. The equivalent source is dependent on steady Reynolds-averaged Navier-Stokes solutions of the jet flow, that capture the nozzle geometry and airframe surface. Contours of the time-averaged streamwise velocity component and turbulent kinetic energy are examined with varying airframe position relative to the nozzle exit. Propagation effects are incorporated by approximating the vector Green's function of the linearized Euler equations. This approximation involves the use of ray theory and an assumption that broadband shock-associated noise is relatively unaffected by the refraction of the jet shear layer. A non-dimensional parameter is proposed that quantifies the changes of the broadband shock-associated noise source with varying jet operating condition and airframe position. Scattered broadband shock-associated noise possesses a second set of broadband lobes that are due to the effect of scattering. Presented predictions demonstrate relatively good agreement compared to a wide variety of measurements.

  5. Habitual fat intake predicts memory function in younger women.

    PubMed

    Gibson, E Leigh; Barr, Suzanne; Jeanes, Yvonne M

    2013-01-01

    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 to 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, Cambridge, UK), i.e., verbal memory, visuo-spatial learning, and delayed pattern matching (DMS), 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 DMS 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 monounsaturated (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

  6. Habitual fat intake predicts memory function in younger women

    PubMed Central

    Gibson, E. Leigh; Barr, Suzanne; Jeanes, Yvonne M.

    2013-01-01

    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 to 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, Cambridge, UK), i.e., verbal memory, visuo-spatial learning, and delayed pattern matching (DMS), 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 DMS 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 monounsaturated (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

  7. "Reverse Genomics" Predicts Function of Human Conserved Noncoding Elements.

    PubMed

    Marcovitz, Amir; Jia, Robin; Bejerano, Gill

    2016-05-01

    Evolutionary changes in cis-regulatory elements are thought to play a key role in morphological and physiological diversity across animals. Many conserved noncoding elements (CNEs) function as cis-regulatory elements, controlling gene expression levels in different biological contexts. However, determining specific associations between CNEs and related phenotypes is a challenging task. Here, we present a computational "reverse genomics" approach that predicts the phenotypic functions of human CNEs. We identify thousands of human CNEs that were lost in at least two independent mammalian lineages (IL-CNEs), and match their evolutionary profiles against a diverse set of phenotypes recently annotated across multiple mammalian species. We identify 2,759 compelling associations between human CNEs and a diverse set of mammalian phenotypes. We discuss multiple CNEs, including a predicted ear element near BMP7, a pelvic CNE in FBN1, a brain morphology element in UBE4B, and an aquatic adaptation forelimb CNE near EGR2, and provide a full list of our predictions. As more genomes are sequenced and more traits are annotated across species, we expect our method to facilitate the interpretation of noncoding mutations in human disease and expedite the discovery of individual CNEs that play key roles in human evolution and development. © The Author 2016. 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.

  8. Premotor functional connectivity predicts impulsivity in juvenile offenders.

    PubMed

    Shannon, Benjamin J; Raichle, Marcus E; Snyder, Abraham Z; Fair, Damien A; Mills, Kathryn L; Zhang, Dongyang; Bache, Kevin; Calhoun, Vince D; Nigg, Joel T; Nagel, Bonnie J; Stevens, Alexander A; Kiehl, Kent A

    2011-07-05

    Teenagers are often impulsive. In some cases this is a phase of normal development; in other cases impulsivity contributes to criminal behavior. Using functional magnetic resonance imaging, we examined resting-state functional connectivity among brain systems and behavioral measures of impulsivity in 107 juveniles incarcerated in a high-security facility. In less-impulsive juveniles and normal controls, motor planning regions were correlated with brain networks associated with spatial attention and executive control. In more-impulsive juveniles, these same regions correlated with the default-mode network, a constellation of brain areas associated with spontaneous, unconstrained, self-referential cognition. The strength of these brain-behavior relationships was sufficient to predict impulsivity scores at the individual level. Our data suggest that increased functional connectivity of motor-planning regions with networks subserving unconstrained, self-referential cognition, rather than those subserving executive control, heightens the predisposition to impulsive behavior in juvenile offenders. To further explore the relationship between impulsivity and neural development, we studied functional connectivity in the same motor-planning regions in 95 typically developing individuals across a wide age span. The change in functional connectivity with age mirrored that of impulsivity: younger subjects tended to exhibit functional connectivity similar to the more-impulsive incarcerated juveniles, whereas older subjects exhibited a less-impulsive pattern. This observation suggests that impulsivity in the offender population is a consequence of a delay in typical development, rather than a distinct abnormality.

  9. Premotor functional connectivity predicts impulsivity in juvenile offenders

    PubMed Central

    Shannon, Benjamin J.; Raichle, Marcus E.; Snyder, Abraham Z.; Fair, Damien A.; Mills, Kathryn L.; Zhang, Dongyang; Bache, Kevin; Calhoun, Vince D.; Nigg, Joel T.; Nagel, Bonnie J.; Stevens, Alexander A.; Kiehl, Kent A.

    2011-01-01

    Teenagers are often impulsive. In some cases this is a phase of normal development; in other cases impulsivity contributes to criminal behavior. Using functional magnetic resonance imaging, we examined resting-state functional connectivity among brain systems and behavioral measures of impulsivity in 107 juveniles incarcerated in a high-security facility. In less-impulsive juveniles and normal controls, motor planning regions were correlated with brain networks associated with spatial attention and executive control. In more-impulsive juveniles, these same regions correlated with the default-mode network, a constellation of brain areas associated with spontaneous, unconstrained, self-referential cognition. The strength of these brain–behavior relationships was sufficient to predict impulsivity scores at the individual level. Our data suggest that increased functional connectivity of motor-planning regions with networks subserving unconstrained, self-referential cognition, rather than those subserving executive control, heightens the predisposition to impulsive behavior in juvenile offenders. To further explore the relationship between impulsivity and neural development, we studied functional connectivity in the same motor-planning regions in 95 typically developing individuals across a wide age span. The change in functional connectivity with age mirrored that of impulsivity: younger subjects tended to exhibit functional connectivity similar to the more-impulsive incarcerated juveniles, whereas older subjects exhibited a less-impulsive pattern. This observation suggests that impulsivity in the offender population is a consequence of a delay in typical development, rather than a distinct abnormality. PMID:21709236

  10. Text Mining Improves Prediction of Protein Functional Sites

    PubMed Central

    Cohn, Judith D.; Ravikumar, Komandur E.

    2012-01-01

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

  11. A Prediction Model of the Capillary Pressure J-Function

    PubMed Central

    Xu, W. S.; Luo, P. Y.; Sun, L.; Lin, N.

    2016-01-01

    The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative. PMID:27603701

  12. Marijuana Use Predicts Cognitive Performance on Tasks of Executive Function

    PubMed Central

    Dahlgren, Mary Kathryn; Sagar, Kelly A.; Racine, Megan T.; Dreman, Meredith W.; Gruber, Staci A.

    2016-01-01

    Objective: Despite growing evidence that chronic marijuana use is associated with cognitive impairment, particularly when use is initiated at an early age, national trends demonstrate significant decreases in the perceived risk of marijuana corresponding with increased use, especially among youth. The current study assessed the impact of marijuana use on executive function and whether patterns of marijuana use, including earlier age at onset, higher frequency, and increased magnitude of use, predict impairment. Method: Forty-four chronic, heavy marijuana smokers (37 male, 7 female) and 32 healthy, nonsmoking control participants (20 male, 12 female) recruited from the Greater Boston area completed two assessments of executive function: the Stroop Color Word Test and Wisconsin Card Sorting Test (WCST). Results: Marijuana smokers had poorer executive function relative to control participants, a between-group difference that was primarily driven by individuals with early onset of marijuana use (before age 16; n = 21); significance remained even when controlling for frequency and magnitude of use. Further, earlier age at marijuana onset and increased marijuana use predicted poorer neurocognitive performance, and perseverative errors on the WCST significantly predicted marijuana group membership. Conclusions: These findings underscore the impact of early onset of marijuana use on executive function impairment independent of increased frequency and magnitude of use. In addition, poorer performance on the WCST may serve as a neuropsychological marker for heavy marijuana users. These results highlight the need for additional research to identify predictors associated with early marijuana use, as exposure to marijuana during a period of developmental vulnerability may result in negative cognitive consequences. PMID:26997188

  13. Classical density functional theory for the prediction of the surface tension and interfacial properties of fluids mixtures of chain molecules based on the statistical associating fluid theory for potentials of variable range.

    PubMed

    Llovell, Fèlix; Galindo, Amparo; Blas, Felipe J; Jackson, George

    2010-07-14

    The statistical associating fluid theory for attractive potentials of variable range (SAFT-VR) density functional theory (DFT) developed by [G. J. Gloor et al., J. Chem. Phys. 121, 12740 (2004)] is revisited and generalized to treat mixtures. The Helmholtz free-energy functional, which is based on the SAFT-VR approach for homogeneous fluids, is constructed by partitioning the free-energy density into a reference term (which incorporates all of the short-range interactions and is treated locally) and an attractive perturbation (which incorporates the long-range dispersion interactions). In this work, two different functionals are compared. In the first, one uses a mean-field version of the theory to treat the long-range dispersive interaction, incorporating an approximate treatment of the effect of the correlations on the attractive energy between the segments by introducing a short-range attractive contribution in the reference term. In the second, one approximates the correlation function of the molecular segments in the inhomogeneous system with that of a homogeneous system for an average density of the two positions, following the ideas proposed by Toxvaerd [S. Toxvaerd, J. Chem. Phys. 64, 2863 (1976)]. The SAFT-VR DFT formalism is then used to study interfacial properties and adsorption phenomena at the interface. A detailed analysis of the influence of the molecular parameters on the surface tension and density/composition profiles of the mixtures is undertaken for binary mixtures of molecules of different chain length, segment diameter, dispersive energy, and attractive range. The effect of the asymmetry of the molecular species on the adsorption phenomena is examined in some depth. The adequacy of the approach is demonstrated by comparing the theoretical predictions with the interfacial properties of some real mixtures. The relative merits of the two approximate free-energy functionals are assessed by examining the vapor-liquid interfacial tension of

  14. CombFunc: predicting protein function using heterogeneous data sources.

    PubMed

    Wass, Mark N; Barton, Geraint; Sternberg, Michael J E

    2012-07-01

    Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein-protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc.

  15. Predicting Acute and Persistent Neuropathy Associated with Oxaliplatin

    PubMed Central

    Alejandro, Linh; Behrendt, Carolyn E.; Chen, Kim; Openshaw, Harry; Shibata, Stephen

    2014-01-01

    Objectives We sought to predict oxaliplatin-associated peripheral neuropathy during modified FOLFOX6 (mFOLFOX6) therapy. Methods In a 50% female sample, patients with previously untreated, primary or recurrent colorectal cancer were followed through a first course of mFOLFOX6 with oxaliplatin 85 mg/m2 every 2 weeks. Accounting for correlation among a subject's cycles, logistic regression estimated per-cycle risk of acute (under 14 days) and persistent (14 days or more) neuropathy. Proportional hazards regression predicted time to persistent neuropathy. Results Among mFOLFOX6 recipients (n=50, age 58.9 +10.1 years), 36% received concomitant bevacizumab. Of total cycles, 94.2% (422/448) were evaluable. Most (84%) subjects reported neuropathy at least once: 74% reported acute and 48% reported persistent symptoms. On multivariate analysis, risk factors shared by acute and persistent neuropathy were body-surface area >2.0, acute neuropathy in a past cycle, and lower body weight. In addition, risk of acute neuropathy decreased with age (adjusted for renal function and winter season), while risk of persistent neuropathy increased with cumulative dose of oxaliplatin and persistent neuropathy in a past cycle. Concomitant bevacizumab was not a risk factor when administered in Stage IV disease but was associated with persistent neuropathy when administered experimentally in Stage III. Females had no increased risk of either form of neuropathy. After 3 cycles, weight, body-surface area, and prior acute neuropathy predicted time to persistent neuropathy. Conclusions Routinely available clinical factors predict acute and persistent neuropathy associated with oxaliplatin. When validated, the proposed prognostic score for persistent neuropathy can help clinicians counsel patients about chemotherapy. PMID:22547012

  16. Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

    PubMed

    Khalsa, Sakh; Mayhew, Stephen D; Przezdzik, Izabela; Wilson, Rebecca; Hale, Joanne; Goldstone, Aimee; Bagary, Manny; Bagshaw, Andrew P

    2016-01-01

    We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance.

  17. Which Working Memory Functions Predict Intelligence?

    ERIC Educational Resources Information Center

    Oberauer, Klaus; Sub, Heinz-Martin; Wilhelm, Oliver; Wittmann, Werner W.

    2008-01-01

    Investigates the relationship between three factors of working memory (storage and processing, relational integration, and supervision) and four factors of intelligence (reasoning, speed, memory, and creativity) using structural equation models. Relational integration predicted reasoning ability at least as well as the storage-and-processing…

  18. GAPIT: genome association and prediction integrated tool

    USDA-ARS?s Scientific Manuscript database

    Advances in high throughput sequencing have improved the detection of genes underlying important traits as well as the prediction accuracy of disease risk and breeding value of crop or livestock. Software programs developed to perform statistical genetic analysis that support these activities should...

  19. Protein Function Prediction: Towards Integration of Similarity Metrics

    PubMed Central

    Erdin, Serkan; Lisewski, Andreas Martin; Lichtarge, Olivier

    2011-01-01

    Summary Genomics centers discover increasingly many protein sequences and structures, but not necessarily their full biological functions. Thus, currently, fewer than one percent of proteins have experimentally verified biochemical activities. To fill this gap, function prediction algorithms apply metrics of similarity between proteins on the premise that those sufficiently alike in sequence, or structure, will perform identical functions. Although high sensitivity is elusive, network analyses that integrate these metrics together hold the promise of rapid gains in function prediction specificity. PMID:21353529

  20. Models for predicting objective function weights in prostate cancer IMRT

    SciTech Connect

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

    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

  1. MASS FUNCTION PREDICTIONS BEYOND {Lambda}CDM

    SciTech Connect

    Bhattacharya, Suman; Lukic, Zarija; Habib, Salman; Heitmann, Katrin; White, Martin; Wagner, Christian

    2011-05-10

    The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference {Lambda}CDM cosmology and for a set of wCDM cosmologies. For the reference {Lambda}CDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) {Lambda}CDM mass function over a mass range of 6 x 10{sup 11}-3 x 10{sup 15} M{sub sun} to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a {Lambda}CDM cosmology and others with w {approx_equal} -1) are described by the fitting formula for the reference {Lambda}CDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

  2. Mass Function Predictions Beyond ΛCDM

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Suman; Heitmann, Katrin; White, Martin; Lukić, Zarija; Wagner, Christian; Habib, Salman

    2011-05-01

    The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference ΛCDM cosmology and for a set of wCDM cosmologies. For the reference ΛCDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) ΛCDM mass function over a mass range of 6 × 1011-3 × 1015 M sun to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a ΛCDM cosmology and others with w ~= -1) are described by the fitting formula for the reference ΛCDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

  3. Early executive function predicts reasoning development.

    PubMed

    Richland, Lindsey E; Burchinal, Margaret R

    2013-01-01

    Analogical reasoning is a core cognitive skill that distinguishes humans from all other species and contributes to general fluid intelligence, creativity, and adaptive learning capacities. Yet its origins are not well understood. In the study reported here, we analyzed large-scale longitudinal data from the Study of Early Child Care and Youth Development to test predictors of growth in analogical-reasoning skill from third grade to adolescence. Our results suggest an integrative resolution to the theoretical debate regarding contributory factors arising from smaller-scale, cross-sectional experiments on analogy development. Children with greater executive-function skills (both composite and inhibitory control) and vocabulary knowledge in early elementary school displayed higher scores on a verbal analogies task at age 15 years, even after adjusting for key covariates. We posit that knowledge is a prerequisite to analogy performance, but strong executive-functioning resources during early childhood are related to long-term gains in fundamental reasoning skills.

  4. Do optimism and pessimism predict physical functioning?

    PubMed

    Brenes, Gretchen A; Rapp, Stephen R; Rejeski, W Jack; Miller, Michael E

    2002-06-01

    Dispositional optimism has been shown to be related to self-report measures of health and well-being, yet little research has examined the relationship between optimism and more objective measures of functioning. The purpose of this study was to examine the relationship between optimism and pessimism and objective physical functioning. Four hundred eighty community-dwelling older adults with knee pain completed a measure of optimism and pessimism and were observed performing four daily activities (walking, lifting an object, climbing stairs, and getting into and out of a car). Results indicated that pessimism was significantly related to performance on all four tasks (p < .001), while optimism was related to performance only on the walking task (p < .05), after controlling for demographic and health variables.

  5. Improving structure-based function prediction using molecular dynamics

    PubMed Central

    Glazer, Dariya S.; Radmer, Randall J.; Altman, Russ B.

    2009-01-01

    Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods. PMID:19604472

  6. Salience Network Functional Connectivity Predicts Placebo Effects in Major Depression

    PubMed Central

    Sikora, Magdalena; Heffernan, Joseph; Avery, Erich T.; Mickey, Brian J.; Zubieta, Jon-Kar; Peciña, Marta

    2015-01-01

    Background Recent neuroimaging studies have demonstrated resting-state functional connectivity (rsFC) abnormalities among intrinsic brain networks in Major Depressive Disorder (MDD); however, their role as predictors of treatment response has not yet been explored. Here, we investigate whether network-based rsFC predicts antidepressant and placebo effects in MDD. Methods We performed a randomized controlled trial of two weeklong, identical placebos (described as having either “active” fast-acting, antidepressant effects or as “inactive”) followed by a ten-week open-label antidepressant medication treatment. Twenty-nine participants underwent a rsFC fMRI scan at the completion of each placebo condition. Networks were isolated from resting-state blood-oxygen-level-dependent signal fluctuations using independent component analysis. Baseline and placebo-induced changes in rsFC within the default-mode, salience, and executive networks were examined for associations with placebo and antidepressant treatment response. Results Increased baseline rsFC in the rostral anterior cingulate (rACC) within the salience network, a region classically implicated in the formation of placebo analgesia and the prediction of treatment response in MDD, was associated with greater response to one week of active placebo and ten weeks of antidepressant treatment. Machine learning further demonstrated that increased salience network rsFC, mainly within the rACC, significantly predicts individual responses to placebo administration. Conclusions These data demonstrate that baseline rsFC within the salience network is linked to clinical placebo responses. This information could be employed to identify patients who would benefit from lower doses of antidepressant medication or non-pharmacological approaches, or to develop biomarkers of placebo effects in clinical trials. PMID:26709390

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

    PubMed

    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.

  8. Gene function prediction using labeled and unlabeled data

    PubMed Central

    Zhao, Xing-Ming; Wang, Yong; Chen, Luonan; Aihara, Kazuyuki

    2008-01-01

    Background In general, gene function prediction can be formalized as a classification problem based on machine learning technique. Usually, both labeled positive and negative samples are needed to train the classifier. For the problem of gene function prediction, however, the available information is only about positive samples. In other words, we know which genes have the function of interested, while it is generally unclear which genes do not have the function, i.e. the negative samples. If all the genes outside of the target functional family are seen as negative samples, the imbalanced problem will arise because there are only a relatively small number of genes annotated in each family. Furthermore, the classifier may be degraded by the false negatives in the heuristically generated negative samples. Results In this paper, we present a new technique, namely Annotating Genes with Positive Samples (AGPS), for defining negative samples in gene function prediction. With the defined negative samples, it is straightforward to predict the functions of unknown genes. In addition, the AGPS algorithm is able to integrate various kinds of data sources to predict gene functions in a reliable and accurate manner. With the one-class and two-class Support Vector Machines as the core learning algorithm, the AGPS algorithm shows good performances for function prediction on yeast genes. Conclusion We proposed a new method for defining negative samples in gene function prediction. Experimental results on yeast genes show that AGPS yields good performances on both training and test sets. In addition, the overlapping between prediction results and GO annotations on unknown genes also demonstrates the effectiveness of the proposed method. PMID:18221567

  9. Taper Functions for Predicting Product Volumes in Natural Shortleaf Pines

    Treesearch

    Robert M. Farrar; Paul A. Murphy

    1987-01-01

    Taper (stem-profile) functions are presented for natural shortleaf pine (Pinus echinata Mill.) trees growing in the West Gulf area. These functions, when integrated, permit the prediction of volume between any two heights on a stem and, conversely by iteration, the volume between any two diameters on a stem. Examples are given of use of the functions...

  10. A survey of the broadband shock associated noise prediction methods

    NASA Technical Reports Server (NTRS)

    Kim, Chan M.; Krejsa, Eugene A.; Khavaran, Abbas

    1992-01-01

    Several different prediction methods to estimate the broadband shock associated noise of a supersonic jet are introduced and compared with experimental data at various test conditions. The nozzle geometries considered for comparison include a convergent and a convergent-divergent nozzle, both axisymmetric. Capabilities and limitations of prediction methods in incorporating the two nozzle geometries, flight effect, and temperature effect are discussed. Predicted noise field shows the best agreement for a convergent nozzle geometry under static conditions. Predicted results for nozzles in flight show larger discrepancies from data and more dependable flight data are required for further comparison. Qualitative effects of jet temperature, as observed in experiment, are reproduced in predicted results.

  11. Does obesity predict functional outcome in the dysvascular amputee?

    PubMed

    Kalbaugh, Corey A; Taylor, Spence M; Kalbaugh, Brooke A; Halliday, Matthew; Daniel, Grace; Cass, Anna L; Blackhurst, Dawn W; Cull, David L; Langan, Eugene M; Carsten, Christopher G; York, John W; Snyder, Bruce A; Youkey, Jerry R

    2006-08-01

    Limited information is available concerning the effects of obesity on the functional outcomes of patients requiring major lower limb amputation because of peripheral arterial disease (PAD). The purpose of this study was to examine the predictive ability of body mass index (BMI) to determine functional outcome in the dysvascular amputee. To do this, 434 consecutive patients (mean age, 65.8 +/- 13.3, 59% male, 71.4% diabetic) undergoing major limb amputation (225 below-knee amputation, 27 through-knee amputation, 132 above-knee amputation, and 50 bilateral) as a complication of PAD from January 1998 through May 2004 were analyzed according to preoperative BMI. BMI was classified according to the four-group Center for Disease Control system: underweight, 0 to 18.4 kg/m2; normal, 18.5 to 24.9 kg/m2; overweight, 25 to 29.9 kg/m2; and obese, > or = 30 kg/m2. Outcome parameters measured included prosthetic usage, maintenance of ambulation, survival, and maintenance of independent living status. The chi2 test for association was used to examine prosthesis wear. Kaplan-Meier curves were constructed to assess maintenance of ambulation, survival, and maintenance of independent living status. Multivariate analysis using the multiple logistic regression model and a Cox proportional hazards model were used to predict variables independently associated with prosthetic use and ambulation, survival, and independence, respectively. Overall prosthetic usage and 36-month ambulation, survival, and independent living status for the entire cohort was 48.6 per cent, 42.8 per cent, 48.1 per cent, 72.3 per cent, and for patients with normal BMI was 41.5 per cent, 37.4 per cent, 45.6 per cent, and 69.5 per cent, respectively. There was no statistically significant difference in outcomes for overweight patients (59.2%, 50.7%, 52.5%, and 75%) or obese patients (51.8%, 46.2%, 49.7%, and 75%) when compared with normal patients. Although there were significantly poorer outcomes for underweight

  12. Associative memory cells: Formation, function and perspective

    PubMed Central

    Wang, Jin-Hui; Cui, Shan

    2017-01-01

    Associative learning and memory are common activities in life, and their cellular infrastructures constitute the basis of cognitive processes. Although neuronal plasticity emerges after memory formation, basic units and their working principles for the storage and retrieval of associated signals remain to be revealed. Current reports indicate that associative memory cells, through their mutual synapse innervations among the co-activated sensory cortices, are recruited to fulfill the integration, storage and retrieval of multiple associated signals, and serve associative thinking and logical reasoning. In this review, we aim to summarize associative memory cells in their formation, features and functional impacts. PMID:28408978

  13. Collective judgment predicts disease-associated single nucleotide variants

    PubMed Central

    2013-01-01

    Background In recent years the number of human genetic variants deposited into the publicly available databases has been increasing exponentially. The latest version of dbSNP, for example, contains ~50 million validated Single Nucleotide Variants (SNVs). SNVs make up most of human variation and are often the primary causes of disease. The non-synonymous SNVs (nsSNVs) result in single amino acid substitutions and may affect protein function, often causing disease. Although several methods for the detection of nsSNV effects have already been developed, the consistent increase in annotated data is offering the opportunity to improve prediction accuracy. Results Here we present a new approach for the detection of disease-associated nsSNVs (Meta-SNP) that integrates four existing methods: PANTHER, PhD-SNP, SIFT and SNAP. We first tested the accuracy of each method using a dataset of 35,766 disease-annotated mutations from 8,667 proteins extracted from the SwissVar database. The four methods reached overall accuracies of 64%-76% with a Matthew's correlation coefficient (MCC) of 0.38-0.53. We then used the outputs of these methods to develop a machine learning based approach that discriminates between disease-associated and polymorphic variants (Meta-SNP). In testing, the combined method reached 79% overall accuracy and 0.59 MCC, ~3% higher accuracy and ~0.05 higher correlation with respect to the best-performing method. Moreover, for the hardest-to-define subset of nsSNVs, i.e. variants for which half of the predictors disagreed with the other half, Meta-SNP attained 8% higher accuracy than the best predictor. Conclusions Here we find that the Meta-SNP algorithm achieves better performance than the best single predictor. This result suggests that the methods used for the prediction of variant-disease associations are orthogonal, encoding different biologically relevant relationships. Careful combination of predictions from various resources is therefore a good strategy

  14. Dopamine neurons share common response function for reward prediction error

    PubMed Central

    Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

    2016-01-01

    Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

  15. Critical evidence for the prediction error theory in associative learning.

    PubMed

    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.

  16. PSiFR: an integrated resource for prediction of protein structure and function.

    PubMed

    Pandit, Shashi B; Brylinski, Michal; Zhou, Hongyi; Gao, Mu; Arakaki, Adrian K; Skolnick, Jeffrey

    2010-03-01

    In the post-genomic era, the annotation of protein function facilitates the understanding of various biological processes. To extend the range of function annotation methods to the twilight zone of sequence identity, we have developed approaches that exploit both protein tertiary structure and/or protein sequence evolutionary relationships. To serve the scientific community, we have integrated the structure prediction tools, TASSER, TASSER-Lite and METATASSER, and the functional inference tools, FINDSITE, a structure-based algorithm for binding site prediction, Gene Ontology molecular function inference and ligand screening, EFICAz(2), a sequence-based approach to enzyme function inference and DBD-hunter, an algorithm for predicting DNA-binding proteins and associated DNA-binding residues, into a unified web resource, Protein Structure and Function prediction Resource (PSiFR). PSiFR is freely available for use on the web at http://psifr.cssb.biology.gatech.edu/

  17. Predicting Transfer Performance: A Comparison of Competing Function Learning Models

    ERIC Educational Resources Information Center

    McDaniel, Mark A.; Dimperio, Eric; Griego, Jacqueline A.; Busemeyer, Jerome R.

    2009-01-01

    The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input…

  18. Predicting Transfer Performance: A Comparison of Competing Function Learning Models

    ERIC Educational Resources Information Center

    McDaniel, Mark A.; Dimperio, Eric; Griego, Jacqueline A.; Busemeyer, Jerome R.

    2009-01-01

    The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input…

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

    EPA Pesticide Factsheets

    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

  20. A yeast functional screen predicts new candidate ALS disease genes

    PubMed Central

    Couthouis, Julien; Hart, Michael P.; Shorter, James; DeJesus-Hernandez, Mariely; Erion, Renske; Oristano, Rachel; Liu, Annie X.; Ramos, Daniel; Jethava, Niti; Hosangadi, Divya; Epstein, James; Chiang, Ashley; Diaz, Zamia; Nakaya, Tadashi; Ibrahim, Fadia; Kim, Hyung-Jun; Solski, Jennifer A.; Williams, Kelly L.; Mojsilovic-Petrovic, Jelena; Ingre, Caroline; Boylan, Kevin; Graff-Radford, Neill R.; Dickson, Dennis W.; Clay-Falcone, Dana; Elman, Lauren; McCluskey, Leo; Greene, Robert; Kalb, Robert G.; Lee, Virginia M.-Y.; Trojanowski, John Q.; Ludolph, Albert; Robberecht, Wim; Andersen, Peter M.; Nicholson, Garth A.; Blair, Ian P.; King, Oliver D.; Bonini, Nancy M.; Van Deerlin, Vivianna; Rademakers, Rosa; Mourelatos, Zissimos; Gitler, Aaron D.

    2011-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating and universally fatal neurodegenerative disease. Mutations in two related RNA-binding proteins, TDP-43 and FUS, that harbor prion-like domains, cause some forms of ALS. There are at least 213 human proteins harboring RNA recognition motifs, including FUS and TDP-43, raising the possibility that additional RNA-binding proteins might contribute to ALS pathogenesis. We performed a systematic survey of these proteins to find additional candidates similar to TDP-43 and FUS, followed by bioinformatics to predict prion-like domains in a subset of them. We sequenced one of these genes, TAF15, in patients with ALS and identified missense variants, which were absent in a large number of healthy controls. These disease-associated variants of TAF15 caused formation of cytoplasmic foci when expressed in primary cultures of spinal cord neurons. Very similar to TDP-43 and FUS, TAF15 aggregated in vitro and conferred neurodegeneration in Drosophila, with the ALS-linked variants having a more severe effect than wild type. Immunohistochemistry of postmortem spinal cord tissue revealed mislocalization of TAF15 in motor neurons of patients with ALS. We propose that aggregation-prone RNA-binding proteins might contribute very broadly to ALS pathogenesis and the genes identified in our yeast functional screen, coupled with prion-like domain prediction analysis, now provide a powerful resource to facilitate ALS disease gene discovery. PMID:22065782

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

    EPA Pesticide Factsheets

    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

  2. A new protein structure representation for efficient protein function prediction.

    PubMed

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average.

  3. Adaptive bandwidth measurements of importance functions for speech intelligibility prediction.

    PubMed

    Whitmal, Nathaniel A; DeRoy, Kristina

    2011-12-01

    The Articulation Index (AI) and Speech Intelligibility Index (SII) predict intelligibility scores from measurements of speech and hearing parameters. One component in the prediction is the "importance function," a weighting function that characterizes contributions of particular spectral regions of speech to speech intelligibility. Previous work with SII predictions for hearing-impaired subjects suggests that prediction accuracy might improve if importance functions for individual subjects were available. Unfortunately, previous importance function measurements have required extensive intelligibility testing with groups of subjects, using speech processed by various fixed-bandwidth low-pass and high-pass filters. A more efficient approach appropriate to individual subjects is desired. The purpose of this study was to evaluate the feasibility of measuring importance functions for individual subjects with adaptive-bandwidth filters. In two experiments, ten subjects with normal-hearing listened to vowel-consonant-vowel (VCV) nonsense words processed by low-pass and high-pass filters whose bandwidths were varied adaptively to produce specified performance levels in accordance with the transformed up-down rules of Levitt [(1971). J. Acoust. Soc. Am. 49, 467-477]. Local linear psychometric functions were fit to resulting data and used to generate an importance function for VCV words. Results indicate that the adaptive method is reliable and efficient, and produces importance function data consistent with that of the corresponding AI/SII importance function.

  4. Adaptive bandwidth measurements of importance functions for speech intelligibility prediction

    PubMed Central

    Whitmal, Nathaniel A.; DeRoy, Kristina

    2011-01-01

    The Articulation Index (AI) and Speech Intelligibility Index (SII) predict intelligibility scores from measurements of speech and hearing parameters. One component in the prediction is the “importance function,” a weighting function that characterizes contributions of particular spectral regions of speech to speech intelligibility. Previous work with SII predictions for hearing-impaired subjects suggests that prediction accuracy might improve if importance functions for individual subjects were available. Unfortunately, previous importance function measurements have required extensive intelligibility testing with groups of subjects, using speech processed by various fixed-bandwidth low-pass and high-pass filters. A more efficient approach appropriate to individual subjects is desired. The purpose of this study was to evaluate the feasibility of measuring importance functions for individual subjects with adaptive-bandwidth filters. In two experiments, ten subjects with normal-hearing listened to vowel-consonant-vowel (VCV) nonsense words processed by low-pass and high-pass filters whose bandwidths were varied adaptively to produce specified performance levels in accordance with the transformed up-down rules of Levitt [(1971). J. Acoust. Soc. Am. 49, 467–477]. Local linear psychometric functions were fit to resulting data and used to generate an importance function for VCV words. Results indicate that the adaptive method is reliable and efficient, and produces importance function data consistent with that of the corresponding AI/SII importance function. PMID:22225057

  5. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    EPA Science Inventory

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  6. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    EPA Science Inventory

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  7. Empirical sediment transport function predicting seepage erosion undercutting for cohesive bank failure prediction

    USDA-ARS?s Scientific Manuscript database

    Seepage erosion is an important factor in hillslope instability and failure. However, predicting erosion by subsurface flow or seepage and incorporating its effects into stability models remains a challenge. Limitations exist with all existing seepage erosion sediment transport functions, including ...

  8. INTEGRATING COMPUTATIONAL PROTEIN FUNCTION PREDICTION INTO DRUG DISCOVERY INITIATIVES

    PubMed Central

    Grant, Marianne A.

    2014-01-01

    Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes. PMID:25530654

  9. A Unitary Executive Function Predicts Intelligence in Children

    ERIC Educational Resources Information Center

    Brydges, Christopher R.; Reid, Corinne L.; Fox, Allison M.; Anderson, Mike

    2012-01-01

    Executive functions (EF) and intelligence are of critical importance to success in many everyday tasks. Working memory, or updating, which is one latent variable identified in confirmatory factor analytic models of executive functions, predicts intelligence (both fluid and crystallised) in adults, but inhibition and shifting do not (Friedman et…

  10. A Unitary Executive Function Predicts Intelligence in Children

    ERIC Educational Resources Information Center

    Brydges, Christopher R.; Reid, Corinne L.; Fox, Allison M.; Anderson, Mike

    2012-01-01

    Executive functions (EF) and intelligence are of critical importance to success in many everyday tasks. Working memory, or updating, which is one latent variable identified in confirmatory factor analytic models of executive functions, predicts intelligence (both fluid and crystallised) in adults, but inhibition and shifting do not (Friedman et…

  11. A critical assessment of topologically associating domain prediction tools

    PubMed Central

    Dali, Rola

    2017-01-01

    Abstract Topologically associating domains (TADs) have been proposed to be the basic unit of chromosome folding and have been shown to play key roles in genome organization and gene regulation. Several different tools are available for TAD prediction, but their properties have never been thoroughly assessed. In this manuscript, we compare the output of seven different TAD prediction tools on two published Hi-C data sets. TAD predictions varied greatly between tools in number, size distribution and other biological properties. Assessed against a manual annotation of TADs, individual TAD boundary predictions were found to be quite reliable, but their assembly into complete TAD structures was much less so. In addition, many tools were sensitive to sequencing depth and resolution of the interaction frequency matrix. This manuscript provides users and designers of TAD prediction tools with information that will help guide the choice of tools and the interpretation of their predictions. PMID:28334773

  12. A large-scale evaluation of computational protein function prediction.

    PubMed

    Radivojac, Predrag; Clark, Wyatt T; Oron, Tal Ronnen; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kaßner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Boehm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas A; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-03-01

    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 high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

  13. Protein Structure and Function Prediction Using I-TASSER.

    PubMed

    Yang, Jianyi; Zhang, Yang

    2015-12-17

    I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. Copyright © 2015 John Wiley & Sons, Inc.

  14. A large-scale evaluation of computational protein function prediction

    PubMed Central

    Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    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 high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

  15. Lung function indices for predicting mortality in COPD

    PubMed Central

    Boutou, Afroditi K.; Shrikrishna, Dinesh; Tanner, Rebecca J.; Smith, Cayley; Kelly, Julia L.; Ward, Simon P.; Polkey, Michael I.; Hopkinson, Nicholas S.

    2013-01-01

    Chronic obstructive pulmonary disease (COPD) is characterised by high morbidity and mortality. It remains unknown which aspect of lung function carries the most prognostic information and if simple spirometry is sufficient. Survival was assessed in COPD outpatients whose data had been added prospectively to a clinical audit database from the point of first full lung function testing including spirometry, lung volumes, gas transfer and arterial blood gases. Variables univariately associated with survival were entered into a multivariate Cox proportional hazard model. 604 patients were included (mean±sd age 61.9±9.7 years; forced expiratory volume in 1 s 37±18.1% predicted; 62.9% males); 229 (37.9%) died during a median follow-up of 83 months. Median survival was 91.9 (95% CI 80.8–103) months with survival rates at 3 and 5 years 0.83 and 0.66, respectively. Carbon monoxide transfer factor % pred quartiles (best quartile (>51%): HR 0.33, 95% CI 0.172–0.639; and second quartile (51–37.3%): HR 0.52, 95% CI 0.322–0.825; versus lowest quartile (<27.9%)), age (HR 1.04, 95% CI 1.02–1.06) and arterial oxygen partial pressure (HR 0.85, 95% CI 0.77–0.94) were the only parameters independently associated with mortality. Measurement of gas transfer provides additional prognostic information compared to spirometry in patients under hospital follow-up and could be considered routinely. PMID:23349449

  16. Relating Phylogenetic and Functional Diversity among Denitrifiers and Quantifying their Capacity to Predict Community Functioning.

    PubMed

    Salles, Joana Falcão; Le Roux, Xavier; Poly, Franck

    2012-01-01

    Genetic diversity of phylogenetic or functional markers is widely used as a proxy of microbial diversity. However, it remains unclear to what extent functional diversity (FD), gene sequence diversity and community functioning are linked. For a range of denitrifying bacteria, we analyzed the relationships between (i) the similarity of functional traits evaluated from metabolic profiles (BIOLOG plates) or from N(2)O accumulation patterns on different carbon sources and (ii) the similarity of phylogenetic (16S rRNA gene) or functional (nir gene) markers. We also calculated different proxies for the diversity of denitrifier community based on taxa richness, phylogenetic (16S rRNA gene) or functional similarities (based either on metabolic profiles or N(2)O accumulation patterns), and evaluated their performance in inferring the functioning of assembled denitrifying communities. For individual strains, the variation in the 16S rRNA gene sequence was weakly correlated with the variation in metabolic patterns (ρ = 0.35) and was not related to N(2)O accumulation. The latter was correlated with the similarity of nitrite reductase residues. When nir genes were analyzed separately, the similarity in amino acids coded by the nirS genes was highly correlated with the observed patterns of N(2)O accumulation (ρ = 0.62), whereas nirK amino acid residues were unrelated to N(2)O accumulation. For bacterial assemblages, phylogenetic diversity (average similarity among species in a community) and mean community dissimilarity (average distance between species) calculated using 16S rRNA gene sequences, and FD measures associated with metabolic profiles, poorly predicted the variation in the functioning of assembled communities (≤15%). In contrast, the proxies of FD based on N(2)O accumulation patterns performed better and explained from 23 to 42% of the variation in denitrification. Amongst those, community niche was the best metric, indicating the importance of

  17. Relating Phylogenetic and Functional Diversity among Denitrifiers and Quantifying their Capacity to Predict Community Functioning

    PubMed Central

    Salles, Joana Falcão; Le Roux, Xavier; Poly, Franck

    2012-01-01

    Genetic diversity of phylogenetic or functional markers is widely used as a proxy of microbial diversity. However, it remains unclear to what extent functional diversity (FD), gene sequence diversity and community functioning are linked. For a range of denitrifying bacteria, we analyzed the relationships between (i) the similarity of functional traits evaluated from metabolic profiles (BIOLOG plates) or from N2O accumulation patterns on different carbon sources and (ii) the similarity of phylogenetic (16S rRNA gene) or functional (nir gene) markers. We also calculated different proxies for the diversity of denitrifier community based on taxa richness, phylogenetic (16S rRNA gene) or functional similarities (based either on metabolic profiles or N2O accumulation patterns), and evaluated their performance in inferring the functioning of assembled denitrifying communities. For individual strains, the variation in the 16S rRNA gene sequence was weakly correlated with the variation in metabolic patterns (ρ = 0.35) and was not related to N2O accumulation. The latter was correlated with the similarity of nitrite reductase residues. When nir genes were analyzed separately, the similarity in amino acids coded by the nirS genes was highly correlated with the observed patterns of N2O accumulation (ρ = 0.62), whereas nirK amino acid residues were unrelated to N2O accumulation. For bacterial assemblages, phylogenetic diversity (average similarity among species in a community) and mean community dissimilarity (average distance between species) calculated using 16S rRNA gene sequences, and FD measures associated with metabolic profiles, poorly predicted the variation in the functioning of assembled communities (≤15%). In contrast, the proxies of FD based on N2O accumulation patterns performed better and explained from 23 to 42% of the variation in denitrification. Amongst those, community niche was the best metric, indicating the importance of complementarity for

  18. BLANNOTATOR: enhanced homology-based function prediction of bacterial proteins.

    PubMed

    Kankainen, Matti; Ojala, Teija; Holm, Liisa

    2012-02-15

    Automated function prediction has played a central role in determining the biological functions of bacterial proteins. Typically, protein function annotation relies on homology, and function is inferred from other proteins with similar sequences. This approach has become popular in bacterial genomics because it is one of the few methods that is practical for large datasets and because it does not require additional functional genomics experiments. However, the existing solutions produce erroneous predictions in many cases, especially when query sequences have low levels of identity with the annotated source protein. This problem has created a pressing need for improvements in homology-based annotation. We present an automated method for the functional annotation of bacterial protein sequences. Based on sequence similarity searches, BLANNOTATOR accurately annotates query sequences with one-line summary descriptions of protein function. It groups sequences identified by BLAST into subsets according to their annotation and bases its prediction on a set of sequences with consistent functional information. We show the results of BLANNOTATOR's performance in sets of bacterial proteins with known functions. We simulated the annotation process for 3090 SWISS-PROT proteins using a database in its state preceding the functional characterisation of the query protein. For this dataset, our method outperformed the five others that we tested, and the improved performance was maintained even in the absence of highly related sequence hits. We further demonstrate the value of our tool by analysing the putative proteome of Lactobacillus crispatus strain ST1. BLANNOTATOR is an accurate method for bacterial protein function prediction. It is practical for genome-scale data and does not require pre-existing sequence clustering; thus, this method suits the needs of bacterial genome and metagenome researchers. The method and a web-server are available at http://ekhidna.biocenter.helsinki.fi/poxo/blannotator/.

  19. Curved saccade trajectories reveal conflicting predictions in associative learning.

    PubMed

    Koenig, Stephan; Lachnit, Harald

    2011-09-01

    We report how the trajectories of saccadic eye movements are affected by memory interference acquired during associative learning. Human participants learned to perform saccadic choice responses based on the presentation of arbitrary central cues A, B, AC, BC, AX, BY, X, and Y that were trained to predict the appearance of a peripheral target stimulus at 1 of 3 possible locations, right (R), mid (M), or left (L), in the upper hemifield. We analyzed as measures of associative learning the frequency, latency, and curvature of saccades elicited by the cues and directed at the trained locations in anticipation of the targets. Participants were trained on two concurrent discrimination problems A+R, AC+R, AX+M, X+M and B+L, BC+L, BY+M, Y+M. From a connectionist perspective, cues were predicted to acquire associative links connecting the cues to the trained outcomes in memory. Model simulations based on the learning rule of the Rescorla and Wagner (1972) model revealed that for some cues, the prediction of the correct target location was challenged by the interfering prediction of an incorrect location. We observed that saccades directed at the correct location in anticipation of the target curved away from the location that was predicted by the interfering association. Furthermore, changes in curvature during training corresponded to predicted changes in associative memory. We propose that this curvature was caused by the inhibition of the incorrect prediction, as previously has been suggested with the concept of distractor inhibition (Sheliga, Riggio, & Rizzolatti, 1994; Tipper, Howard, & Houghton, 2000). The paradigm provides a new method to examine memory interference during associative learning.

  20. Functional Specialization and Flexibility in Human Association Cortex.

    PubMed

    Yeo, B T Thomas; Krienen, Fenna M; Eickhoff, Simon B; Yaakub, Siti N; Fox, Peter T; Buckner, Randy L; Asplund, Christopher L; Chee, Michael W L

    2015-10-01

    The association cortex supports cognitive functions enabling flexible behavior. Here, we explored the organization of human association cortex by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions. Application of the model to a large data set of neuroimaging experiments (N = 10 449) identified complex zones of frontal and parietal regions that ranged from being highly specialized to highly flexible. The network organization of the specialized and flexible regions was explored with an independent resting-state fMRI data set (N = 1000). Cortical regions specialized for the same components were strongly coupled, suggesting that components function as partially isolated networks. Functionally flexible regions participated in multiple components to different degrees. This heterogeneous selectivity was predicted by the connectivity between flexible and specialized regions. Functionally flexible regions might support binding or integrating specialized brain networks that, in turn, contribute to the ability to execute multiple and varied tasks.

  1. Prediction of protein function from protein sequence and structure.

    PubMed

    Whisstock, James C; Lesk, Arthur M

    2003-08-01

    The sequence of a genome contains the plans of the possible life of an organism, but implementation of genetic information depends on the functions of the proteins and nucleic acids that it encodes. Many individual proteins of known sequence and structure present challenges to the understanding of their function. In particular, a number of genes responsible for diseases have been identified but their specific functions are unknown. Whole-genome sequencing projects are a major source of proteins of unknown function. Annotation of a genome involves assignment of functions to gene products, in most cases on the basis of amino-acid sequence alone. 3D structure can aid the assignment of function, motivating the challenge of structural genomics projects to make structural information available for novel uncharacterized proteins. Structure-based identification of homologues often succeeds where sequence-alone-based methods fail, because in many cases evolution retains the folding pattern long after sequence similarity becomes undetectable. Nevertheless, prediction of protein function from sequence and structure is a difficult problem, because homologous proteins often have different functions. Many methods of function prediction rely on identifying similarity in sequence and/or structure between a protein of unknown function and one or more well-understood proteins. Alternative methods include inferring conservation patterns in members of a functionally uncharacterized family for which many sequences and structures are known. However, these inferences are tenuous. Such methods provide reasonable guesses at function, but are far from foolproof. It is therefore fortunate that the development of whole-organism approaches and comparative genomics permits other approaches to function prediction when the data are available. These include the use of protein-protein interaction patterns, and correlations between occurrences of related proteins in different organisms, as

  2. Predicting functional brain ROIs via fiber shape models.

    PubMed

    Zhang, Tuo; Guo, Lei; Li, Kaiming; Zhu, Dajing; Cui, Guangbin; Liu, Tianming

    2011-01-01

    Study of structural and functional connectivities of the human brain has received significant interest and effort recently. A fundamental question arises when attempting to measure the structural and/or functional connectivities of specific brain networks: how to best identify possible Regions of Interests (ROIs)? In this paper, we present a novel ROI prediction framework that localizes ROIs in individual brains based on learned fiber shape models from multimodal task-based fMRI and diffusion tensor imaging (DTI) data. In the training stage, ROIs are identified as activation peaks in task-based fMRI data. Then, shape models of white matter fibers emanating from these functional ROIs are learned. In addition, ROIs' location distribution model is learned to be used as an anatomical constraint. In the prediction stage, functional ROIs are predicted in individual brains based on DTI data. The ROI prediction is formulated and solved as an energy minimization problem, in which the two learned models are used as energy terms. Our experiment results show that the average ROI prediction error is 3.45 mm, in comparison with the benchmark data provided by working memory task-based fMRI. Promising results were also obtained on the ADNI-2 longitudinal DTI dataset.

  3. Genome-environment associations in sorghum landraces predict adaptive traits

    PubMed Central

    Lasky, Jesse R.; Upadhyaya, Hari D.; Ramu, Punna; Deshpande, Santosh; Hash, C. Tom; Bonnette, Jason; Juenger, Thomas E.; Hyma, Katie; Acharya, Charlotte; Mitchell, Sharon E.; Buckler, Edward S.; Brenton, Zachary; Kresovich, Stephen; Morris, Geoffrey P.

    2015-01-01

    Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. PMID:26601206

  4. PredictProtein--an open resource for online prediction of protein structural and functional features.

    PubMed

    Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

    2014-07-01

    PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein-protein binding sites (ISIS2), protein-polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. SitesIdentify: a protein functional site prediction tool

    PubMed Central

    2009-01-01

    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/ PMID:19922660

  6. Biochemical functional predictions for protein structures of unknown or uncertain function.

    PubMed

    Mills, Caitlyn L; Beuning, Penny J; Ondrechen, Mary Jo

    2015-01-01

    With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

  7. Gene function prediction based on the Gene Ontology hierarchical structure.

    PubMed

    Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

    2014-01-01

    The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

  8. Predicting regional neurodegeneration from the healthy brain functional connectome.

    PubMed

    Zhou, Juan; Gennatas, Efstathios D; Kramer, Joel H; Miller, Bruce L; Seeley, William W

    2012-03-22

    Neurodegenerative diseases target large-scale neural networks. Four competing mechanistic hypotheses have been proposed to explain network-based disease patterning: nodal stress, transneuronal spread, trophic failure, and shared vulnerability. Here, we used task-free fMRI to derive the healthy intrinsic connectivity patterns seeded by brain regions vulnerable to any of five distinct neurodegenerative diseases. These data enabled us to investigate how intrinsic connectivity in health predicts region-by-region vulnerability to disease. For each illness, specific regions emerged as critical network "epicenters" whose normal connectivity profiles most resembled the disease-associated atrophy pattern. Graph theoretical analyses in healthy subjects revealed that regions with higher total connectional flow and, more consistently, shorter functional paths to the epicenters, showed greater disease-related vulnerability. These findings best fit a transneuronal spread model of network-based vulnerability. Molecular pathological approaches may help clarify what makes each epicenter vulnerable to its targeting disease and how toxic protein species travel between networked brain structures.

  9. PREDICTION OF FUNCTIONAL MOVEMENT SCREEN™ PERFORMANCE FROM LOWER EXTREMITY RANGE OF MOTION AND CORE TESTS.

    PubMed

    Chimera, Nicole J; Knoeller, Shelby; Cooper, Ron; Kothe, Nicholas; Smith, Craig; Warren, Meghan

    2017-04-01

    There are varied reports in the literature regarding the association of the Functional Movement Screen™ (FMS™) with injury. The FMS™ has been correlated with hamstring range of motion and plank hold times; however, limited research is available on the predictability of lower extremity range of motion (ROM) and core function on FMS™ performance. The purpose of this study was to examine whether active lower extremity ROM measurements and core functional tests predict FMS™ performance. The authors hypothesized that lower extremity ROM and core functional tests would predict FMS™ composite score (CS) and performance on individual FMS™ fundamental movement patterns. Descriptive cohort study. Forty recreationally active participants had active lower extremity ROM measured, performed two core functional tests, the single leg wall sit hold (SLWS) and the repetitive single leg squat (RSLS), and performed the FMS™. Independent t tests were used to assess differences between right and left limb ROM measures and outcomes of core functional tests. Linear and ordinal logistic regressions were used to determine the best predictors of FMS™ CS and fundamental movement patterns, respectively. On the left side, reduced DF and SLWS significantly predicted lower FMS™ CS. On the right side only reduced DF significantly predicted lower FMS™ CS. Ordinal logistic regression models for the fundamental movement patterns demonstrated that reduced DF ROM was significantly associated with lower performance on deep squat. Reduced left knee extension was significantly associated with better performance in left straight leg raise; while reduced right hip flexion was significantly associated with reduced right straight leg raise. Lower SLWS was associated with reduced trunk stability performance. FMS™ movement patterns were affected by lower extremity ROM and core function. Researchers should consider lower FMS™ performance as indicative of underlying issues in ROM and

  10. Predicting species establishment using absent species and functional neighborhoods.

    PubMed

    Bennett, Jonathan A; Pärtel, Meelis

    2017-04-01

    Species establishment within a community depends on their interactions with the local environment and resident community. Such environmental and biotic filtering is frequently inferred from functional trait and phylogenetic patterns within communities; these patterns may also predict which additional species can establish. However, differentiating between environmental and biotic filtering can be challenging, which may complicate establishment predictions. Creating a habitat-specific species pool by identifying which absent species within the region can establish in the focal habitat allows us to isolate biotic filtering by modeling dissimilarity between the observed and biotically excluded species able to pass environmental filters. Similarly, modeling the dissimilarity between the habitat-specific species pool and the environmentally excluded species within the region can isolate local environmental filters. Combined, these models identify potentially successful phenotypes and why certain phenotypes were unsuccessful. Here, we present a framework that uses the functional dissimilarity among these groups in logistic models to predict establishment of additional species. This approach can use multivariate trait distances and phylogenetic information, but is most powerful when using individual traits and their interactions. It also requires an appropriate distance-based dissimilarity measure, yet the two most commonly used indices, nearest neighbor (one species) and mean pairwise (all species) distances, may inaccurately predict establishment. By iteratively increasing the number of species used to measure dissimilarity, a functional neighborhood can be chosen that maximizes the detection of underlying trait patterns. We tested this framework using two seed addition experiments in calcareous grasslands. Although the functional neighborhood size that best fits the community's trait structure depended on the type of filtering considered, selecting these functional

  11. 3D-Fun: predicting enzyme function from structure.

    PubMed

    von Grotthuss, Marcin; Plewczynski, Dariusz; Vriend, Gert; Rychlewski, Leszek

    2008-07-01

    The 'omics' revolution is causing a flurry of data that all needs to be annotated for it to become useful. Sequences of proteins of unknown function can be annotated with a putative function by comparing them with proteins of known function. This form of annotation is typically performed with BLAST or similar software. Structural genomics is nowadays also bringing us three dimensional structures of proteins with unknown function. We present here software that can be used when sequence comparisons fail to determine the function of a protein with known structure but unknown function. The software, called 3D-Fun, is implemented as a server that runs at several European institutes and is freely available for everybody at all these sites. The 3D-Fun servers accept protein coordinates in the standard PDB format and compare them with all known protein structures by 3D structural superposition using the 3D-Hit software. If structural hits are found with proteins with known function, these are listed together with their function and some vital comparison statistics. This is conceptually very similar in 3D to what BLAST does in 1D. Additionally, the superposition results are displayed using interactive graphics facilities. Currently, the 3D-Fun system only predicts enzyme function but an expanded version with Gene Ontology predictions will be available soon. The server can be accessed at http://3dfun.bioinfo.pl/ or at http://3dfun.cmbi.ru.nl/.

  12. Inference of Functional Relations in Predicted Protein Networks with a Machine Learning Approach

    PubMed Central

    Ezkurdia, Iakes; Andrés-León, Eduardo; Valencia, Alfonso

    2010-01-01

    Background Molecular biology is currently facing the challenging task of functionally characterizing the proteome. The large number of possible protein-protein interactions and complexes, the variety of environmental conditions and cellular states in which these interactions can be reorganized, and the multiple ways in which a protein can influence the function of others, requires the development of experimental and computational approaches to analyze and predict functional associations between proteins as part of their activity in the interactome. Methodology/Principal Findings We have studied the possibility of constructing a classifier in order to combine the output of the several protein interaction prediction methods. The AODE (Averaged One-Dependence Estimators) machine learning algorithm is a suitable choice in this case and it provides better results than the individual prediction methods, and it has better performances than other tested alternative methods in this experimental set up. To illustrate the potential use of this new AODE-based Predictor of Protein InterActions (APPIA), when analyzing high-throughput experimental data, we show how it helps to filter the results of published High-Throughput proteomic studies, ranking in a significant way functionally related pairs. Availability: All the predictions of the individual methods and of the combined APPIA predictor, together with the used datasets of functional associations are available at http://ecid.bioinfo.cnio.es/. Conclusions We propose a strategy that integrates the main current computational techniques used to predict functional associations into a unified classifier system, specifically focusing on the evaluation of poorly characterized protein pairs. We selected the AODE classifier as the appropriate tool to perform this task. AODE is particularly useful to extract valuable information from large unbalanced and heterogeneous data sets. The combination of the information provided by five

  13. Predictability of Genetic Interactions from Functional Gene Modules

    PubMed Central

    Young, Jonathan H.; Marcotte, Edward M.

    2016-01-01

    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. PMID:28007839

  14. Predicting enzymatic function from global binding site descriptors.

    PubMed

    Volkamer, Andrea; Kuhn, Daniel; Rippmann, Friedrich; Rarey, Matthias

    2013-03-01

    Due to the rising number of solved protein structures, computer-based techniques for automatic protein functional annotation and classification into families are of high scientific interest. DoGSiteScorer automatically calculates global descriptors for self-predicted pockets based on the 3D structure of a protein. Protein function predictors on three levels with increasing granularity are built by use of a support vector machine (SVM), based on descriptors of 26632 pockets from enzymes with known structure and enzyme classification. The SVM models represent a generalization of the available descriptor space for each enzyme class, subclass, and substrate-specific sub-subclass. Cross-validation studies show accuracies of 68.2% for predicting the correct main class and accuracies between 62.8% and 80.9% for the six subclasses. Substrate-specific recall rates for a kinase subset are 53.8%. Furthermore, application studies show the ability of the method for predicting the function of unknown proteins and gaining valuable information for the function prediction field. Copyright © 2012 Wiley Periodicals, Inc.

  15. Prediction of First Grade Social-Emotional and Intellectual Functioning.

    ERIC Educational Resources Information Center

    Kohn, Martin; And Others

    In order to determine the longitudinal persistence of two major personality dimensions, namely Apathy-Withdrawal versus Interest-Participation (Factor 1) and Anger-Defiance versus Conformity-Compliance (Factor 2), and to test the hypothesis that the social-emotional functioning of the preschool child is predictive of later intellectual-academic…

  16. Exploring Function Prediction in Protein Interaction Networks via Clustering Methods

    PubMed Central

    Trivodaliev, Kire; Bogojeska, Aleksandra; Kocarev, Ljupco

    2014-01-01

    Complex networks have recently become the focus of research in many fields. Their structure reveals crucial information for the nodes, how they connect and share information. In our work we analyze protein interaction networks as complex networks for their functional modular structure and later use that information in the functional annotation of proteins within the network. We propose several graph representations for the protein interaction network, each having different level of complexity and inclusion of the annotation information within the graph. We aim to explore what the benefits and the drawbacks of these proposed graphs are, when they are used in the function prediction process via clustering methods. For making this cluster based prediction, we adopt well established approaches for cluster detection in complex networks using most recent representative algorithms that have been proven as efficient in the task at hand. The experiments are performed using a purified and reliable Saccharomyces cerevisiae protein interaction network, which is then used to generate the different graph representations. Each of the graph representations is later analysed in combination with each of the clustering algorithms, which have been possibly modified and implemented to fit the specific graph. We evaluate results in regards of biological validity and function prediction performance. Our results indicate that the novel ways of presenting the complex graph improve the prediction process, although the computational complexity should be taken into account when deciding on a particular approach. PMID:24972109

  17. Human transfer functions used to predict system performance parameters

    NASA Technical Reports Server (NTRS)

    1966-01-01

    Automatic, parameter-tracking, model-matching technique compares the responses of a human operator with those of an analog computer model of a human operator to predict and analyze the performance of mechanical or electromechanical systems prior to construction. Transfer functions represent the input-output relation of an operator controlling a closed-loop system.

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

    PubMed Central

    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 (p<.001), associations with productivity (r=.51), mental health (r=.48), and distress (r=.47). Conclusions: The screener (WFS-H) had good predictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers. PMID:27010085

  19. Prediction error associated with the perceptual segmentation of naturalistic events.

    PubMed

    Zacks, Jeffrey M; Kurby, Christopher A; Eisenberg, Michelle L; Haroutunian, Nayiri

    2011-12-01

    Predicting the near future is important for survival and plays a central role in theories of perception, language processing, and learning. Prediction failures may be particularly important for initiating the updating of perceptual and memory systems and, thus, for the subjective experience of events. Here, we asked observers to make predictions about what would happen 5 sec later in a movie of an everyday activity. Those points where prediction was more difficult corresponded with subjective boundaries in the stream of experience. At points of unpredictability, midbrain and striatal regions associated with the phasic release of the neurotransmitter dopamine transiently increased in activity. This activity could provide a global updating signal, cuing other brain systems that a significant new event has begun.

  20. Can infant lung function predict respiratory morbidity during the first year of life in preterm infants?

    PubMed

    Proietti, Elena; Riedel, Thomas; Fuchs, Oliver; Pramana, Isabelle; Singer, Florian; Schmidt, Anne; Kuehni, Claudia; Latzin, Philipp; Frey, Urs

    2014-06-01

    Compared with term-born infants, preterm infants have increased respiratory morbidity in the first year of life. We investigated whether lung function tests performed near term predict subsequent respiratory morbidity during the first year of life and compared this to standard clinical parameters in preterms. The prospective birth cohort included randomly selected preterm infants with and without bronchopulmonary dysplasia. Lung function (tidal breathing and multiple-breath washout) was measured at 44 weeks post-menstrual age during natural sleep. We assessed respiratory morbidity (wheeze, hospitalisation, inhalation and home oxygen therapy) after 1 year using a standardised questionnaire. We first assessed the association between lung function and subsequent respiratory morbidity. Secondly, we compared the predictive power of standard clinical predictors with and without lung function data. In 166 preterm infants, tidal volume, time to peak tidal expiratory flow/expiratory time ratio and respiratory rate were significantly associated with subsequent wheeze. In comparison with standard clinical predictors, lung function did not improve the prediction of later respiratory morbidity in an individual child. Although associated with later wheeze, noninvasive infant lung function shows large physiological variability and does not add to clinically relevant risk prediction for subsequent respiratory morbidity in an individual preterm.

  1. Curved Saccade Trajectories Reveal Conflicting Predictions in Associative Learning

    ERIC Educational Resources Information Center

    Koenig, Stephan; Lachnit, Harald

    2011-01-01

    We report how the trajectories of saccadic eye movements are affected by memory interference acquired during associative learning. Human participants learned to perform saccadic choice responses based on the presentation of arbitrary central cues A, B, AC, BC, AX, BY, X, and Y that were trained to predict the appearance of a peripheral target…

  2. Implicit Alcohol Associations, Especially Drinking Identity, Predict Drinking Over Time

    PubMed Central

    Lindgren, Kristen P.; Neighbors, Clayton; Teachman, Bethany A.; Baldwin, Scott A.; Norris, Jeanette; Kaysen, Debra; Gasser, Melissa L.; Wiers, Reinout W.

    2016-01-01

    Objective There is considerable excitement about implicit alcohol associations (IAAs) as predictors of college student hazardous drinking; however, few studies have investigated IAAs prospectively, included multiple assessments, or controlled for previous drinking. Doing so is essential to show their utility as a predictor and, ultimately, target for screening or intervention. Therefore, three IAAs (drinking identity, alcohol approach, alcohol excitement) were evaluated as prospective predictors of drinking in first- and second-year US undergraduates. Method A sample of 506 undergraduates completed eight online assessments of IAAs, explicit measures of the IAA constructs, and hazardous drinking (consumption, problems, and risk of alcohol use disorders) every three months over a 21-month period. Retention rates, ordered by follow-up points were 90%, 76%, 76%, 77%, 72%, 67%, and 66%, respectively. Fifty percent of participants were non-drinkers at baseline; 21% were above clinical cutoffs for hazardous drinking. Results Drinking identity and alcohol excitement associations predicted future alcohol consumption and problems after controlling for previous drinking and explicit measures; drinking identity also predicted future risk of alcohol use disorder. Relative to the other IAAs, drinking identity predicted alcohol consumption for the longest duration (i.e., 21 months). Alcohol approach associations rarely predicted variance in drinking. Conclusions IAAs vary in their utility as prospective predictors of college student hazardous drinking. Drinking identity and, to a lesser extent, alcohol excitement emerged as robust prospective predictors of hazardous drinking. Intervention and screening efforts could likely benefit from targeting those associations. PMID:27505215

  3. Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors

    PubMed Central

    Guo, Maozu; Guo, Yahong; Li, Jinbao; Ding, Jian; Liu, Yong; Dai, Qiguo; Li, Jin; Teng, Zhixia; Huang, Yufei

    2013-01-01

    Background The identification of human disease-related microRNAs (disease miRNAs) is important for further investigating their involvement in the pathogenesis of diseases. More experimentally validated miRNA-disease associations have been accumulated recently. On the basis of these associations, it is essential to predict disease miRNAs for various human diseases. It is useful in providing reliable disease miRNA candidates for subsequent experimental studies. Methodology/Principal Findings It is known that miRNAs with similar functions are often associated with similar diseases and vice versa. Therefore, the functional similarity of two miRNAs has been successfully estimated by measuring the semantic similarity of their associated diseases. To effectively predict disease miRNAs, we calculated the functional similarity by incorporating the information content of disease terms and phenotype similarity between diseases. Furthermore, the members of miRNA family or cluster are assigned higher weight since they are more probably associated with similar diseases. A new prediction method, HDMP, based on weighted k most similar neighbors is presented for predicting disease miRNAs. Experiments validated that HDMP achieved significantly higher prediction performance than existing methods. In addition, the case studies examining prostatic neoplasms, breast neoplasms, and lung neoplasms, showed that HDMP can uncover potential disease miRNA candidates. Conclusions The superior performance of HDMP can be attributed to the accurate measurement of miRNA functional similarity, the weight assignment based on miRNA family or cluster, and the effective prediction based on weighted k most similar neighbors. The online prediction and analysis tool is freely available at http://nclab.hit.edu.cn/hdmpred. PMID:23950912

  4. Disorganized symptoms and executive functioning predict impaired social functioning in subjects at risk for psychosis.

    PubMed

    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.

  5. Structure-based Methods for Computational Protein Functional Site Prediction

    PubMed Central

    Dukka, B KC

    2013-01-01

    Due to the advent of high throughput sequencing techniques and structural genomic projects, the number of gene and protein sequences has been ever increasing. Computational methods to annotate these genes and proteins are even more indispensable. Proteins are important macromolecules and study of the function of proteins is an important problem in structural bioinformatics. This paper discusses a number of methods to predict protein functional site especially focusing on protein ligand binding site prediction. Initially, a short overview is presented on recent advances in methods for selection of homologous sequences. Furthermore, a few recent structural based approaches and sequence-and-structure based approaches for protein functional sites are discussed in details. PMID:24688745

  6. Protein Function Prediction Using Deep Restricted Boltzmann Machines

    PubMed Central

    Zou, Xianchun; Wang, Guijun

    2017-01-01

    Accurately annotating biological functions of proteins is one of the key tasks in the postgenome era. Many machine learning based methods have been applied to predict functional annotations of proteins, but this task is rarely solved by deep learning techniques. Deep learning techniques recently have been successfully applied to a wide range of problems, such as video, images, and nature language processing. Inspired by these successful applications, we investigate deep restricted Boltzmann machines (DRBM), a representative deep learning technique, to predict the missing functional annotations of partially annotated proteins. Experimental results on Homo sapiens, Saccharomyces cerevisiae, Mus musculus, and Drosophila show that DRBM achieves better performance than other related methods across different evaluation metrics, and it also runs faster than these comparing methods. PMID:28744460

  7. Automated protein function prediction--the genomic challenge.

    PubMed

    Friedberg, Iddo

    2006-09-01

    Overwhelmed with genomic data, biologists are facing the first big post-genomic question--what do all genes do? First, not only is the volume of pure sequence and structure data growing, but its diversity is growing as well, leading to a disproportionate growth in the number of uncharacterized gene products. Consequently, established methods of gene and protein annotation, such as homology-based transfer, are annotating less data and in many cases are amplifying existing erroneous annotation. Second, there is a need for a functional annotation which is standardized and machine readable so that function prediction programs could be incorporated into larger workflows. This is problematic due to the subjective and contextual definition of protein function. Third, there is a need to assess the quality of function predictors. Again, the subjectivity of the term 'function' and the various aspects of biological function make this a challenging effort. This article briefly outlines the history of automated protein function prediction and surveys the latest innovations in all three topics.

  8. Predicting plants -modeling traits as a function of environment

    NASA Astrophysics Data System (ADS)

    Franklin, Oskar

    2016-04-01

    A central problem in understanding and modeling vegetation dynamics is how to represent the variation in plant properties and function across different environments. Addressing this problem there is a strong trend towards trait-based approaches, where vegetation properties are functions of the distributions of functional traits rather than of species. Recently there has been enormous progress in in quantifying trait variability and its drivers and effects (Van Bodegom et al. 2012; Adier et al. 2014; Kunstler et al. 2015) based on wide ranging datasets on a small number of easily measured traits, such as specific leaf area (SLA), wood density and maximum plant height. However, plant function depends on many other traits and while the commonly measured trait data are valuable, they are not sufficient for driving predictive and mechanistic models of vegetation dynamics -especially under novel climate or management conditions. For this purpose we need a model to predict functional traits, also those not easily measured, and how they depend on the plants' environment. Here I present such a mechanistic model based on fitness concepts and focused on traits related to water and light limitation of trees, including: wood density, drought response, allocation to defense, and leaf traits. The model is able to predict observed patterns of variability in these traits in relation to growth and mortality, and their responses to a gradient of water limitation. The results demonstrate that it is possible to mechanistically predict plant traits as a function of the environment based on an eco-physiological model of plant fitness. References Adier, P.B., Salguero-Gómez, R., Compagnoni, A., Hsu, J.S., Ray-Mukherjee, J., Mbeau-Ache, C. et al. (2014). Functional traits explain variation in plant lifehistory strategies. Proc. Natl. Acad. Sci. U. S. A., 111, 740-745. Kunstler, G., Falster, D., Coomes, D.A., Hui, F., Kooyman, R.M., Laughlin, D.C. et al. (2015). Plant functional traits

  9. Extended Range Hydrological Predictions: Uncertainty Associated with Model Parametrization

    NASA Astrophysics Data System (ADS)

    Joseph, J.; Ghosh, S.; Sahai, A. K.

    2016-12-01

    The better understanding of various atmospheric processes has led to improved predictions of meteorological conditions at various temporal scale, ranging from short term which cover a period up to 2 days to long term covering a period of more than 10 days. Accurate prediction of hydrological variables can be done using these predicted meteorological conditions, which would be helpful in proper management of water resources. Extended range hydrological simulation includes the prediction of hydrological variables for a period more than 10 days. The main sources of uncertainty in hydrological predictions include the uncertainty in the initial conditions, meteorological forcing and model parametrization. In the present study, the Extended Range Prediction developed for India for monsoon by Indian Institute of Tropical Meteorology (IITM), Pune is used as meteorological forcing for the Variable Infiltration Capacity (VIC) model. Sensitive hydrological parameters, as derived from literature, along with a few vegetation parameters are assumed to be uncertain and 1000 random values are generated given their prescribed ranges. Uncertainty bands are generated by performing Monte-Carlo Simulations (MCS) for the generated sets of parameters and observed meteorological forcings. The basins with minimum human intervention, within the Indian Peninsular region, are identified and validation of results are carried out using the observed gauge discharge. Further, the uncertainty bands are generated for the extended range hydrological predictions by performing MCS for the same set of parameters and extended range meteorological predictions. The results demonstrate the uncertainty associated with the model parametrisation for the extended range hydrological simulations. Keywords: Extended Range Prediction, Variable Infiltration Capacity model, Monte Carlo Simulation.

  10. Predicting functional decline and survival in amyotrophic lateral sclerosis.

    PubMed

    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.

  11. Predicting functional decline and survival in amyotrophic lateral sclerosis

    PubMed Central

    Ong, Mei-Lyn; Tan, Pei Fang

    2017-01-01

    Background 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. Methods 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. Results 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. Conclusions 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. PMID:28406915

  12. Predicting bacterial fitness cost associated with drug resistance.

    PubMed

    Guo, Beining; Abdelraouf, Kamilia; Ledesma, Kimberly R; Nikolaou, Michael; Tam, Vincent H

    2012-04-01

    It has been proposed that antimicrobial resistance could be associated with a fitness cost in bacteria, which is often determined by competition experiments between isogenic strains (wild-type and mutant). However, this conventional approach is time consuming and labour intensive. An alternative method was developed to assess the fitness cost in drug-resistant bacteria. Time-growth studies were performed with approximately 1 × 10(5) cfu/mL of Acinetobacter baumannii or Pseudomonas aeruginosa at baseline. Serial samples were obtained to quantify the bacterial burden over 24 h. The growth rates (K(g)) of isogenic strains (antibiotic susceptible and resistant) were determined individually and used to predict their relative abundance in a co-culture over an extended period of time. The predicted difference between the two strains was subsequently validated by in vitro growth competition experiments. The growth rates of A. baumannii were not significantly different in different strengths of growth medium. The difference in bacterial burden observed in competition studies was in general agreement with the predicted difference based on K(g) values, suggesting good predicting ability of the mathematical model. The proposed mathematical model was found to be reasonable in characterizing bacterial growth and predicting the fitness cost of resistance. This simple method appears robust in the assessment of fitness cost associated with drug resistance and warrants further investigations.

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

    PubMed

    Amidi, Shervine; Amidi, Afshine; Vlachakis, Dimitrios; Paragios, Nikos; Zacharaki, Evangelia I

    2017-01-01

    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.

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

    PubMed Central

    Paragios, Nikos

    2017-01-01

    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. PMID:28367366

  15. Differential association between chronic cannabis use and brain function deficits.

    PubMed

    Soueif, M I

    1976-01-01

    To summarize, 12 objective tests that generated 16 test variables were administered to 850 male regular cannabis users and 839 nonusers. The tests were designed to assess various modalities, including speed of psychomotor performance, distance estimation, time estimation, immediate memory, and visuomotor coordination. Most of the test variables differentiated significantly between consumers and controls. At the same time, a significant second-order interaction emerged in most cases. This interaction meant that, under certain conditions that relate to the two dimensions "literacy-illiteracy" and/or "urbanism-ruralism," the superiority of controls over cannabis users became impressive, whereas under other conditions it almost disappeared. To account for this complex pattern of results, a working hypothesis was presented to the effect that "other conditions being equal, the lower the nondrug level of proficiency on tests of cognitive and psychomotor performance the smaller the size of function deficit associated with drug usage." For an empirical examination of the hypothesis, six predictions were formulated. Three predictions defined specific relationships between level of performance, on one hand, and each of three organismic variables, on the other: literacy, urbanism, and age. The remaining predictions delineated relationships to be expected between size of function deficit and the three organismic variables. All our predictions were confirmed, showing less function impairment to be contingent with cannabis usage among the illiterates, rurals, and older subjects. Level of cortical arousal was suggested as the central process associated with the three organismic variables. Because the version of our working hypothesis was formulated with reference to chronic material, the possibility of a transposition of the paradign to research on the acute effects of the drug was discussed. The suggestion was made that our working hypothesis, in either version, is capable of

  16. Predicting protein function and other biomedical characteristics with heterogeneous ensembles

    PubMed Central

    Whalen, Sean; Pandey, Om Prakash

    2015-01-01

    Prediction problems in biomedical sciences, including protein function prediction (PFP), are generally quite difficult. This is due in part to incomplete knowledge of the cellular phenomenon of interest, the appropriateness and data quality of the variables and measurements used for prediction, as well as a lack of consensus regarding the ideal predictor for specific problems. In such scenarios, a powerful approach to improving prediction performance is to construct heterogeneous ensemble predictors that combine the output of diverse individual predictors that capture complementary aspects of the problems and/or datasets. In this paper, we demonstrate the potential of such heterogeneous ensembles, derived from stacking and ensemble selection methods, for addressing PFP and other similar biomedical prediction problems. Deeper analysis of these results shows that the superior predictive ability of these methods, especially stacking, can be attributed to their attention to the following aspects of the ensemble learning process: (i) better balance of diversity and performance, (ii) more effective calibration of outputs and (iii) more robust incorporation of additional base predictors. Finally, to make the effective application of heterogeneous ensembles to large complex datasets (big data) feasible, we present DataSink, a distributed ensemble learning framework, and demonstrate its sound scalability using the examined datasets. DataSink is publicly available from https://github.com/shwhalen/datasink. PMID:26342255

  17. Inductive matrix completion for predicting gene-disease associations.

    PubMed

    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 <15% chance. We demonstrate that the inductive method is particularly effective for a query disease with no previously known gene associations, and for predicting novel genes, i.e. genes that are previously not linked to diseases. Thus the method is capable of predicting novel genes even for well-characterized diseases. We also validate the novelty of predictions by evaluating the method on recently reported OMIM associations and on associations recently reported in the literature

  18. Inductive matrix completion for predicting gene–disease associations

    PubMed Central

    Natarajan, Nagarajan; Dhillon, Inderjit S.

    2014-01-01

    Motivation: 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. Results: 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 <15% chance. We demonstrate that the inductive method is particularly effective for a query disease with no previously known gene associations, and for predicting novel genes, i.e. genes that are previously not linked to diseases. Thus the method is capable of predicting novel genes even for well-characterized diseases. We also validate the novelty of predictions by evaluating the method on recently reported OMIM associations and on associations recently

  19. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function.

    PubMed

    Hancock, Dana B; Eijgelsheim, Mark; Wilk, Jemma B; Gharib, Sina A; Loehr, Laura R; Marciante, Kristin D; Franceschini, Nora; van Durme, Yannick M T A; Chen, Ting-Hsu; Barr, R Graham; Schabath, Matthew B; Couper, David J; Brusselle, Guy G; Psaty, Bruce M; van Duijn, Cornelia M; Rotter, Jerome I; Uitterlinden, André G; Hofman, Albert; Punjabi, Naresh M; Rivadeneira, Fernando; Morrison, Alanna C; Enright, Paul L; North, Kari E; Heckbert, Susan R; Lumley, Thomas; Stricker, Bruno H C; O'Connor, George T; London, Stephanie J

    2010-01-01

    Spirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV(1)) and its ratio to forced vital capacity (FEV(1)/FVC), an indicator of airflow obstruction. This meta-analysis included 20,890 participants of European ancestry from four CHARGE Consortium studies: Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study and Rotterdam Study. We identified eight loci associated with FEV(1)/FVC (HHIP, GPR126, ADAM19, AGER-PPT2, FAM13A, PTCH1, PID1 and HTR4) and one locus associated with FEV(1) (INTS12-GSTCD-NPNT) at or near genome-wide significance (P < 5 x 10(-8)) in the CHARGE Consortium dataset. Our findings may offer insights into pulmonary function and pathogenesis of chronic lung disease.

  20. On the estimation of risk associated with an attenuation prediction

    NASA Technical Reports Server (NTRS)

    Crane, R. K.

    1992-01-01

    Viewgraphs from a presentation on the estimation of risk associated with an attenuation prediction is presented. Topics covered include: link failure - attenuation exceeding a specified threshold for a specified time interval or intervals; risk - the probability of one or more failures during the lifetime of the link or during a specified accounting interval; the problem - modeling the probability of attenuation by rainfall to provide a prediction of the attenuation threshold for a specified risk; and an accounting for the inadequacy of a model or models.

  1. Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

    PubMed Central

    Shoichet, Brian K.; Gillis, Jesse

    2016-01-01

    The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA: sea.docking.org), where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63–0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited. PMID:27467773

  2. Protein function prediction using local 3D templates.

    PubMed

    Laskowski, Roman A; Watson, James D; Thornton, Janet M

    2005-08-19

    The prediction of a protein's function from its 3D structure is becoming more and more important as the worldwide structural genomics initiatives gather pace and continue to solve 3D structures, many of which are of proteins of unknown function. Here, we present a methodology for predicting function from structure that shows great promise. It is based on 3D templates that are defined as specific 3D conformations of small numbers of residues. We use four types of template, covering enzyme active sites, ligand-binding residues, DNA-binding residues and reverse templates. The latter are templates generated from the target structure itself and scanned against a representative subset of all known protein structures. Together, the templates provide a fairly thorough coverage of the known structures and ensure that if there is a match to a known structure it is unlikely to be missed. A new scoring scheme provides a highly sensitive means of discriminating between true positive and false positive template matches. In all, the methodology provides a powerful new tool for function prediction to complement those already in use.

  3. Predicting acute recovery of physical function following total knee joint arthroplasty.

    PubMed

    Robbins, Shawn M; Rastogi, Ravi; McLaughlin, Terry-Lyne

    2014-02-01

    The objective was to explore predictors of physical function during acute in-patient rehabilitation within a few days after TKA. Physical function status of participants (n = 72) three days after total knee arthroplasty (TKA) was measured using the Timed Up and Go Test (TUG) and the function subscale of the Western Ontario McMaster Universities Index of Osteoarthritis (WOMAC-function). Potential predictors of physical function were measured day one post-TKA. Their relationship with physical function was examined using backward elimination, multiple regression analyses. Older age and increased comorbidity were associated (R(2) = 0.20) with worse TUG times. Increased pain severity was associated (R(2) = 0.08) with worse WOMAC-function scores. Age, comorbidity, and pain severity should be considered when predicting which patients will struggle with acute recovery post-TKA.

  4. Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations.

    PubMed

    Martelotto, Luciano G; Ng, Charlotte Ky; De Filippo, Maria R; Zhang, Yan; Piscuoglio, Salvatore; Lim, Raymond S; Shen, Ronglai; Norton, Larry; Reis-Filho, Jorge S; Weigelt, Britta

    2014-10-28

    Massively parallel sequencing studies have led to the identification of a large number of mutations present in a minority of cancers of a given site. Hence, methods to identify the likely pathogenic mutations that are worth exploring experimentally and clinically are required. We sought to compare the performance of 15 mutation effect prediction algorithms and their agreement. As a hypothesis-generating aim, we sought to define whether combinations of prediction algorithms would improve the functional effect predictions of specific mutations. Literature and database mining of single nucleotide variants (SNVs) affecting 15 cancer genes was performed to identify mutations supported by functional evidence or hereditary disease association to be classified either as non-neutral (n = 849) or neutral (n = 140) with respect to their impact on protein function. These SNVs were employed to test the performance of 15 mutation effect prediction algorithms. The accuracy of the prediction algorithms varies considerably. Although all algorithms perform consistently well in terms of positive predictive value, their negative predictive value varies substantially. Cancer-specific mutation effect predictors display no-to-almost perfect agreement in their predictions of these SNVs, whereas the non-cancer-specific predictors showed no-to-moderate agreement. Combinations of predictors modestly improve accuracy and significantly improve negative predictive values. The information provided by mutation effect predictors is not equivalent. No algorithm is able to predict sufficiently accurately SNVs that should be taken forward for experimental or clinical testing. Combining algorithms aggregates orthogonal information and may result in improvements in the negative predictive value of mutation effect predictions.

  5. Incremental fuzzy mining of gene expression data for gene function prediction.

    PubMed

    Ma, Patrick C H; Chan, Keith C C

    2011-05-01

    Due to the complexity of the underlying biological processes, gene expression data obtained from DNA microarray technologies are typically noisy and have very high dimensionality and these make the mining of such data for gene function prediction very difficult. To tackle these difficulties, we propose to use an incremental fuzzy mining technique called incremental fuzzy mining (IFM). By transforming quantitative expression values into linguistic terms, such as highly or lowly expressed, IFM can effectively capture heterogeneity in expression data for pattern discovery. It does so using a fuzzy measure to determine if interesting association patterns exist between the linguistic gene expression levels. Based on these patterns, IFM can make accurate gene function predictions and these predictions can be made in such a way that each gene can be allowed to belong to more than one functional class with different degrees of membership. Gene function prediction problem can be formulated both as classification and clustering problems, and IFM can be used either as a classification technique or together with existing clustering algorithms to improve the cluster groupings discovered for greater prediction accuracies. IFM is characterized also by its being an incremental data mining technique so that the discovered patterns can be continually refined based only on newly collected data without the need for retraining using the whole dataset. For performance evaluation, IFM has been tested with real expression datasets for both classification and clustering tasks. Experimental results show that it can effectively uncover hidden patterns for accurate gene function predictions. © 2011 IEEE

  6. Functional analysis of variance for association studies.

    PubMed

    Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Greenwood, Mark C; Wei, Changshuai; Lu, Qing

    2014-01-01

    While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods - SKAT and a previously proposed method based on functional linear models (FLM), - especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM) to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity.

  7. COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps.

    PubMed

    Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P; Kasif, Simon; Roberts, Richard J; Steffen, Martin

    2016-01-04

    The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼ 3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue.

  8. Plant functional traits predict green roof ecosystem services.

    PubMed

    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.

  9. The association between personal care products and lung function.

    PubMed

    Dales, Robert E; Cakmak, Sabit; Leech, Judith; Liu, Ling

    2013-02-01

    Chemical exposures are important determinants of respiratory health. The objective of the present study was to determine the association between the use of personal care products, which may contain respirable components, and lung function. Using questionnaire and spirometry data collected during the Canadian Health Measures population survey, the association was tested between 1-second forced expiratory volume (FEV(l)) and forced vital capacity (FVC) expressed as a percentage of predicted, and the frequency of use of personal care products categorized as eye makeup, fragrances, hairstyle products, lipstick, and scented body products. Five thousand sixteen of the 5604 participants in the survey reported using at least one personal care product in the past 3 months. Among men and women, an interquartile increase in hairstyle products was associated with an approximate 2% decrease in both FEV(1) and FVC (P < .05). Among women, each product category was associated with a significant decrease in lung function with the largest observed effect being a 4.08% (95% confidence interval, 7.71-0.45) decrease in FVC associated with an interquartile range increase in the frequency of use of scented body products. This study provides data suggesting that using personal care products may have a small adverse effect on lung function. Further research is warranted to investigate this possibility. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  10. Accurate perception of negative emotions predicts functional capacity in schizophrenia.

    PubMed

    Abram, Samantha V; Karpouzian, Tatiana M; Reilly, James L; Derntl, Birgit; Habel, Ute; Smith, Matthew J

    2014-04-30

    Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration.

  11. Optimizing Non-Decomposable Loss Functions in Structured Prediction

    PubMed Central

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N.; Li, Ze-Nian; Mori, Greg

    2012-01-01

    We develop an algorithm for structured prediction with non-decomposable performance measures. The algorithm learns parameters of Markov random fields and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines) and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a quadratic program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset. PMID:22868650

  12. Ferromagnetic elements by epitaxial growth: A density functional prediction

    NASA Astrophysics Data System (ADS)

    Schönecker, Stephan; Richter, Manuel; Koepernik, Klaus; Eschrig, Helmut

    2012-01-01

    The periodic table contains only six natural elements with a ferromagnetic ground state. For example, the metal uranium, which is magnetically ordered in many compounds, is paramagnetic in all its known elemental bulk phases. Also, the iron-group elements ruthenium and osmium are known to be bulk paramagnets. We predict by means of density functional calculations that epitaxial growth of uranium, ruthenium, or osmium on suitable substrates may allow stabilization of bulklike films with tetragonal structures showing ferromagnetic order.

  13. High Precision Prediction of Functional Sites in Protein Structures

    PubMed Central

    Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

    2014-01-01

    We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

  14. Functional MRI in Awake Dogs Predicts Suitability for Assistance Work

    NASA Astrophysics Data System (ADS)

    Berns, Gregory S.; Brooks, Andrew M.; Spivak, Mark; Levy, Kerinne

    2017-03-01

    The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17-21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs’ subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala.

  15. Functional MRI in Awake Dogs Predicts Suitability for Assistance Work

    PubMed Central

    Berns, Gregory S.; Brooks, Andrew M.; Spivak, Mark; Levy, Kerinne

    2017-01-01

    The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17–21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs’ subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala. PMID:28266550

  16. Functional MRI in Awake Dogs Predicts Suitability for Assistance Work.

    PubMed

    Berns, Gregory S; Brooks, Andrew M; Spivak, Mark; Levy, Kerinne

    2017-03-07

    The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17-21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs' subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala.

  17. Predictions of Geospace Drivers By the Probability Distribution Function Model

    NASA Astrophysics Data System (ADS)

    Bussy-Virat, C.; Ridley, A. J.

    2014-12-01

    Geospace drivers like the solar wind speed, interplanetary magnetic field (IMF), and solar irradiance have a strong influence on the density of the thermosphere and the near-Earth space environment. This has important consequences on the drag on satellites that are in low orbit and therefore on their position. One of the basic problems with space weather prediction is that these drivers can only be measured about one hour before they affect the environment. In order to allow for adequate planning for some members of the commercial, military, or civilian communities, reliable long-term space weather forecasts are needed. The study presents a model for predicting geospace drivers up to five days in advance. This model uses the same general technique to predict the solar wind speed, the three components of the IMF, and the solar irradiance F10.7. For instance, it uses Probability distribution functions (PDFs) to relate the current solar wind speed and slope to the future solar wind speed, as well as the solar wind speed to the solar wind speed one solar rotation in the future. The PDF Model has been compared to other models for predictions of the speed. It has been found that it is better than using the current solar wind speed (i.e., persistence), and better than the Wang-Sheeley-Arge Model for prediction horizons of 24 hours. Once the drivers are predicted, and the uncertainty on the drivers are specified, the density in the thermosphere can be derived using various models of the thermosphere, such as the Global Ionosphere Thermosphere Model. In addition, uncertainties on the densities can be estimated, based on ensembles of simulations. From the density and uncertainty predictions, satellite positions, as well as the uncertainty in those positions can be estimated. These can assist operators in determining the probability of collisions between objects in low Earth orbit.

  18. Asian Summer Monsoon Rainfall associated with ENSO and its Predictability

    NASA Astrophysics Data System (ADS)

    Shin, C. S.; Huang, B.; Zhu, J.; Marx, L.; Kinter, J. L.; Shukla, J.

    2015-12-01

    The leading modes of the Asian summer monsoon (ASM) rainfall variability and their seasonal predictability are investigated using the CFSv2 hindcasts initialized from multiple ocean analyses over the period of 1979-2008 and observation-based analyses. It is shown that the two leading empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies, which together account for about 34% of total variance, largely correspond to the ASM responses to the ENSO influences during the summers of the developing and decaying years of a Pacific anomalous event, respectively. These two ASM modes are then designated as the contemporary and delayed ENSO responses, respectively. It is demonstrated that the CFSv2 is capable of predicting these two dominant ASM modes up to the lead of 5 months. More importantly, the predictability of the ASM rainfall are much higher with respect to the delayed ENSO mode than the contemporary one, with the predicted principal component time series of the former maintaining high correlation skill and small ensemble spread with all lead months whereas the latter shows significant degradation in both measures with lead-time. A composite analysis for the ASM rainfall anomalies of all warm ENSO events in this period substantiates the finding that the ASM is more predictable following an ENSO event. The enhanced predictability mainly comes from the evolution of the warm SST anomalies over the Indian Ocean in the spring of the ENSO maturing phases and the persistence of the anomalous high sea surface pressure over the western Pacific in the subsequent summer, which the hindcasts are able to capture reasonably well. The results also show that the ensemble initialization with multiple ocean analyses improves the CFSv2's prediction skill of both ENSO and ASM rainfall. In fact, the skills of the ensemble mean hindcasts initialized from the four different ocean analyses are always equivalent to the best ones initialized from any individual ocean

  19. ESCRT functions in autophagy and associated disease.

    PubMed

    Rusten, Tor Erik; Simonsen, Anne

    2008-05-01

    Mutations in the endosomal sorting complexes required for transport (ESCRT)-III subunit CHMP2B are associated with frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), both human neurodegenerative diseases characterized by accumulation of ubiquitinated proteins aggregates in affected neurons. The ESCRT proteins are known to be involved in diverse cellular processes such as mRNA transport, cytokinesis, transcriptional regulation and sorting of transmembrane proteins into the inner vesicles of the multivesicular body (MVB) during endocytosis. It was until recently not clear how ESCRT function may be involved in neurodegeneration. New findings in mammalian cells and in Drosophila melanogaster show that functional ESCRTs are required for efficient fusion of autophagic vesicles with the endocytic pathway and for degradation of autophagic cargo. Moreover, defective ESCRT function led to the accumulation of cytoplasmic protein aggregates containing ubiquitin, p62/Sequestosome-1 and TAR DNA binding protein 43 (TDP-43). Using cellular and Drosophila models for Huntington's disease it was also shown that reduced ESCRT levels inhibit clearance of expanded polyglutamine aggregates and aggravate their neurotoxic effect. These data indicate that efficient autophagic degradation requires functional MVBs and provides a possible explanation to the observed neurodegenerative phenotype seen in patients with CHMP2B mutations.

  20. WBSMDA: Within and Between Score for MiRNA-Disease Association prediction

    PubMed Central

    Chen, Xing; Yan, Chenggang Clarence; Zhang, Xu; You, Zhu-Hong; Deng, Lixi; Liu, Ying; Zhang, Yongdong; Dai, Qionghai

    2016-01-01

    Increasing evidences have indicated that microRNAs (miRNAs) are functionally associated with the development and progression of various complex human diseases. However, the roles of miRNAs in multiple biological processes or various diseases and their underlying molecular mechanisms still have not been fully understood yet. Predicting potential miRNA-disease associations by integrating various heterogeneous biological datasets is of great significance to the biomedical research. Computational methods could obtain potential miRNA-disease associations in a short time, which significantly reduce the experimental time and cost. Considering the limitations in previous computational methods, we developed the model of Within and Between Score for MiRNA-Disease Association prediction (WBSMDA) to predict potential miRNAs associated with various complex diseases. WBSMDA could be applied to the diseases without any known related miRNAs. The AUC of 0.8031 based on Leave-one-out cross validation has demonstrated its reliable performance. WBSMDA was further applied to Colon Neoplasms, Prostate Neoplasms, and Lymphoma for the identification of their potential related miRNAs. As a result, 90%, 84%, and 80% of predicted miRNA-disease pairs in the top 50 prediction list for these three diseases have been confirmed by recent experimental literatures, respectively. It is anticipated that WBSMDA would be a useful resource for potential miRNA-disease association identification. PMID:26880032

  1. Functional brain imaging predicts public health campaign success.

    PubMed

    Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

    2016-02-01

    Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns.

  2. Functional brain imaging predicts public health campaign success

    PubMed Central

    O’Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

    2016-01-01

    Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. PMID:26400858

  3. Origin and Functional Prediction of Pollen Allergens in Plants.

    PubMed

    Chen, Miaolin; Xu, Jie; Devis, Deborah; Shi, Jianxin; Ren, Kang; Searle, Iain; Zhang, Dabing

    2016-09-01

    Pollen allergies have long been a major pandemic health problem for human. However, the evolutionary events and biological function of pollen allergens in plants remain largely unknown. Here, we report the genome-wide prediction of pollen allergens and their biological function in the dicotyledonous model plant Arabidopsis (Arabidopsis thaliana) and the monocotyledonous model plant rice (Oryza sativa). In total, 145 and 107 pollen allergens were predicted from rice and Arabidopsis, respectively. These pollen allergens are putatively involved in stress responses and metabolic processes such as cell wall metabolism during pollen development. Interestingly, these putative pollen allergen genes were derived from large gene families and became diversified during evolution. Sequence analysis across 25 plant species from green alga to angiosperms suggest that about 40% of putative pollen allergenic proteins existed in both lower and higher plants, while other allergens emerged during evolution. Although a high proportion of gene duplication has been observed among allergen-coding genes, our data show that these genes might have undergone purifying selection during evolution. We also observed that epitopes of an allergen might have a biological function, as revealed by comprehensive analysis of two known allergens, expansin and profilin. This implies a crucial role of conserved amino acid residues in both in planta biological function and allergenicity. Finally, a model explaining how pollen allergens were generated and maintained in plants is proposed. Prediction and systematic analysis of pollen allergens in model plants suggest that pollen allergens were evolved by gene duplication and then functional specification. This study provides insight into the phylogenetic and evolutionary scenario of pollen allergens that will be helpful to future characterization and epitope screening of pollen allergens. © 2016 American Society of Plant Biologists. All rights reserved.

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

    PubMed

    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.

  5. Using the functional response of a consumer to predict biotic resistance to invasive prey.

    PubMed

    Twardochleb, Laura A; Novak, Mark; Moore, Jonathan W

    2012-06-01

    Predators sometimes provide biotic resistance against invasions by nonnative prey. Understanding and predicting the strength of biotic resistance remains a key challenge in invasion biology. A predator's functional response to nonnative prey may predict whether a predator can provide biotic resistance against nonnative prey at different prey densities. Surprisingly, functional responses have not been used to make quantitative predictions about biotic resistance. We parameterized the functional response of signal crayfish (Pacifastacus leniusculus) to invasive New Zealand mud snails (Potamopyrgus antipodarum; NZMS) and used this functional response and a simple model of NZMS population growth to predict the probability of biotic resistance at different predator and prey densities. Signal crayfish were effective predators of NZMS, consuming more than 900 NZMS per predator in a 12-h period, and Bayesian model fitting indicated their consumption rate followed a type 3 functional response to NZMS density. Based on this functional response and associated parameter uncertainty, we predict that NZMS will be able to invade new systems at low crayfish densities (< 0.2 crayfish/m2) regardless of NZMS density. At intermediate to high crayfish densities (> 0.2 crayfish/m2), we predict that low densities of NZMS will be able to establish in new communities; however, once NZMS reach a threshold density of -2000 NZMS/m2, predation by crayfish will drive negative NZMS population growth. Further, at very high densities, NZMS overwhelm predation by crayfish and invade. Thus, interacting thresholds of propagule pressure and predator densities define the probability of biotic resistance. Quantifying the shape and uncertainty of predator functional responses to nonnative prey may help predict the outcomes of invasions.

  6. Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

    PubMed

    Lefcheck, Jonathan S; Duffy, J Emmett

    2015-11-01

    The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context.

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

    PubMed Central

    Wong, Aloysius; Gehring, Chris; 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. PMID:26106597

  8. PBHMDA: Path-Based Human Microbe-Disease Association Prediction

    PubMed Central

    Huang, Zhi-An; Chen, Xing; Zhu, Zexuan; Liu, Hongsheng; Yan, Gui-Ying; You, Zhu-Hong; Wen, Zhenkun

    2017-01-01

    With the advance of sequencing technology and microbiology, the microorganisms have been found to be closely related to various important human diseases. The increasing identification of human microbe-disease associations offers important insights into the underlying disease mechanism understanding from the perspective of human microbes, which are greatly helpful for investigating pathogenesis, promoting early diagnosis and improving precision medicine. However, the current knowledge in this domain is still limited and far from complete. Here, we present the computational model of Path-Based Human Microbe-Disease Association prediction (PBHMDA) based on the integration of known microbe-disease associations and the Gaussian interaction profile kernel similarity for microbes and diseases. A special depth-first search algorithm was implemented to traverse all possible paths between microbes and diseases for inferring the most possible disease-related microbes. As a result, PBHMDA obtained a reliable prediction performance with AUCs (The area under ROC curve) of 0.9169 and 0.8767 in the frameworks of both global and local leave-one-out cross validations, respectively. Based on 5-fold cross validation, average AUCs of 0.9082 ± 0.0061 further demonstrated the efficiency of the proposed model. For the case studies of liver cirrhosis, type 1 diabetes, and asthma, 9, 7, and 9 out of predicted microbes in the top 10 have been confirmed by previously published experimental literatures, respectively. We have publicly released the prioritized microbe-disease associations, which may help to select the most potential pairs for further guiding the experimental confirmation. In conclusion, PBHMDA may have potential to boost the discovery of novel microbe-disease associations and aid future research efforts toward microbe involvement in human disease mechanism. The code and data of PBHMDA is freely available at http://www.escience.cn/system/file?fileId=85214. PMID:28275370

  9. PBHMDA: Path-Based Human Microbe-Disease Association Prediction.

    PubMed

    Huang, Zhi-An; Chen, Xing; Zhu, Zexuan; Liu, Hongsheng; Yan, Gui-Ying; You, Zhu-Hong; Wen, Zhenkun

    2017-01-01

    With the advance of sequencing technology and microbiology, the microorganisms have been found to be closely related to various important human diseases. The increasing identification of human microbe-disease associations offers important insights into the underlying disease mechanism understanding from the perspective of human microbes, which are greatly helpful for investigating pathogenesis, promoting early diagnosis and improving precision medicine. However, the current knowledge in this domain is still limited and far from complete. Here, we present the computational model of Path-Based Human Microbe-Disease Association prediction (PBHMDA) based on the integration of known microbe-disease associations and the Gaussian interaction profile kernel similarity for microbes and diseases. A special depth-first search algorithm was implemented to traverse all possible paths between microbes and diseases for inferring the most possible disease-related microbes. As a result, PBHMDA obtained a reliable prediction performance with AUCs (The area under ROC curve) of 0.9169 and 0.8767 in the frameworks of both global and local leave-one-out cross validations, respectively. Based on 5-fold cross validation, average AUCs of 0.9082 ± 0.0061 further demonstrated the efficiency of the proposed model. For the case studies of liver cirrhosis, type 1 diabetes, and asthma, 9, 7, and 9 out of predicted microbes in the top 10 have been confirmed by previously published experimental literatures, respectively. We have publicly released the prioritized microbe-disease associations, which may help to select the most potential pairs for further guiding the experimental confirmation. In conclusion, PBHMDA may have potential to boost the discovery of novel microbe-disease associations and aid future research efforts toward microbe involvement in human disease mechanism. The code and data of PBHMDA is freely available at http://www.escience.cn/system/file?fileId=85214.

  10. Predicting functional outcomes among college drinkers: reliability and predictive validity of the Young Adult Alcohol Consequences Questionnaire.

    PubMed

    Read, Jennifer P; Merrill, Jennifer E; Kahler, Christopher W; Strong, David R

    2007-11-01

    Heavy drinking and associated consequences are widespread among U.S. college students. Recently, Read et al. (Read, J. P., Kahler, C. W., Strong, D., & Colder, C. R. (2006). Development and preliminary validation of the Young Adult Alcohol Consequences Questionnaire. Journal of Studies on Alcohol, 67, 169-178) developed the Young Adult Alcohol Consequences Questionnaire (YAACQ) to assess the broad range of consequences that may result from heavy drinking in the college milieu. In the present study, we sought to add to the psychometric validation of this measure by employing a prospective design to examine the test-retest reliability, concurrent validity, and predictive validity of the YAACQ. We also sought to examine the utility of the YAACQ administered early in the semester in the prediction of functional outcomes later in the semester, including the persistence of heavy drinking, and academic functioning. Ninety-two college students (48 females) completed a self-report assessment battery during the first weeks of the Fall semester, and approximately one week later. Additionally, 64 subjects (37 females) participated at an optional third time point at the end of the semester. Overall, the YAACQ demonstrated strong internal consistency, test-retest reliability, and concurrent and predictive validity. YAACQ scores also were predictive of both drinking frequency, and "binge" drinking frequency. YAACQ total scores at baseline were an early indicator of academic performance later in the semester, with greater number of total consequences experienced being negatively associated with end-of-semester grade point average. Specific YAACQ subscale scores (Impaired Control, Dependence Symptoms, Blackout Drinking) showed unique prediction of persistent drinking and academic outcomes.

  11. Motor functioning differentially predicts mortality in men and women.

    PubMed

    Bravell, Marie Ernsth; Finkel, Deborah; Dahl Aslan, Anna; Reynolds, Chandra A; Hallgren, Jenny; Pedersen, Nancy L

    2017-09-01

    Research indicates gender differences in functional performance at advanced ages, but little is known about their impact on longevity for men and women. To derive a set of motor function factors from a battery of functional performance measures and examine their associations with mortality, incorporating possible gender interactions. Analyses were performed on the longitudinal Swedish Adoption/Twin Study of Aging (SATSA) including twenty-four assessments of motor function up to six times over a 19-year period. Three motor factors were derived from several factor analyses; fine motor, balance/upper strength, and flexibility. A latent growth curve model was used to capture longitudinal age changes in the motor factors and generated estimates of intercept at age 70 (I), rates of change before (S1) and after age 70 (S2) for each factor. Cox regression models were used to determine how gender in interaction with the motor factors was related to mortality. Females demonstrated lower functional performance in all motor functions relative to men. Cox regression survival analyses demonstrated that both balance/upper strength, and fine motor function were significantly related to mortality. Gender specific analyses revealed that this was true for women only. For men, none of the motor factors were related to mortality. Women demonstrated more difficulties in all functioning facets, and only among women were motor functioning (balance/upper strength and fine motor function) associated with mortality. These results provide evidence for the importance of considering motor functioning, and foremost observed gender differences when planning for individualized treatment and rehabilitation. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Predicting Cognitive Function from Clinical Measures of Physical Function and Health Status in Older Adults

    PubMed Central

    Bolandzadeh, Niousha; Kording, Konrad; Salowitz, Nicole; Davis, Jennifer C.; Hsu, Liang; Chan, Alison; Sharma, Devika; Blohm, Gunnar; Liu-Ambrose, Teresa

    2015-01-01

    Introduction Current research suggests that the neuropathology of dementia—including brain changes leading to memory impairment and cognitive decline—is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies. Methods We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1–L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation. Results Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year. Discussion We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a

  13. Cardiorespiratory function associated with dietary nitrate supplementation

    PubMed Central

    Bond, Vernon; Curry, Bryan H.; Adams, Richard G.; Millis, Richard M.; Haddad, Georges E.

    2014-01-01

    The advent of medical nutrition therapy and nutritional physiology affords the opportunity to link diet to specific cardiovascular mechanisms, suggesting novel treatments for cardiovascular disease. This study tests the hypothesis that beetroot juice increases the plasma nitric oxide (NO) concentration, which is associated with improvements in cardiorespiratory function at rest and during submaximal aerobic exercise. The subjects were 12 healthy, young adult, normotensive African-American females, with a body mass of 61 ± 2 kg, body fat of 28% ± 4%, and peak oxygen consumption of 26 ± 3 mL·kg−1·min−1. The subjects were studied at rest and during cycle ergometer exercise at 40%, 60%, and 80% of peak oxygen consumption. Plasma NO concentration, respiratory quotient (RQ), minute ventilation, systolic and diastolic blood pressure (SBP and DBP), heart rate, and oxygen consumption were compared between isocaloric, isovolumetric placebo control orange juice and experimental beetroot juice treatments on separate days. The beetroot juice treatment increased plasma NO concentration and decreased oxygen consumption, SBP, and the heart rate-SBP product at rest and at 40%, 60%, and 80% of peak oxygen consumption in the absence of significant effects on RQ, minute ventilation, heart rate, and DBP. These findings suggest that, in healthy subjects, beetroot juice treatments increase plasma NO concentration and decrease cardiac afterload and myocardial oxygen demand at rest and during 3 submaximal levels of aerobic exercise. Future studies should determine the cellular and molecular mechanisms responsible for the improvement in cardiorespiratory function associated with dietary nitrate supplementation and whether they translate into better cardiovascular function and exercise tolerance in individuals with a compromised cardiovascular system. PMID:24476472

  14. An empirical propellant response function for combustion stability predictions

    NASA Technical Reports Server (NTRS)

    Hessler, R. O.

    1980-01-01

    An empirical response function model was developed for ammonium perchlorate propellants to supplant T-burner testing at the preliminary design stage. The model was developed by fitting a limited T-burner data base, in terms of oxidizer size and concentration, to an analytical two parameter response function expression. Multiple peaks are predicted, but the primary effect is of a single peak for most formulations, with notable bulges for the various AP size fractions. The model was extended to velocity coupling with the assumption that dynamic response was controlled primarily by the solid phase described by the two parameter model. The magnitude of velocity coupling was then scaled using an erosive burning law. Routine use of the model for stability predictions on a number of propulsion units indicates that the model tends to overpredict propellant response. It is concluded that the model represents a generally conservative prediction tool, suited especially for the preliminary design stage when T-burner data may not be readily available. The model work included development of a rigorous summation technique for pseudopropellant properties and of a concept for modeling ordered packing of particulates.

  15. Integrating phenotype and gene expression data for predicting gene function.

    PubMed

    Malone, Brandon M; Perkins, Andy D; Bridges, Susan M

    2009-10-08

    This paper presents a framework for integrating disparate data sets to predict gene function. The algorithm constructs a graph, called an integrated similarity graph, by computing similarities based upon both gene expression and textual phenotype data. This integrated graph is then used to make predictions about whether individual genes should be assigned a particular annotation from the Gene Ontology. A combined graph was generated from publicly-available gene expression data and phenotypic information from Saccharomyces cerevisiae. This graph was used to assign annotations to genes, as were graphs constructed from gene expression data and textual phenotype information alone. While the F-measure appeared similar for all three methods, annotations based upon the integrated similarity graph exhibited a better overall precision than gene expression or phenotype information alone can generate. The integrated approach was also able to assign almost as many annotations as the gene expression method alone, and generated significantly more total and correct assignments than the phenotype information could provide. These results suggest that augmenting standard gene expression data sets with publicly-available textual phenotype data can help generate more precise functional annotation predictions while mitigating the weaknesses of a standard textual phenotype approach.

  16. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    PubMed Central

    Kasess, Christian H.; Meyer, Bernhard M.; Hofmaier, Tina; Diers, Kersten; Bartova, Lucie; Pail, Gerald; Huf, Wolfgang; Uzelac, Zeljko; Hartinger, Beate; Kalcher, Klaudius; Perkmann, Thomas; Haslacher, Helmuth; Meyer-Lindenberg, Andreas; Kasper, Siegfried; Freissmuth, Michael; Windischberger, Christian; Willeit, Matthäus; Lanzenberger, Rupert; Esterbauer, Harald; Brocke, Burkhard; Moser, Ewald; Sitte, Harald H.; Pezawas, Lukas

    2014-01-01

    Background The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. Methods A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet Vmax. Results The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity. Conclusion This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation. PMID:24667541

  17. Predictive computation of genomic logic processing functions in embryonic development

    PubMed Central

    Peter, Isabelle S.; Faure, Emmanuel; Davidson, Eric H.

    2012-01-01

    Gene regulatory networks (GRNs) control the dynamic spatial patterns of regulatory gene expression in development. Thus, in principle, GRN models may provide system-level, causal explanations of developmental process. To test this assertion, we have transformed a relatively well-established GRN model into a predictive, dynamic Boolean computational model. This Boolean model computes spatial and temporal gene expression according to the regulatory logic and gene interactions specified in a GRN model for embryonic development in the sea urchin. Additional information input into the model included the progressive embryonic geometry and gene expression kinetics. The resulting model predicted gene expression patterns for a large number of individual regulatory genes each hour up to gastrulation (30 h) in four different spatial domains of the embryo. Direct comparison with experimental observations showed that the model predictively computed these patterns with remarkable spatial and temporal accuracy. In addition, we used this model to carry out in silico perturbations of regulatory functions and of embryonic spatial organization. The model computationally reproduced the altered developmental functions observed experimentally. Two major conclusions are that the starting GRN model contains sufficiently complete regulatory information to permit explanation of a complex developmental process of gene expression solely in terms of genomic regulatory code, and that the Boolean model provides a tool with which to test in silico regulatory circuitry and developmental perturbations. PMID:22927416

  18. Multiscale prediction of patient-specific platelet function under flow.

    PubMed

    Flamm, Matthew H; Colace, Thomas V; Chatterjee, Manash S; Jing, Huiyan; Zhou, Songtao; Jaeger, Daniel; Brass, Lawrence F; Sinno, Talid; Diamond, Scott L

    2012-07-05

    During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient's platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donor's pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y(1) inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subject's platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.

  19. Nanoparticles-cell association predicted by protein corona fingerprints

    NASA Astrophysics Data System (ADS)

    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

  20. The predictability of molecular evolution during functional innovation.

    PubMed

    Blank, Diana; Wolf, Luise; Ackermann, Martin; Silander, Olin K

    2014-02-25

    Determining the molecular changes that give rise to functional innovations is a major unresolved problem in biology. The paucity of examples has served as a significant hindrance in furthering our understanding of this process. Here we used experimental evolution with the bacterium Escherichia coli to quantify the molecular changes underlying functional innovation in 68 independent instances ranging over 22 different metabolic functions. Using whole-genome sequencing, we show that the relative contribution of regulatory and structural mutations depends on the cellular context of the metabolic function. In addition, we find that regulatory mutations affect genes that act in pathways relevant to the novel function, whereas structural mutations affect genes that act in unrelated pathways. Finally, we use population genetic modeling to show that the relative contributions of regulatory and structural mutations during functional innovation may be affected by population size. These results provide a predictive framework for the molecular basis of evolutionary innovation, which is essential for anticipating future evolutionary trajectories in the face of rapid environmental change.

  1. Personality predicts cognitive function over 7 years in older persons.

    PubMed

    Chapman, Benjamin; Duberstein, Paul; Tindle, Hilary A; Sink, Kaycee M; Robbins, John; Tancredi, Daniel J; Franks, Peter

    2012-07-01

    To determine whether Neuroticism as well as the less-studied dimensions the Five Factor Model of personality (Extraversion, Openness to Experience, Agreeableness, and Conscientiousness) were associated with 7-year trajectories of cognitive functioning in older persons. Primary analysis of existing clinical trial data. 602 persons of average age 79 at baseline. The NEO-Five Factor Inventory of personality, completed at baseline, and the Modified Mini-Mental State Examination measured every 6 months for 7 years. Controlling for demographics, baseline morbidities including depression, health behaviors, apolipoprotein E4 genotype, and self-rated health, higher Neuroticism was associated with worse average cognitive functioning and a steeper rate of decline over follow-up. Higher Extraversion and lower Openness were both associated with worse average cognitive functioning prospectively, while persons higher in Conscientiousness showed a slower rate of cognitive decline. In addition to Neuroticism, other dispositional tendencies appear prognostically relevant for cognitive functioning in older persons. More work is needed to understand the mechanisms by which traits operate, as well as whether mitigation of certain dispositional tendencies can facilitate a better course of cognitive function.

  2. Personality Predicts Cognitive Function Over Seven Years in Older Persons

    PubMed Central

    Chapman, Benjamin; Duberstein, Paul; Tindle, Hilary A; Sink, Kaycee M; Robbins, John; Tancredi, Daniel J.; Franks, Peter

    2011-01-01

    Objectives To determine whether Neuroticism, as well as the less-studied dimensions the Five Factor Model of personality (Extraversion, Openness to Experience, Agreeableness, and Conscientiousness) were associated with 7-year trajectories of cognitive functioning in older persons. Design Primary analysis of existing clinical trial data. Participants 602 persons of average age 79 at baseline. Measurements The NEO-Five Factor Inventory of personality, completed at baseline, and the modified Mini Mental Status Exam (3MSE) measured every 6 months for 7 years. Results Controlling for demographics, baseline morbidities including depression, health behaviors, Apolipoprotein E4 genotype, and self-rated health, higher Neuroticism was associated with worse average cognitive functioning and a steeper rate of decline over follow-up. Higher Extraversion and lower Openness were both associated with worse average cognitive functioning prospectively, while persons higher in Conscientiousness showed a slower rate of cognitive decline. Conclusions In addition to Neuroticism, other dispositional tendencies appear prognostically relevant for cognitive functioning in older persons. More work is needed to understand the mechanisms by which traits operate, as well as whether mitigation of certain dispositional tendencies can facilitate a better course of cognitive function. PMID:22735597

  3. Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity

    PubMed Central

    Khalsa, Sakh; Mayhew, Stephen D.; Przezdzik, Izabela; Wilson, Rebecca; Hale, Joanne; Goldstone, Aimee; Bagary, Manny; Bagshaw, Andrew P.

    2016-01-01

    Study Objectives: We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). Methods: Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). Results: cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. Conclusions: This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link

  4. Finding directionality and gene-disease predictions in disease associations.

    PubMed

    Garcia-Albornoz, Manuel; Nielsen, Jens

    2015-07-15

    Understanding the underlying molecular mechanisms in human diseases is important for diagnosis and treatment of complex conditions and has traditionally been done by establishing associations between disorder-genes and their associated diseases. This kind of network analysis usually includes only the interaction of molecular components and shared genes. The present study offers a network and association analysis under a bioinformatics frame involving the integration of HUGO Gene Nomenclature Committee approved gene symbols, KEGG metabolic pathways and ICD-10-CM codes for the analysis of human diseases based on the level of inclusion and hypergeometric enrichment between genes and metabolic pathways shared by the different human disorders. The present study offers the integration of HGNC approved gene symbols, KEGG metabolic pathways andICD-10-CM codes for the analysis of associations based on the level of inclusion and hypergeometricenrichment between genes and metabolic pathways shared by different diseases. 880 unique ICD-10-CM codes were mapped to the 4315 OMIM phenotypes and 3083 genes with phenotype-causing mutation. From this, a total of 705 ICD-10-CM codes were linked to 1587 genes with phenotype-causing mutations and 801 KEGG pathways creating a tripartite network composed by 15,455 code-gene-pathway interactions. These associations were further used for an inclusion analysis between diseases along with gene-disease predictions based on a hypergeometric enrichment methodology. The results demonstrate that even though a large number of genes and metabolic pathways are shared between diseases of the same categories, inclusion levels between these genes and pathways are directional and independent of the disease classification. However, the gene-disease-pathway associations can be used for prediction of new gene-disease interactions that will be useful in drug discovery and therapeutic applications.

  5. iPFPi: A System for Improving Protein Function Prediction through Cumulative Iterations.

    PubMed

    Taha, Kamal; Yoo, Paul D; Alzaabi, Mohammed

    2015-01-01

    We propose a classifier system called iPFPi that predicts the functions of un-annotated proteins. iPFPi assigns an un-annotated protein P the functions of GO annotation terms that are semantically similar to P. An un-annotated protein P and a GO annotation term T are represented by their characteristics. The characteristics of P are GO terms found within the abstracts of biomedical literature associated with P. The characteristics of Tare GO terms found within the abstracts of biomedical literature associated with the proteins annotated with the function of T. Let F and F/ be the important (dominant) sets of characteristic terms representing T and P, respectively. iPFPi would annotate P with the function of T, if F and F/ are semantically similar. We constructed a novel semantic similarity measure that takes into consideration several factors, such as the dominance degree of each characteristic term t in set F based on its score, which is a value that reflects the dominance status of t relative to other characteristic terms, using pairwise beats and looses procedure. Every time a protein P is annotated with the function of T, iPFPi updates and optimizes the current scores of the characteristic terms for T based on the weights of the characteristic terms for P. Set F will be updated accordingly. Thus, the accuracy of predicting the function of T as the function of subsequent proteins improves. This prediction accuracy keeps improving over time iteratively through the cumulative weights of the characteristic terms representing proteins that are successively annotated with the function of T. We evaluated the quality of iPFPi by comparing it experimentally with two recent protein function prediction systems. Results showed marked improvement.

  6. Confronting species distribution model predictions with species functional traits.

    PubMed

    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.

  7. Prediction of functional residues in water channels and related proteins.

    PubMed Central

    Froger, A.; Tallur, B.; Thomas, D.; Delamarche, C.

    1998-01-01

    In this paper, we present an updated classification of the ubiquitous MIP (Major Intrinsic Protein) family proteins, including 153 fully or partially sequenced members available in public databases. Presently, about 30 of these proteins have been functionally characterized, exhibiting essentially two distinct types of channel properties: (1) specific water transport by the aquaporins, and (2) small neutral solutes transport, such as glycerol by the glycerol facilitators. Sequence alignments were used to predict amino acids and motifs discriminant in channel specificity. The protein sequences were also analyzed using statistical tools (comparisons of means and correspondence analysis). Five key positions were clearly identified where the residues are specific for each functional subgroup and exhibit high dissimilar physico-chemical properties. Moreover, we have found that the putative channels for small neutral solutes clearly differ from the aquaporins by the amino acid content and the length of predicted loop regions, suggesting a substrate filter function for these loops. From these results, we propose a signature pattern for water transport. PMID:9655351

  8. Understanding and predicting ground behavior associated with trenchless operations

    SciTech Connect

    Chapman, D.N.; Rogers, C.D.F.

    1996-08-01

    This paper aims to provide a state-of-the-art review of literature related to both ground behaviour associated with trenchless service installation techniques and the methods available for predicting this ground behavior. The paper concentrates on four specific methods of trenchless installation: pipejacking (including microtunnelling), pipebursting, steerable moling (including its relationship with directional drilling) and impact moling. It is shown that, with the possible exception of pipebursting, there is a lack of field information available to make judgements on the precise effects of the operations on adjacent sub-structures and surface structures. Nevertheless accurate prediction is possible using a combination of simple theoretical models and a geotechnically based appreciation of the various stresses and forced displacements that occur during any one operation. Recommendations are made for future areas of work to improve current knowledge.

  9. An expanded evaluation of protein function prediction methods shows an improvement in accuracy.

    PubMed

    Jiang, Yuxiang; Oron, Tal Ronnen; Clark, Wyatt T; Bankapur, Asma R; D'Andrea, Daniel; Lepore, Rosalba; Funk, Christopher S; Kahanda, Indika; Verspoor, Karin M; Ben-Hur, Asa; Koo, Da Chen Emily; Penfold-Brown, Duncan; Shasha, Dennis; Youngs, Noah; Bonneau, Richard; Lin, Alexandra; Sahraeian, Sayed M E; Martelli, Pier Luigi; Profiti, Giuseppe; Casadio, Rita; Cao, Renzhi; Zhong, Zhaolong; Cheng, Jianlin; Altenhoff, Adrian; Skunca, Nives; Dessimoz, Christophe; Dogan, Tunca; Hakala, Kai; Kaewphan, Suwisa; Mehryary, Farrokh; Salakoski, Tapio; Ginter, Filip; Fang, Hai; Smithers, Ben; Oates, Matt; Gough, Julian; Törönen, Petri; Koskinen, Patrik; Holm, Liisa; Chen, Ching-Tai; Hsu, Wen-Lian; Bryson, Kevin; Cozzetto, Domenico; Minneci, Federico; Jones, David T; Chapman, Samuel; Bkc, Dukka; Khan, Ishita K; Kihara, Daisuke; Ofer, Dan; Rappoport, Nadav; Stern, Amos; Cibrian-Uhalte, Elena; Denny, Paul; Foulger, Rebecca E; Hieta, Reija; Legge, Duncan; Lovering, Ruth C; Magrane, Michele; Melidoni, Anna N; Mutowo-Meullenet, Prudence; Pichler, Klemens; Shypitsyna, Aleksandra; Li, Biao; Zakeri, Pooya; ElShal, Sarah; Tranchevent, Léon-Charles; Das, Sayoni; Dawson, Natalie L; Lee, David; Lees, Jonathan G; Sillitoe, Ian; Bhat, Prajwal; Nepusz, Tamás; Romero, Alfonso E; Sasidharan, Rajkumar; Yang, Haixuan; Paccanaro, Alberto; Gillis, Jesse; Sedeño-Cortés, Adriana E; Pavlidis, Paul; Feng, Shou; Cejuela, Juan M; Goldberg, Tatyana; Hamp, Tobias; Richter, Lothar; Salamov, Asaf; Gabaldon, Toni; Marcet-Houben, Marina; Supek, Fran; Gong, Qingtian; Ning, Wei; Zhou, Yuanpeng; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Toppo, Stefano; Ferrari, Carlo; Giollo, Manuel; Piovesan, Damiano; Tosatto, Silvio C E; Del Pozo, Angela; Fernández, José M; Maietta, Paolo; Valencia, Alfonso; Tress, Michael L; Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Rehman, Hafeez Ur; Re, Matteo; Mesiti, Marco; Valentini, Giorgio; Bargsten, Joachim W; van Dijk, Aalt D J; Gemovic, Branislava; Glisic, Sanja; Perovic, Vladmir; Veljkovic, Veljko; Veljkovic, Nevena; Almeida-E-Silva, Danillo C; Vencio, Ricardo Z N; Sharan, Malvika; Vogel, Jörg; Kansakar, Lakesh; Zhang, Shanshan; Vucetic, Slobodan; Wang, Zheng; Sternberg, Michael J E; Wass, Mark N; Huntley, Rachael P; Martin, Maria J; O'Donovan, Claire; Robinson, Peter N; Moreau, Yves; Tramontano, Anna; Babbitt, Patricia C; Brenner, Steven E; Linial, Michal; Orengo, Christine A; Rost, Burkhard; Greene, Casey S; Mooney, Sean D; Friedberg, Iddo; Radivojac, Predrag

    2016-09-07

    A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.

  10. Prediction of Dislocation Cores in Aluminum from Density Functional Theory

    NASA Astrophysics Data System (ADS)

    Woodward, C.; Trinkle, D. R.; Hector, L. G., Jr.; Olmsted, D. L.

    2008-02-01

    The strain field of isolated screw and edge dislocation cores in aluminum are calculated using density-functional theory and a flexible boundary condition method. Nye tensor density contours and differential displacement fields are used to accurately bound Shockley partial separation distances. Our results of 5 7.5 Å (screw) and 7.0 9.5 Å (edge) eliminate uncertainties resulting from the wide range of previous results based on Peierls-Nabarro and atomistic methods. Favorable agreement of the predicted cores with limited experimental measurements demonstrates the need for quantum mechanical treatment of dislocation cores.

  11. Pediatric brain injury: Can DTI scalars predict functional outcome?

    PubMed Central

    Xu, Duan; Mukherjee, Pratik; Barkovich, A James

    2013-01-01

    Diffusion imaging has made significant inroads into the clinical diagnosis of a variety of diseases by inferring changes in microstructure, namely cell membranes, myelin sheath and other structures that inhibit water diffusion. This review discusses recent progress in the use of diffusion parameters in predicting functional outcome. Studies in the literature using only scalar parameters from diffusion measurements, such as apparent diffusion coefficient (ADC) and fractional anisotropy (FA), are summarized. Other more complex mathematical models and post-processing uses are also discussed briefly. PMID:23288477

  12. Associations between Markers of Glucose and Insulin Function and Cognitive Function in Healthy African American Elders

    PubMed Central

    Skinner, Jeannine S.; Morgan, Amy; Hernandez-Saucedo, Hector; Hansen, Angela; Corbett, Selena; Arbuckle, Matthew; Leverenz, James BA; Wilkins, Consuelo H.; Craft, Suzanne; Baker, Laura D.

    2015-01-01

    Background Glucose and insulin are important moderators of cognitive function. African Americans have poorer glycemic control across the glycemic spectrum and are at increased risk for type 2 diabetes and poor cognitive health. It is unclear which glucoregulatory markers predict cognitive function in this at-risk population. The purpose of this study was to examine the association between cognitive function and common markers of glucoregulation in non-diabetic African Americans elders. Methods Thirty-four, community-dwelling African Americans, aged 50-75 years completed cognitive testing and blood collection as part of a health screening assessment. Cognitive outcomes were composite scores derived from neuropsychological tests of executive function and verbal memory. Linear regression was used to examine relationships between cognitive composite scores and fasting blood levels of glucose, insulin, and hemoglobin A1C, with adjustments for age, education, body mass index, and antihypertensive medication use. Results Fasting plasma glucose was negatively associated with executive function (β=−0.41, p=0.03). There was a trend of an association between fasting plasma glucose and verbal memory (β=−0.34, p=0.06). Fasting insulin and hemoglobin A1c were not associated with cognitive function. Conclusion High non-diabetic fasting glucose levels were associated with poorer executive function and verbal memory. These results provide preliminary support for proactive glucose control in older African Americans even before glycemic criteria for type 2 diabetes are met. Our findings suggests that high-normal FPG levels may represent an early red-flag to signify increased risk of cognitive impairment or decline. PMID:26798567

  13. Prediction of functional rehabilitation outcomes in clients with stroke.

    PubMed

    Man, David Wai-Kwong; Tam, Sing Fai; Hui-Chan, Christina

    2006-02-01

    To evaluate the validity of the Neurobehavioral Cognitive Status Examination (NCSE or Cognistat) and to determine its effects in order to estimate the functional outcomes of survivors with stroke. The present study first studied the factor structure NCSE in 148 Chinese survivors with stroke (aged 45-91 years). They were admitted to hospital consecutively and recruited prospectively. The relationship of NCSE with Functional Independence Measures (FIM), a set of measures commonly adopted as an indicator of the outcome of rehabilitation, was studied. One hundred and forty-eight patients with stroke (49.3% male, 50.7% female), with a mean age of 70.38 and an average number of years of education of 3.50 years joined the study. A two-factor NCSE structure was obtained, namely verbal-spatial and integrated cognition, accounting for 62.77% of the variance. A significant relationship between NCSE factors and the functional status of clients with stroke on admission and upon discharge, as well as age, years of education and length of hospital stay were indicated. This study supports a systematic relationship between cognitive factors and functional outcome in Chinese patients with stroke. Similarities and differences in the NCSE factor structure between the population with stroke and general neurological populations were discussed and the utility of NCSE in stroke rehabilitation, such as its predictive validity in functional independence is suggested.

  14. Muscle Strength Predicts Changes in Physical Function in Women with Systemic Lupus Erythematosus

    PubMed Central

    Andrews, James S.; Trupin, Laura; Schmajuk, Gabriela; Barton, Jennifer; Margaretten, Mary; Yazdany, Jinoos; Yelin, Edward H.; Katz, Patricia P.

    2015-01-01

    Objective Cross-sectional studies have observed that muscle weakness is associated with worse physical function among women with systemic lupus erythematosus (SLE). The present study examines whether reduced upper and lower extremity muscle strength predict declines in function over time among adult women with SLE. Methods One hundred forty-six women from a longitudinal SLE cohort participated in the study. All measures were collected during in-person research visits approximately 2 years apart. Upper extremity muscle strength was assessed by grip strength. Lower extremity muscle strength was assessed by peak knee torque of extension and flexion. Physical function was assessed using the Short Physical Performance Battery (SPPB). Regression analyses modeled associations of baseline upper and lower extremity muscle strength with follow-up SPPB scores controlling for baseline SPPB, age, SLE duration, SLE disease activity (Systemic Lupus Activity Questionnaire [SLAQ]), physical activity level, prednisone use, body composition, and depression. Secondary analyses tested whether associations of baseline muscle strength with follow-up in SPPB scores differed between intervals of varying baseline muscle strength. Results Lower extremity muscle strength strongly predicted changes over 2 years in physical function even when controlling for covariates. The association of reduced lower extremity muscle strength with reduced future physical function was greatest among the weakest women. Conclusions Reduced lower extremity muscle strength predicted clinically significant declines in physical function, especially among the weakest women. Future studies should test whether therapies that promote preservation of lower extremity muscle strength may prevent declines in function among women with SLE. PMID:25623919

  15. Defining Predictive Probability Functions for Species Sampling Models.

    PubMed

    Lee, Jaeyong; Quintana, Fernando A; Müller, Peter; Trippa, Lorenzo

    2013-01-01

    We review the class of species sampling models (SSM). In particular, we investigate the relation between the exchangeable partition probability function (EPPF) and the predictive probability function (PPF). It is straightforward to define a PPF from an EPPF, but the converse is not necessarily true. In this paper we introduce the notion of putative PPFs and show novel conditions for a putative PPF to define an EPPF. We show that all possible PPFs in a certain class have to define (unnormalized) probabilities for cluster membership that are linear in cluster size. We give a new necessary and sufficient condition for arbitrary putative PPFs to define an EPPF. Finally, we show posterior inference for a large class of SSMs with a PPF that is not linear in cluster size and discuss a numerical method to derive its PPF.

  16. Predicting Infrared Spectra of Nerve Agents Using Density Functional Theory

    NASA Astrophysics Data System (ADS)

    Zhang, Y.-P.; Wang, H.-T.; Zheng, W.-P.; Sun, C.; Bai, Y.; Guo, X.-D.; Sun, H.

    2016-09-01

    Vibration frequencies of four nerve agents and two simulators are calculated using B3LYP coupled with ten basis sets. To evaluate the accuracy of calculated spectra, root mean square error (RMSE) and weighted cross-correlation average (WCCA) are considered. The evaluation shows that B3LYP/6-311+g(d,p) performs best in predicting infrared spectra, and polarization functions are found to be more important than diffusion functions in spectra simulation. Moreover, B3LYP calculation underestimates frequencies related to the P atom. The WCCA metric derives 1.008 as a unique scaling factor for calculated frequencies. The results indicate that the WCCA metric can identify six agents based on calculated spectra.

  17. Functional Specialization and Flexibility in Human Association Cortex

    PubMed Central

    Yeo, B. T. Thomas; Krienen, Fenna M.; Eickhoff, Simon B.; Yaakub, Siti N.; Fox, Peter T.; Buckner, Randy L.; Asplund, Christopher L.; Chee, Michael W.L.

    2015-01-01

    The association cortex supports cognitive functions enabling flexible behavior. Here, we explored the organization of human association cortex by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions. Application of the model to a large data set of neuroimaging experiments (N = 10 449) identified complex zones of frontal and parietal regions that ranged from being highly specialized to highly flexible. The network organization of the specialized and flexible regions was explored with an independent resting-state fMRI data set (N = 1000). Cortical regions specialized for the same components were strongly coupled, suggesting that components function as partially isolated networks. Functionally flexible regions participated in multiple components to different degrees. This heterogeneous selectivity was predicted by the connectivity between flexible and specialized regions. Functionally flexible regions might support binding or integrating specialized brain networks that, in turn, contribute to the ability to execute multiple and varied tasks. PMID:25249407

  18. Inter-individual differences in the experience of negative emotion predict variations in functional brain architecture

    PubMed Central

    Petrican, Raluca; Saverino, Cristina; Rosenbaum, R. Shayna; Grady, Cheryl

    2016-01-01

    Current evidence suggests that two spatially distinct neuroanatomical networks, the dorsal attention network (DAN) and the default mode network (DMN), support externally and internally oriented cognition, respectively, and are functionally regulated by a third, frontoparietal control network (FPC). Interactions among these networks contribute to normal variations in cognitive functioning and to the aberrant affective profiles present in certain clinical conditions, such as major depression. Nevertheless, their links to non-clinical variations in affective functioning are still poorly understood. To address this issue, we used fMRI to measure the intrinsic functional interactions among these networks in a sample of predominantly younger women (N = 162) from the Human Connectome Project. Consistent with the previously documented dichotomous motivational orientations (i.e., withdrawal versus approach) associated with sadness versus anger, we hypothesized that greater sadness would predict greater DMN (rather than DAN) functional dominance, whereas greater anger would predict the opposite. Overall, there was evidence of greater DAN (rather than DMN) functional dominance, but this pattern was modulated by current experience of specific negative emotions, as well as subclinical depressive and anxiety symptoms. Thus, greater levels of currently experienced sadness and subclinical depression independently predicted weaker DAN functional dominance (i.e., weaker DAN-FPC functional connectivity), likely reflecting reduced goal-directed attention towards the external perceptual environment. Complementarily, greater levels of currently experienced anger and subclinical anxiety predicted greater DAN functional dominance (i.e., greater DAN-FPC functional connectivity and, for anxiety only, also weaker DMN-FPC coupling). Our findings suggest that distinct affective states and subclinical mood symptoms have dissociable neural signatures, reflective of the symbiotic relationship

  19. Does human presynaptic striatal dopamine function predict social conformity?

    PubMed

    Stokes, Paul R A; Benecke, Aaf; Puraite, Julita; Bloomfield, Michael A P; Shotbolt, Paul; Reeves, Suzanne J; Lingford-Hughes, Anne R; Howes, Oliver; Egerton, Alice

    2014-03-01

    Socially desirable responding (SDR) is a personality trait which reflects either a tendency to present oneself in an overly positive manner to others, consistent with social conformity (impression management (IM)), or the tendency to view one's own behaviour in an overly positive light (self-deceptive enhancement (SDE)). Neurochemical imaging studies report an inverse relationship between SDR and dorsal striatal dopamine D₂/₃ receptor availability. This may reflect an association between SDR and D₂/₃ receptor expression, synaptic dopamine levels or a combination of the two. In this study, we used a [¹⁸F]-DOPA positron emission tomography (PET) image database to investigate whether SDR is associated with presynaptic dopamine function. Striatal [¹⁸F]-DOPA uptake, (k(i)(cer), min⁻¹), was determined in two independent healthy participant cohorts (n=27 and 19), by Patlak analysis using a cerebellar reference region. SDR was assessed using the revised Eysenck Personality Questionnaire (EPQ-R) Lie scale, and IM and SDE were measured using the Paulhus Deception Scales. No significant associations were detected between Lie, SDE or IM scores and striatal [¹⁸F]-DOPA k(i)(cer). These results indicate that presynaptic striatal dopamine function is not associated with social conformity and suggests that social conformity may be associated with striatal D₂/₃ receptor expression rather than with synaptic dopamine levels.

  20. Evolutionary Trace Annotation Server: automated enzyme function prediction in protein structures using 3D templates

    PubMed Central

    Matthew Ward, R.; Venner, Eric; Daines, Bryce; Murray, Stephen; Erdin, Serkan; Kristensen, David M.; Lichtarge, Olivier

    2009-01-01

    Summary:The Evolutionary Trace Annotation (ETA) Server predicts enzymatic activity. ETA starts with a structure of unknown function, such as those from structural genomics, and with no prior knowledge of its mechanism uses the phylogenetic Evolutionary Trace (ET) method to extract key functional residues and propose a function-associated 3D motif, called a 3D template. ETA then searches previously annotated structures for geometric template matches that suggest molecular and thus functional mimicry. In order to maximize the predictive value of these matches, ETA next applies distinctive specificity filters—evolutionary similarity, function plurality and match reciprocity. In large scale controls on enzymes, prediction coverage is 43% but the positive predictive value rises to 92%, thus minimizing false annotations. Users may modify any search parameter, including the template. ETA thus expands the ET suite for protein structure annotation, and can contribute to the annotation efforts of metaservers. Availability:The ETA Server is a web application available at http://mammoth.bcm.tmc.edu/eta/. Contact: lichtarge@bcm.edu PMID:19307237

  1. miRDB: an online resource for microRNA target prediction and functional annotations.

    PubMed

    Wong, Nathan; Wang, Xiaowei

    2015-01-01

    MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.

  2. Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

    NASA Technical Reports Server (NTRS)

    Miller, Steven; Morris, Philip J.

    2012-01-01

    An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

  3. Predicting functional neuroanatomical maps from fusing brain networks with genetic information.

    PubMed

    Ganglberger, Florian; Kaczanowska, Joanna; Penninger, Josef M; Hess, Andreas; Bühler, Katja; Haubensak, Wulf

    2017-09-03

    Functional neuroanatomical maps provide a mesoscale reference framework for studies from molecular to systems neuroscience and psychiatry. The underlying structure-function relationships are typically derived from functional manipulations or imaging approaches. Although highly informative, these are experimentally costly. The increasing amount of publicly available brain and genetic data offers a rich source that could be mined to address this problem computationally. Here, we developed an algorithm that fuses gene expression and connectivity data with functional genetic meta data and exploits cumulative effects to derive neuroanatomical maps related to multi-genic functions. We validated the approach by using public available mouse and human data. The generated neuroanatomical maps recapture known functional anatomical annotations from literature and functional MRI data. When applied to multi-genic meta data from mouse quantitative trait loci (QTL) studies and human neuropsychiatric databases, this method predicted known functional maps underlying behavioral or psychiatric traits. Taken together, genetically weighted connectivity analysis (GWCA) allows for high throughput functional exploration of brain anatomy in silico. It maps functional genetic associations onto brain circuitry for refining functional neuroanatomy, or identifying trait-associated brain circuitry, from genetic data. Copyright © 2017. Published by Elsevier Inc.

  4. Association between lung function and airway wall density

    NASA Astrophysics Data System (ADS)

    Leader, J. Ken; Zheng, Bin; Fuhrman, Carl R.; Tedrow, John; Park, Sang C.; Tan, Jun; Pu, Jiantao; Drescher, John M.; Gur, David; Sciurba, Frank C.

    2009-02-01

    Computed tomography (CT) examination is often used to quantify the relation between lung function and airway remodeling in chronic obstructive pulmonary disease (COPD). In this preliminary study, we examined the association between lung function and airway wall computed attenuation ("density") in 200 COPD screening subjects. Percent predicted FVC (FVC%), percent predicted FEV1 (FEV1%), and the ratio of FEV1 to FVC as a percentage (FEV1/FVC%) were measured post-bronchodilator. The apical bronchus of the right upper lobe was manually selected from CT examinations for evaluation. Total airway area, lumen area, wall area, lumen perimeter and wall area as fraction of the total airway area were computed. Mean HU (meanHU) and maximum HU (maxHU) values were computed across pixels assigned membership in the wall and with a HU value greater than -550. The Pearson correlation coefficients (PCC) between FVC%, FEV1%, and FEV1/FVC% and meanHU were -0.221 (p = 0.002), -0.175 (p = 0.014), and -0.110 (p = 0.123), respectively. The PCCs for maxHU were only significant for FVC%. The correlations between lung function and the airway morphometry parameters were slightly stronger compared to airway wall density. MeanHU was significantly correlated with wall area (PCC = 0.720), airway area (0.498) and wall area percent (0.611). This preliminary work demonstrates that airway wall density is associated with lung function. Although the correlations in our study were weaker than a recent study, airway wall density initially appears to be an important parameter in quantitative CT analysis of COPD.

  5. Graphlet kernels for prediction of functional residues in protein structures.

    PubMed

    Vacic, Vladimir; Iakoucheva, Lilia M; Lonardi, Stefano; Radivojac, Predrag

    2010-01-01

    We introduce a novel graph-based kernel method for annotating functional residues in protein structures. A structure is first modeled as a protein contact graph, where nodes correspond to residues and edges connect spatially neighboring residues. Each vertex in the graph is then represented as a vector of counts of labeled non-isomorphic subgraphs (graphlets), centered on the vertex of interest. A similarity measure between two vertices is expressed as the inner product of their respective count vectors and is used in a supervised learning framework to classify protein residues. We evaluated our method on two function prediction problems: identification of catalytic residues in proteins, which is a well-studied problem suitable for benchmarking, and a much less explored problem of predicting phosphorylation sites in protein structures. The performance of the graphlet kernel approach was then compared against two alternative methods, a sequence-based predictor and our implementation of the FEATURE framework. On both tasks, the graphlet kernel performed favorably; however, the margin of difference was considerably higher on the problem of phosphorylation site prediction. While there is data that phosphorylation sites are preferentially positioned in intrinsically disordered regions, we provide evidence that for the sites that are located in structured regions, neither the surface accessibility alone nor the averaged measures calculated from the residue microenvironments utilized by FEATURE were sufficient to achieve high accuracy. The key benefit of the graphlet representation is its ability to capture neighborhood similarities in protein structures via enumerating the patterns of local connectivity in the corresponding labeled graphs.

  6. BRWLDA: bi-random walks for predicting lncRNA-disease associations

    PubMed Central

    Yu, Guoxian; Fu, Guangyuan; Lu, Chang; Ren, Yazhou; Wang, Jun

    2017-01-01

    Increasing efforts have been done to figure out the association between lncRNAs and complex diseases. Many computational models construct various lncRNA similarity networks, disease similarity networks, along with known lncRNA-disease associations to infer novel associations. However, most of them neglect the structural difference between lncRNAs network and diseases network, hierarchical relationships between diseases and pattern of newly discovered associations. In this study, we developed a model that performs Bi-Random Walks to predict novel LncRNA-Disease Associations (BRWLDA in short). This model utilizes multiple heterogeneous data to construct the lncRNA functional similarity network, and Disease Ontology to construct a disease network. It then constructs a directed bi-relational network based on these two networks and available lncRNAs-disease associations. Next, it applies bi-random walks on the network to predict potential associations. BRWLDA achieves reliable and better performance than other comparing methods not only on experiment verified associations, but also on the simulated experiments with masked associations. Case studies further demonstrate the feasibility of BRWLDA in identifying new lncRNA-disease associations.

  7. BRWLDA: bi-random walks for predicting lncRNA-disease associations.

    PubMed

    Yu, Guoxian; Fu, Guangyuan; Lu, Chang; Ren, Yazhou; Wang, Jun

    2017-09-01

    Increasing efforts have been done to figure out the association between lncRNAs and complex diseases. Many computational models construct various lncRNA similarity networks, disease similarity networks, along with known lncRNA-disease associations to infer novel associations. However, most of them neglect the structural difference between lncRNAs network and diseases network, hierarchical relationships between diseases and pattern of newly discovered associations. In this study, we developed a model that performs Bi-Random Walks to predict novel LncRNA-Disease Associations (BRWLDA in short). This model utilizes multiple heterogeneous data to construct the lncRNA functional similarity network, and Disease Ontology to construct a disease network. It then constructs a directed bi-relational network based on these two networks and available lncRNAs-disease associations. Next, it applies bi-random walks on the network to predict potential associations. BRWLDA achieves reliable and better performance than other comparing methods not only on experiment verified associations, but also on the simulated experiments with masked associations. Case studies further demonstrate the feasibility of BRWLDA in identifying new lncRNA-disease associations.

  8. Functional Embedding Predicts the Variability of Neural Activity

    PubMed Central

    Mišić, Bratislav; Vakorin, Vasily A.; Paus, Tomáš; McIntosh, Anthony R.

    2011-01-01

    Neural activity is irregular and unpredictable, yet little is known about why this is the case and how this property relates to the functional architecture of the brain. Here we show that the variability of a region’s activity systematically varies according to its topological role in functional networks. We recorded the resting-state electroencephalogram (EEG) and constructed undirected graphs of functional networks. We measured the centrality of each node in terms of the number of connections it makes (degree), the ease with which the node can be reached from other nodes in the network (efficiency) and the tendency of the node to occupy a position on the shortest paths between other pairs of nodes in the network (betweenness). As a proxy for variability, we estimated the information content of neural activity using multiscale entropy analysis. We found that the rate at which information was generated was largely predicted by centrality. Namely, nodes with greater degree, betweenness, and efficiency were more likely to have high information content, while peripheral nodes had relatively low information content. These results suggest that the variability of regional activity reflects functional embedding. PMID:22164135

  9. Risk prediction for myocardial infarction via generalized functional regression models.

    PubMed

    Ieva, Francesca; Paganoni, Anna M

    2016-08-01

    In this paper, we propose a generalized functional linear regression model for a binary outcome indicating the presence/absence of a cardiac disease with multivariate functional data among the relevant predictors. In particular, the motivating aim is the analysis of electrocardiographic traces of patients whose pre-hospital electrocardiogram (ECG) has been sent to 118 Dispatch Center of Milan (the Italian free-toll number for emergencies) by life support personnel of the basic rescue units. The statistical analysis starts with a preprocessing of ECGs treated as multivariate functional data. The signals are reconstructed from noisy observations. The biological variability is then removed by a nonlinear registration procedure based on landmarks. Thus, in order to perform a data-driven dimensional reduction, a multivariate functional principal component analysis is carried out on the variance-covariance matrix of the reconstructed and registered ECGs and their first derivatives. We use the scores of the Principal Components decomposition as covariates in a generalized linear model to predict the presence of the disease in a new patient. Hence, a new semi-automatic diagnostic procedure is proposed to estimate the risk of infarction (in the case of interest, the probability of being affected by Left Bundle Brunch Block). The performance of this classification method is evaluated and compared with other methods proposed in literature. Finally, the robustness of the procedure is checked via leave-j-out techniques.

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

    PubMed

    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.

  11. 47 CFR 69.603 - Association functions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... that are associated with the preparation, defense, and modification of association tariffs, those... of all other association expenses. Category I Expenses shall be sub-divided into three components in... Line revenues, the association Carrier Common Line revenues, the association Special Access Surcharge...

  12. 47 CFR 69.603 - Association functions.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... that are associated with the preparation, defense, and modification of association tariffs, those... of all other association expenses. Category I Expenses shall be sub-divided into three components in... Line revenues, the association Carrier Common Line revenues, the association Special Access Surcharge...

  13. 47 CFR 69.603 - Association functions.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... that are associated with the preparation, defense, and modification of association tariffs, those... of all other association expenses. Category I Expenses shall be sub-divided into three components in... Line revenues, the association Carrier Common Line revenues, the association Special Access Surcharge...

  14. Prediction of functional aerobic capacity without exercise testing

    NASA Technical Reports Server (NTRS)

    Jackson, A. S.; Blair, S. N.; Mahar, M. T.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.

    1990-01-01

    The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

  15. Prediction of functional aerobic capacity without exercise testing

    NASA Technical Reports Server (NTRS)

    Jackson, A. S.; Blair, S. N.; Mahar, M. T.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.

    1990-01-01

    The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

  16. Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

    PubMed

    Shah, Sonia; Bonder, Marc J; Marioni, Riccardo E; Zhu, Zhihong; McRae, Allan F; Zhernakova, Alexandra; Harris, Sarah E; Liewald, Dave; Henders, Anjali K; Mendelson, Michael M; Liu, Chunyu; Joehanes, Roby; Liang, Liming; Levy, Daniel; Martin, Nicholas G; Starr, John M; Wijmenga, Cisca; Wray, Naomi R; Yang, Jian; Montgomery, Grant W; Franke, Lude; Deary, Ian J; Visscher, Peter M

    2015-07-02

    We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Predictive factors associated with hepatitis C antiviral therapy response

    PubMed Central

    Cavalcante, Lourianne Nascimento; Lyra, André Castro

    2015-01-01

    Hepatitis C virus (HCV) infection may lead to significant liver injury, and viral, environmental, host, immunologic and genetic factors may contribute to the differences in the disease expression and treatment response. In the early 2000s, dual therapy using a combination of pegylated interferon plus ribavirin (PR) became the standard of care for HCV treatment. In this PR era, predictive factors of therapy response related to virus and host have been identified. In 2010/2011, therapeutic regimens for HCV genotype 1 patients were modified, and the addition of NS3/4a protease inhibitors (boceprevir or telaprevir) to dual therapy increased the effectiveness and chances of sustained virologic response (SVR). Nevertheless, the first-generation triple therapy is associated with many adverse events, some of which are serious and associated with death, particularly in cirrhotic patients. This led to the need to identify viral and host predictive factors that might influence the SVR rate to triple therapy and avoid unnecessary exposure to these drugs. Over the past four years, hepatitis C treatment has been rapidly changing with the development of new therapies and other developments. Currently, with the more recent generations of pangenotipic antiviral therapies, there have been higher sustained virologic rates, and prognostic factors may not have the same importance and strength as before. Nonetheless, some variables may still be consistent with the low rates of non-response with regimens that include sofosbuvir, daclatasvir and ledipasvir. In this manuscript, we review the predictive factors of therapy response across the different treatment regimens over the last decade including the new antiviral drugs. PMID:26140082

  18. Microtubule-Associated Protein Expression and Predicting Taxane Response

    DTIC Science & Technology

    2009-10-01

    taxanes. Our results indicate that MAP- tau functions as a prognostic factor in both the Yale cohort and the TAX 307 cohort with high MAP- tau ...expression associated with longer overall survival and TTP. Tau does NOT behave as a predictor of response to taxane-based chemotherapy since differences...between low and high MAP- tau groups by treatment arm and response rate were not observed in the TAX 307 clinical trial cohort. Our data supports the

  19. Mini-Review: Prediction errors, attention and associative learning

    PubMed Central

    Holland, Peter C.; Schiffino, Felipe L.

    2016-01-01

    Most modern theories of associative learning emphasize a critical role for prediction error (PE, the difference between received and expected events). One class of theories, exemplified by the Rescorla-Wagner (1972) model, asserts that PE determines the effectiveness of the reinforcer or unconditioned stimulus (US): surprising reinforcers are more effective than expected ones. A second class, represented by the Pearce-Hall (1980) model, argues that PE determines the associability of conditioned stimuli (CSs), the rate at which they may enter into new learning: the surprising delivery or omission of a reinforcer enhances subsequent processing of the CSs that were present when PE was induced. In this mini-review we describe evidence, mostly from our laboratory, for PE-induced changes in the associability of both CSs and USs, and the brain systems involved in the coding, storage and retrieval of these altered associability values. This evidence favors a number of modifications to behavioral models of how PE influences event processing, and suggests the involvement of widespread brain systems in animals’ responses to PE. PMID:26948122

  20. Fast rule-based bioactivity prediction using associative classification mining

    PubMed Central

    2012-01-01

    Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM), which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, classification based on predictive association rules (CPAR), classification based on multiple association rules (CMAR) and classification based on association rules (CBA) are employed on three datasets using various descriptor sets. Experimental evaluations on anti-tuberculosis (antiTB), mutagenicity and hERG (the human Ether-a-go-go-Related Gene) blocker datasets show that these three methods are computationally scalable and appropriate for high speed mining. Additionally, they provide comparable accuracy and efficiency to the commonly used Bayesian and support vector machines (SVM) methods, and produce highly interpretable models. PMID:23176548

  1. Predictive factors of functional ability after lower-limb amputation.

    PubMed

    Pohjolainen, T; Alaranta, H

    1991-01-01

    Functional ability and accommodation situation were studied by personal interview and examination of 125 surviving lower-limb amputees after one postoperative year. Among ten independent variables studied by multiple linear regression analysis, an unfavourable association was found between increasing age and the following aspects of physical function: walking distance (P less than 0.001), walking time (P less than 0.001), amount of outdoor walking outdoors (P less than 0.001), increased need for aids to ambulation (P less than 0.01), use of a prosthesis (P less than 0.05). Using a partial correlation coefficient analysis of functional ability and accommodation situation, with adjustment for age, the time lag between surgery and prosthetic fitting, and the occurrence of cerebrovascular disease displayed a similar unfavourable association with prosthetic usage. In the group of BK (below-knee) amputees the length of the stump had a significant favourable relationship with walking distance (P less than 0.01). In the male group of vascular BK amputees, smoking had an unfavourable association with walking distance (P less than 0.01), ability to walk outdoors (P less than 0.01) and walking time (P less than 0.05). None of the variables showed any significant relationship with the postoperative accommodation situation.

  2. Word List Memory Predicts Everyday Function and Problem-Solving in the Elderly: Results from the ACTIVE Cognitive Intervention Trial

    PubMed Central

    Gross, Alden L.; Rebok, George W.; Unverzagt, Frederick W.; Willis, Sherry L.; Brandt, Jason

    2011-01-01

    Data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial (N=2,802) were analyzed to examine whether word list learning predicts future everyday functioning. Using stepwise random effects modeling, measures from the modified administrations of the Hopkins Verbal Learning Test (HVLT) and the Auditory Verbal Learning Test (AVLT) were independently predictive of everyday IADL functioning, problem-solving, and psychomotor speed. Associations between memory scores and everyday functioning outcomes remained significant across follow-up intervals spanning five years. HVLT total recall score was consistently the strongest predictor of each functional outcome. Results suggest that verbal memory measures are uniquely associated with both current and future functioning and that specific verbal memory tests like the HVLT and AVLT have important clinical utility in predicting future functional ability among older adults. PMID:21069610

  3. General functioning predicts reward and punishment learning in schizophrenia.

    PubMed

    Somlai, Zsuzsanna; Moustafa, Ahmed A; Kéri, Szabolcs; Myers, Catherine E; Gluck, Mark A

    2011-04-01

    Previous studies investigating feedback-driven reinforcement learning in patients with schizophrenia have provided mixed results. In this study, we explored the clinical predictors of reward and punishment learning using a probabilistic classification learning task. Patients with schizophrenia (n=40) performed similarly to healthy controls (n=30) on the classification learning task. However, more severe negative and general symptoms were associated with lower reward-learning performance, whereas poorer general psychosocial functioning was correlated with both lower reward- and punishment-learning performances. Multiple linear regression analyses indicated that general psychosocial functioning was the only significant predictor of reinforcement learning performance when education, antipsychotic dose, and positive, negative and general symptoms were included in the analysis. These results suggest a close relationship between reinforcement learning and general psychosocial functioning in schizophrenia.

  4. Functional network connectivity predicts treatment outcome during treatment of nicotine use disorder.

    PubMed

    Wilcox, Claire E; Calhoun, Vince D; Rachakonda, Srinivas; Claus, Eric D; Littlewood, Rae A; Mickey, Jessica; Arenella, Pamela B; Hutchison, Kent E

    2017-07-30

    Altered resting state functional connectivity (rsFC) and functional network connectivity (FNC), which is a measure of coherence between brain networks, may be associated with nicotine use disorder (NUD). We hypothesized that higher connectivity between insula and 1) dorsal anterior cingulate cortex (dACC) and 2) dorsolateral prefrontal cortex (dlPFC) would predict better treatment outcomes. We also performed an exploratory analysis of the associations between FNC values between additional key frontal and striatal regions and treatment outcomes. One hundred and forty four individuals with NUD underwent a resting state session during functional MRI prior to randomization to treatment with varenicline (n=82) or placebo. Group independent component analysis (ICA) was utilized to extract individual subject components and time series from intrinsic connectivity networks in aforementioned regions, and FNC between all possible pairs were calculated. Higher FNC between insula and dACC (rho=0.21) was significantly correlated with lower levels of baseline smoking quantity but did not predict treatment outcome upon controlling for baseline smoking. Higher FNC between putamen and dACC, caudate and dACC, and caudate and dlPFC significantly predicted worse treatment outcome in participants reporting high subjective withdrawal before the scan. FNC between key regions hold promise as biomarkers to predict outcome in NUD. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  5. Density-functional theory for polar fluids at functionalized surfaces. I. Fluid-wall association

    NASA Astrophysics Data System (ADS)

    Tripathi, Sandeep; Chapman, Walter G.

    2003-12-01

    We present a novel perturbation density-functional theory (DFT) to describe adsorption of associating fluids on surfaces activated with polar sites to which fluid molecules can bond or associate, such as water adsorbing on activated carbon, silica, clay minerals, etc. Association is modeled within the framework of first order thermodynamic perturbation theory (TPT1). In this first of two papers, we explore in detail the changes brought about in a system due to fluid-wall (FW) association. Hence fluid-fluid association is not considered here. However, the theory can be coupled with existing DF theories of associating fluids to study the interplay between the wall-fluid and fluid-fluid association as is shown in a future paper by S. Tripathi. The proposed theory, in excellent agreement with simulations, shows that FW association significantly changes the fluid structure and adsorption behavior. The theory accurately predicts the distribution of bonded and nonbonded species away from the surface, adsorption characteristics and surface coverage over a range of conditions commonly found in several real systems. The most striking feature of the theory is that in addition to properties away from the wall, it also estimates the distribution of the fluid along the surface, or the three-dimensional (3D) structure, despite being one-dimensional (1D) in form.

  6. Predictive factors of functional capacity and real-world functioning in patients with schizophrenia.

    PubMed

    Menendez-Miranda, I; Garcia-Portilla, M P; Garcia-Alvarez, L; Arrojo, M; Sanchez, P; Sarramea, F; Gomar, J; Bobes-Bascaran, M T; Sierra, P; Saiz, P A; Bobes, J

    2015-07-01

    This study was performed to identify the predictive factors of functional capacity assessed by the Spanish University of California Performance Skills Assessment (Sp-UPSA) and real-world functioning assessed by the Spanish Personal and Social Performance scale (PSP) in outpatients with schizophrenia. Naturalistic, 6-month follow-up, multicentre, validation study. Here, we report data on 139 patients with schizophrenia at their baseline visit. Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression-Severity (CGI-S), Sp-UPSA and PSP. Pearson's correlation coefficient (r) was used to determine the relationships between variables, and multivariable stepwise linear regression analyses to identify predictive variables of Sp-UPSA and PSP total scores. Functional capacity: scores on the PSP and PANSS-GP entered first and second at P<0.0001 and accounted for 21% of variance (R(2)=0.208, model df=2, F=15.724, P<0.0001). Real-world functioning: scores on the CGI-S (B=-5.406), PANSS-N (B=-0.657) and Sp-UPSA (B=0.230) entered first, second and third, and accounted for 51% of variance (model df=3, F=37.741, P<0.0001). In patients with schizophrenia, functional capacity and real-world functioning are two related but different constructs. Each one predicts the other along with other factors; general psychopathology for functional capacity, and severity of the illness and negative symptoms for real-world functioning. These findings have important clinical implications: (1) both types of functioning should be assessed in patients with schizophrenia and (2) strategies for improving them should be different. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  7. Personality traits predicting quality of life and overall functioning in schizophrenia.

    PubMed

    Ridgewell, Caitlin; Blackford, Jennifer Urbano; McHugo, Maureen; Heckers, Stephan

    2017-04-01

    Clinical symptoms and sociodemographic variables predict level of functioning and quality of life in patients with schizophrenia. However, few studies have examined the effect of personality traits on quality of life and overall functioning in schizophrenia. Personality traits are premorbid to illness and may predict the way patients experience schizophrenia. The aim of this study was to examine the individual and additive effects of two core personality traits-neuroticism and extraversion-on quality of life and functioning. Patients with schizophrenia-spectrum disorders (n=153) and healthy controls (n=125) completed personality and quality of life questionnaires. Global functioning was assessed during a clinician-administered structured interview. Neuroticism and extraversion scores were analyzed both as continuous variables and as categorical extremes (High versus Normal Neuroticism, Low versus Normal Extraversion). Quality of life was significantly associated with neuroticism, extraversion, and the neuroticism×diagnosis and extraversion×diagnosis interactions. For patients, a lower neuroticism score (in the normal range) was associated with quality of life scores comparable to controls; whereas high neuroticism scores in patients were associated with the lowest quality of life. For overall functioning, only diagnosis had a significant effect. Neuroticism modulates quality of life and may provide an important key to improving the life of patients with schizophrenia. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Sagittal spinopelvic alignment predicts hip function after total hip arthroplasty.

    PubMed

    Ochi, Hironori; Homma, Yasuhiro; Baba, Tomonori; Nojiri, Hidetoshi; Matsumoto, Mikio; Kaneko, Kazuo

    2017-02-01

    The aim of this study was to investigate the association between preoperative sagittal spinopelvic alignment and postoperative clinical outcomes after total hip arthroplasty (THA). This retrospective study included 92 patients with hip osteoarthritis who underwent primary THA between May 2013 and October 2015. Patients' characteristics, radiographic sagittal spinopelvic parameters and modified Harris Hip Scores, including function scores (gait scores and functional activities scores), were investigated. Multivariate linear regression analysis was performed to determine the associations between each preoperative sagittal spinopelvic parameter and postoperative hip function The preoperative sagittal spinopelvic parameters that were associated with postoperative gait scores were sagittal vertical axis (adjusted β-coefficient=-0.28, P=0.02), lumbar lordosis angle (adjusted β-coefficient=0.29, P=0.0089), pelvic tilt (adjusted β-coefficient=-0.25, P=0.045), sacral slope (adjusted β-coefficient=0.27, P=0.017) and pelvic incidence minus lumbar lordosis angle (adjusted β-coefficient=-0.31, P=0.01). The preoperative sagittal spinopelvic parameters that were related to the postoperative functional activities scores were sagittal vertical axis (adjusted β-coefficient=-0.38, P=0.0051) and pelvic incidence minus lumbar lordosis angle (adjusted β-coefficient=-0.39, P=0.0033). Patients with preoperative imbalanced sagittal alignment such as larger sagittal vertical axis, larger pelvic incidence minus lumbar lordosis and retroversion of pelvis had poorer clinical outcomes than others after THA. While, those preoperative imbalanced patients with anteversion of pelvis may have a compensatory ability which could correct the abnormal sagittal alignment after THA. Preoperative sagittal spinopelvic alignment affected postoperative clinical outcomes after THA. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    PubMed

    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.

  10. Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis.

    PubMed

    Nieves, Jeri W; Gennings, Chris; Factor-Litvak, Pam; Hupf, Jonathan; Singleton, Jessica; Sharf, Valerie; Oskarsson, Björn; Fernandes Filho, J Americo M; Sorenson, Eric J; D'Amico, Emanuele; Goetz, Ray; Mitsumoto, Hiroshi

    2016-12-01

    There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS). To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis. A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less. Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ). Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale-Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC). Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5-68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of "good" micronutrients and "good" food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses. Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional

  11. Histopathological analysis of the non - tumour parenchyma following radical nephrectomy: can it predict renal functional outcome?

    PubMed

    Birendra, Rana; John, Nirmal Thampi; Duhli, Neelaveni; Devasia, Antony; Kekre, Nitin; Manojkumar, Ramani

    2017-01-01

    Radical nephrectomy (RN), a recommended treatment option for patients with Renal cell carcinoma (RCC) leads to an inevitable decline in global renal function. Pathological changes in the non-tumour parenchyma of the kidney may help predict the function of the remaining kidney. Aim of this prospective, observational study was to find histopathological factors in the non-tumor renal parenchyma that could predict the decline in global renal function postoperatively and its association with co-morbidities like diabetes (DM). Data of consecutive patients undergoing RN from December-2013 to January-2015 was collected. Non-tumor parenchyma of the specimen was reported by a dedicated histopathologist. eGFR was calculated using Cockcroft-Gault formula before the surgery and at last follow up of at least 12 months. 73 RN specimens were analyzed. Mean follow up was 12.3 months. The mean decrease in eGFR was 22% (p=.0001). Percent decrease in eGFR did not show association with any of the histopathological parameters studied. DM was significantly associated with decrease in percent eGFR (p<0.05) and increase in arteriolar hyalinosis (p=0.004), Glomerulosclerosis (p=0.03) and Interstitial fibrosis/ Tubular atrophy (p=.0001). Maximum size of the tumor showed a negative correlation with percentage change in eGFR (p=0.028). Histological parameters in the non-tumour portion of the RN specimen may not be able to predict renal function outcome over a short follow up. However, presence of DM was associated with adverse pathological changes and significant decrease in renal function postoperatively. Copyright® by the International Brazilian Journal of Urology.

  12. Link prediction boosted psychiatry disorder classification for functional connectivity network

    NASA Astrophysics Data System (ADS)

    Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

    2017-02-01

    Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

  13. A Prediction for the 4-Loop beta Function in QCD

    SciTech Connect

    Samuel, Mark A.

    2003-05-14

    We predict that the four-loop contribution {beta}{sub 3} to the QCD {beta} function in the {ovr MS} prescription is given by {beta}{sub 3} {approx_equal} 23,600(900) - 6,400(200) N{sub f} + 350(70)N{sub f}{sup 2} + 1.5 N{sub f}{sup 3}, where N{sub f} is the number of flavours and the coefficient of N{sub f}{sup 3} is an exact result from large-N{sub f} expansion. In the phenomenologically-interesting case N{sub f} = 3, we estimate {beta}{sub 3} = (7.6 {+-} 0.1) x 10{sup 3}. We discuss our estimates of the errors in these QCD predictions, basing them on the demonstrated accuracy of our method in test applications to the O(N) {Phi}{sup 4} theory, and on variations in the details of our estimation method, which goes beyond conventional Pade approximants by estimating and correcting for subasymptotic deviations from exact results.

  14. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    DOE PAGES

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO22+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root mean square deviation from experiment < 1.0 for log K1 values ranging from 0more » to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

  15. Predicting biomedical document access as a function of past use.

    PubMed

    Goodwin, J Caleb; Johnson, Todd R; Cohen, Trevor; Herskovic, Jorge R; Bernstam, Elmer V

    2012-01-01

    To determine whether past access to biomedical documents can predict future document access. The authors used 394 days of query log (August 1, 2009 to August 29, 2010) from PubMed users in the Texas Medical Center, which is the largest medical center in the world. The authors evaluated two document access models based on the work of Anderson and Schooler. The first is based on how frequently a document was accessed. The second is based on both frequency and recency. The model based only on frequency of past access was highly correlated with the empirical data (R²=0.932), whereas the model based on frequency and recency had a much lower correlation (R²=0.668). The frequency-only model accurately predicted whether a document will be accessed based on past use. Modeling accesses as a function of frequency requires storing only the number of accesses and the creation date for the document. This model requires low storage overheads and is computationally efficient, making it scalable to large corpora such as MEDLINE. It is feasible to accurately model the probability of a document being accessed in the future based on past accesses.

  16. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    SciTech Connect

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO22+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K1 values are significantly overestimated. Accurate predictions of the absolute log K1 values (root mean square deviation from experiment < 1.0 for log K1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.

  17. Prediction of glass durability as a function of environmental conditions

    SciTech Connect

    Jantzen, C M

    1988-01-01

    A thermodynamic model of glass durability is applied to natural, ancient, and nuclear waste glasses. The durabilities of over 150 different natural and man-made glasses, including actual ancient Roman and Islamic glasses (Jalame ca. 350 AD, Nishapur 10-11th century AD and Gorgon 9-11th century AD), are compared. Glass durability is a function of the thermodynamic hydration free energy, ..delta..G/sub hyd/, which can be calculated from glass composition and solution pH. The durability of the most durable nuclear waste glasses examined was /approximately/10/sup 6/ years. The least durable waste glass formulations were comparable in durability to the most durable simulated medieval window glasses of /approximately/10/sup 3/ years. In this manner, the durability of nuclear waste glasses has been interpolated to be /approximately/10/sup 6/ years and no less than 10/sup 3/ years. Hydration thermodynamics have been shown to be applicable to the dissolution of glass in various natural environments. Groundwater-glass interactions relative to geologic disposal of nuclear waste, hydration rind dating of obsidians, andor other archeological studies can be modeled, e.g., the relative durabilities of six simulated medieval window glasses have been correctly predicted for both laboratory (one month) and burial (5 years) experiments. Effects of solution pH on glass dissolution has been determined experimentally for the 150 different glasses and can be predicted theoretically by hydration thermodynamics. The effects of solution redox on dissolution of glass matrix elements such as SI and B have shown to be minimal. The combined effects of solution pH and Eh have been described and unified by construction of thermodynamically calculated Pourbaix (pH-Eh) diagrams for glass dissolution. The Pourbaix diagrams have been quantified to describe glass dissolution as a function of environmental conditions by use of the data derived from hydration thermodynamics. 56 refs., 7 figs.

  18. GAPIT Version 2: An Enhanced Integrated Tool for Genomic Association and Prediction.

    PubMed

    Tang, You; Liu, Xiaolei; Wang, Jiabo; Li, Meng; Wang, Qishan; Tian, Feng; Su, Zhongbin; Pan, Yuchun; Liu, Di; Lipka, Alexander E; Buckler, Edward S; Zhang, Zhiwu

    2016-07-01

    Most human diseases and agriculturally important traits are complex. Dissecting their genetic architecture requires continued development of innovative and powerful statistical methods. Corresponding advances in computing tools are critical to efficiently use these statistical innovations and to enhance and accelerate biomedical and agricultural research and applications. The genome association and prediction integrated tool (GAPIT) was first released in 2012 and became widely used for genome-wide association studies (GWAS) and genomic prediction. The GAPIT implemented computationally efficient statistical methods, including the compressed mixed linear model (CMLM) and genomic prediction by using genomic best linear unbiased prediction (gBLUP). New state-of-the-art statistical methods have now been implemented in a new, enhanced version of GAPIT. These methods include factored spectrally transformed linear mixed models (FaST-LMM), enriched CMLM (ECMLM), FaST-LMM-Select, and settlement of mixed linear models under progressively exclusive relationship (SUPER). The genomic prediction methods implemented in this new release of the GAPIT include gBLUP based on CMLM, ECMLM, and SUPER. Additionally, the GAPIT was updated to improve its existing output display features and to add new data display and evaluation functions, including new graphing options and capabilities, phenotype simulation, power analysis, and cross-validation. These enhancements make the GAPIT a valuable resource for determining appropriate experimental designs and performing GWAS and genomic prediction. The enhanced R-based GAPIT software package uses state-of-the-art methods to conduct GWAS and genomic prediction. The GAPIT also provides new functions for developing experimental designs and creating publication-ready tabular summaries and graphs to improve the efficiency and application of genomic research.

  19. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism.

    PubMed

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L; Kenworthy, Lauren; Martin, Alex

    2015-12-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome--adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement.

  20. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism

    PubMed Central

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L.; Kenworthy, Lauren; Martin, Alex

    2015-01-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome—adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement. PMID:26627261

  1. In vitro function of the aryl hydrocarbon receptor predicts in ...

    EPA Pesticide Factsheets

    Differences in sensitivity to dioxin-like compounds (DLCs) among species and taxa presents a major challenge to ecological risk assessments. Activation of the aryl hydrocarbon receptor (AHR) regulates adverse effects associated with exposure to DLCs in vertebrates. Prior investigations demonstrated that sensitivity to activation of the AHR1 (50% effect concentration; EC50) in an in vitro luciferase reporter gene (LRG) assay was predictive of the sensitivity of embryos (lethal dose to cause 50% lethality; LD50) across all species of birds for all DLCs. However, nothing was known about whether sensitivity to activation of the AHR is predictive of sensitivity of embryos of fishes to DLCs. Therefore, this study investigated in vitro sensitivities of AHR1s and AHR2s to the model DLC, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), among eight species of fish of known sensitivities of embryos to TCDD. AHR1s and AHR2s of all fishes were activated by TCDD in vitro. There was no significant linear relationship between in vitro sensitivity of AHR1 and in vivo sensitivity among the investigated fishes (R2 = 0.33, p = 0.23). However, there was a significant linear relationship between in vitro sensitivity of AHR2 and in vivo sensitivity among the investigated fishes (R2 = 0.97, p = < 0.0001). The linear relationship between in vitro sensitivity of AHR2 and in vivo sensitivity of embryos among fishes was compared to the previously generated linear relationship between in vitro s

  2. In vitro function of the aryl hydrocarbon receptor predicts in ...

    EPA Pesticide Factsheets

    Differences in sensitivity to dioxin-like compounds (DLCs) among species and taxa presents a major challenge to ecological risk assessments. Activation of the aryl hydrocarbon receptor (AHR) regulates adverse effects associated with exposure to DLCs in vertebrates. Prior investigations demonstrated that sensitivity to activation of the AHR1 (50% effect concentration; EC50) in an in vitro luciferase reporter gene (LRG) assay was predictive of the sensitivity of embryos (lethal dose to cause 50% lethality; LD50) across all species of birds for all DLCs. However, nothing was known about whether sensitivity to activation of the AHR is predictive of sensitivity of embryos of fishes to DLCs. Therefore, this study investigated in vitro sensitivities of AHR1s and AHR2s to the model DLC, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), among eight species of fish of known sensitivities of embryos to TCDD. AHR1s and AHR2s of all fishes were activated by TCDD in vitro. There was no significant linear relationship between in vitro sensitivity of AHR1 and in vivo sensitivity among the investigated fishes (R2 = 0.33, p = 0.23). However, there was a significant linear relationship between in vitro sensitivity of AHR2 and in vivo sensitivity among the investigated fishes (R2 = 0.97, p = < 0.0001). The linear relationship between in vitro sensitivity of AHR2 and in vivo sensitivity of embryos among fishes was compared to the previously generated linear relationship between in vitro s

  3. Do Personality Traits Predict Functional Impairment and Quality of Life in Adult ADHD? A Controlled Study.

    PubMed

    He, J Allison; Antshel, Kevin M; Biederman, Joseph; Faraone, Stephen V

    2015-11-25

    To examine the association of personality traits and characteristics on quality of life and functioning in adults with ADHD. Participants were adults with (n = 206) and without ADHD (n = 123) who completed the Temperament and Character Inventory (TCI), the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), and the Social Adjustment Scale-Self-Report (SAS-SR). Participants also provided information on academic, motor vehicle operation, legal, social, familial, and occupational functioning. Outcomes were examined using stepwise linear regression, logistic regression (for binary outcomes), and negative binomial regression (for count outcomes) controlling for ADHD symptoms, psychiatric comorbidity, and executive dysfunction. Adults with ADHD significantly differed from controls across nearly all TCI personality domains. On average, adults with ADHD endorsed more novelty seeking, harm avoidance, and self-transcendence, and less reward dependence, persistence, self-directedness, and cooperativeness. Personality traits and characteristics, especially self-directedness, significantly predicted functional impairments even after controlling for ADHD symptoms, executive function deficits, and current psychiatric comorbidities. In adults with ADHD, personality traits exert unique associations on quality of life and functional impairment across major life domains, beyond the relations expected of and associated with ADHD symptoms and other associated psychiatric conditions and cognitive vulnerabilities. Addressing personality traits in adults with ADHD may lead to improvements in quality of life and reductions in functional impairment. © The Author(s) 2015.

  4. Organizational Characteristics Associated With the Predicted Sustainability of Villages.

    PubMed

    Scharlach, Andrew E; Lehning, Amanda J; Davitt, Joan K; Greenfield, Emily A; Graham, Carrie L

    2017-02-01

    Guided by resource dependence theory, this mixed-methods study examined organizational characteristics contributing to the perceived sustainability of Villages, a rapidly proliferating grassroots approach for promoting social participation and service access for community-dwelling older adults. Surveys conducted with leaders of 86% of Villages in the United States in 2012 found that higher predicted confidence in their Village's 10-year survival was associated with greater financial reserves, human resources, number of Village members, formal policies and procedures, and formal collaboration agreements. Respondents' explanations of their confidence ratings revealed additional themes of organizational leadership and perceived community need. Member resource inputs were not found to be as salient for Village leaders' perceptions of sustainability as was anticipated given the Village model's emphasis on consumer involvement. Despite the lack of longitudinal prospective data, study findings suggest potential limitations of consumer-driven organizational models such as Villages, including the need for a more stable resource base.

  5. Prediction-based association control scheme in dense femtocell networks

    PubMed Central

    Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

    2017-01-01

    The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992

  6. Functional traits predict relationship between plant abundance dynamic and long-term climate warming.

    PubMed

    Soudzilovskaia, Nadejda A; Elumeeva, Tatiana G; Onipchenko, Vladimir G; Shidakov, Islam I; Salpagarova, Fatima S; Khubiev, Anzor B; Tekeev, Dzhamal K; Cornelissen, Johannes H C

    2013-11-05

    Predicting climate change impact on ecosystem structure and services is one of the most important challenges in ecology. Until now, plant species response to climate change has been described at the level of fixed plant functional types, an approach limited by its inflexibility as there is much interspecific functional variation within plant functional types. Considering a plant species as a set of functional traits greatly increases our possibilities for analysis of ecosystem functioning and carbon and nutrient fluxes associated therewith. Moreover, recently assembled large-scale databases hold comprehensive per-species data on plant functional traits, allowing a detailed functional description of many plant communities on Earth. Here, we show that plant functional traits can be used as predictors of vegetation response to climate warming, accounting in our test ecosystem (the species-rich alpine belt of Caucasus mountains, Russia) for 59% of variability in the per-species abundance relation to temperature. In this mountain belt, traits that promote conservative leaf water economy (higher leaf mass per area, thicker leaves) and large investments in belowground reserves to support next year's shoot buds (root carbon content) were the best predictors of the species increase in abundance along with temperature increase. This finding demonstrates that plant functional traits constitute a highly useful concept for forecasting changes in plant communities, and their associated ecosystem services, in response to climate change.

  7. Functional traits predict relationship between plant abundance dynamic and long-term climate warming

    PubMed Central

    Soudzilovskaia, Nadejda A.; Elumeeva, Tatiana G.; Onipchenko, Vladimir G.; Shidakov, Islam I.; Salpagarova, Fatima S.; Khubiev, Anzor B.; Tekeev, Dzhamal K.; Cornelissen, Johannes H. C.

    2013-01-01

    Predicting climate change impact on ecosystem structure and services is one of the most important challenges in ecology. Until now, plant species response to climate change has been described at the level of fixed plant functional types, an approach limited by its inflexibility as there is much interspecific functional variation within plant functional types. Considering a plant species as a set of functional traits greatly increases our possibilities for analysis of ecosystem functioning and carbon and nutrient fluxes associated therewith. Moreover, recently assembled large-scale databases hold comprehensive per-species data on plant functional traits, allowing a detailed functional description of many plant communities on Earth. Here, we show that plant functional traits can be used as predictors of vegetation response to climate warming, accounting in our test ecosystem (the species-rich alpine belt of Caucasus mountains, Russia) for 59% of variability in the per-species abundance relation to temperature. In this mountain belt, traits that promote conservative leaf water economy (higher leaf mass per area, thicker leaves) and large investments in belowground reserves to support next year’s shoot buds (root carbon content) were the best predictors of the species increase in abundance along with temperature increase. This finding demonstrates that plant functional traits constitute a highly useful concept for forecasting changes in plant communities, and their associated ecosystem services, in response to climate change. PMID:24145400

  8. Prediction and validation of gene-disease associations using methods inspired by social network analyses.

    PubMed

    Singh-Blom, U Martin; Natarajan, Nagarajan; Tewari, Ambuj; Woods, John O; Dhillon, Inderjit S; Marcotte, Edward M

    2013-01-01

    Correctly identifying associations of genes with diseases has long been a goal in biology. With the emergence of large-scale gene-phenotype association datasets in biology, we can leverage statistical and machine learning methods to help us achieve this goal. In this paper, we present two methods for predicting gene-disease associations based on functional gene associations and gene-phenotype associations in model organisms. The first method, the Katz measure, is motivated from its success in social network link prediction, and is very closely related to some of the recent methods proposed for gene-disease association inference. The second method, called Catapult (Combining dATa Across species using Positive-Unlabeled Learning Techniques), is a supervised machine learning method that uses a biased support vector machine where the features are derived from walks in a heterogeneous gene-trait network. We study the performance of the proposed methods and related state-of-the-art methods using two different evaluation strategies, on two distinct data sets, namely OMIM phenotypes and drug-target interactions. Finally, by measuring the performance of the methods using two different evaluation strategies, we show that even though both methods perform very well, the Katz measure is better at identifying associations between traits and poorly studied genes, whereas Catapult is better suited to correctly identifying gene-trait associations overall [corrected].

  9. Predicting Species-environment Relationships with Functional Traits for the Understory Flora of Wisconsin

    NASA Astrophysics Data System (ADS)

    Ash, J.; Li, D.; Johnson, S.; Rogers, D. A.; Waller, D. M.

    2015-12-01

    Understanding the processes that structure species' abundance patterns is a central problem in ecology, both for explaining current species' distributions and predicting future changes. Environmental gradients affect species' distribution patterns with these responses likely depending on species' functional traits. Thus, tracking shifts in species' traits can provide insight into the mechanisms by which species respond to dynamic environmental conditions. We examined how functional traits are associated with long-term changes in the distribution and abundance of understory plants in Wisconsin forests over the last 50+ years. We relied on detailed surveys and resurveys of the same Wisconsin forest plots, data on 12 functional traits, and site-level environmental variables including soil and climate conditions. We then related changes in the abundance of 293 species across a network of 249 sites to these environmental variables and explored whether functional traits served to predict these relationships using multilevel models. Species abundance patterns were strongly related to variation in environmental conditions among sites, but species appear to be responding to distinct sets of environmental variables. Functional traits only weakly predicted these species-environment relationships, limiting our ability to generalize these results to other systems. Nonetheless, understanding how traits interact with environmental gradients to structure species distribution patterns helps us to disentangle the drivers of ecological change across diverse landscapes.

  10. Curved Displacement Transfer Functions for Geometric Nonlinear Large Deformation Structure Shape Predictions

    NASA Technical Reports Server (NTRS)

    Ko, William L.; Fleischer, Van Tran; Lung, Shun-Fat

    2017-01-01

    For shape predictions of structures under large geometrically nonlinear deformations, Curved Displacement Transfer Functions were formulated based on a curved displacement, traced by a material point from the undeformed position to deformed position. The embedded beam (depth-wise cross section of a structure along a surface strain-sensing line) was discretized into multiple small domains, with domain junctures matching the strain-sensing stations. Thus, the surface strain distribution could be described with a piecewise linear or a piecewise nonlinear function. The discretization approach enabled piecewise integrations of the embedded-beam curvature equations to yield the Curved Displacement Transfer Functions, expressed in terms of embedded beam geometrical parameters and surface strains. By entering the surface strain data into the Displacement Transfer Functions, deflections along each embedded beam can be calculated at multiple points for mapping the overall structural deformed shapes. Finite-element linear and nonlinear analyses of a tapered cantilever tubular beam were performed to generate linear and nonlinear surface strains and the associated deflections to be used for validation. The shape prediction accuracies were then determined by comparing the theoretical deflections with the finiteelement- generated deflections. The results show that the newly developed Curved Displacement Transfer Functions are very accurate for shape predictions of structures under large geometrically nonlinear deformations.

  11. Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy.

    PubMed

    Fresco, David M; Roy, Amy K; Adelsberg, Samantha; Seeley, Saren; García-Lesy, Emmanuel; Liston, Conor; Mennin, Douglas S

    2017-01-01

    Despite the success of available medical and psychosocial treatments, a sizable subgroup of individuals with commonly co-occurring disorders, generalized anxiety disorder (GAD) and major depressive disorder (MDD), fail to make sufficient treatment gains thereby prolonging their deficits in life functioning and satisfaction. Clinically, these patients often display temperamental features reflecting heightened sensitivity to underlying motivational systems related to threat/safety and reward/loss (e.g., somatic anxiety) as well as inordinate negative self-referential processing (e.g., worry, rumination). This profile may reflect disruption in two important neural networks associated with emotional/motivational salience (e.g., salience network) and self-referentiality (e.g., default network, DN). Emotion Regulation Therapy (ERT) was developed to target this hypothesized profile and its neurobehavioral markers. In the present study, 22 GAD patients (with and without MDD) completed resting state MRI scans before receiving 16 sessions of ERT. To test study these hypotheses, we examined the associations between baseline patterns of intrinsic functional connectivity (iFC) of the insula and of hubs within the DN (anterior and dorsal medial prefrontal cortex [MPFC] and posterior cingulate cortex [PCC]) and treatment-related changes in worry, somatic anxiety symptoms and decentering. Results suggest that greater treatment linked reductions in worry were associated with iFC clusters in both the insular and parietal cortices. Greater treatment linked gains in decentering, a metacognitive process that involves the capacity to observe items that arise in the mind with healthy psychological distance that is targeted by ERT, was associated with iFC clusters in the anterior and posterior DN. The current study adds to the growing body of research implicating disruptions in the default and salience networks as promising targets of treatment for GAD with and without co-occurring MDD.

  12. Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy

    PubMed Central

    Fresco, David M.; Roy, Amy K.; Adelsberg, Samantha; Seeley, Saren; García-Lesy, Emmanuel; Liston, Conor; Mennin, Douglas S.

    2017-01-01

    Despite the success of available medical and psychosocial treatments, a sizable subgroup of individuals with commonly co-occurring disorders, generalized anxiety disorder (GAD) and major depressive disorder (MDD), fail to make sufficient treatment gains thereby prolonging their deficits in life functioning and satisfaction. Clinically, these patients often display temperamental features reflecting heightened sensitivity to underlying motivational systems related to threat/safety and reward/loss (e.g., somatic anxiety) as well as inordinate negative self-referential processing (e.g., worry, rumination). This profile may reflect disruption in two important neural networks associated with emotional/motivational salience (e.g., salience network) and self-referentiality (e.g., default network, DN). Emotion Regulation Therapy (ERT) was developed to target this hypothesized profile and its neurobehavioral markers. In the present study, 22 GAD patients (with and without MDD) completed resting state MRI scans before receiving 16 sessions of ERT. To test study these hypotheses, we examined the associations between baseline patterns of intrinsic functional connectivity (iFC) of the insula and of hubs within the DN (anterior and dorsal medial prefrontal cortex [MPFC] and posterior cingulate cortex [PCC]) and treatment-related changes in worry, somatic anxiety symptoms and decentering. Results suggest that greater treatment linked reductions in worry were associated with iFC clusters in both the insular and parietal cortices. Greater treatment linked gains in decentering, a metacognitive process that involves the capacity to observe items that arise in the mind with healthy psychological distance that is targeted by ERT, was associated with iFC clusters in the anterior and posterior DN. The current study adds to the growing body of research implicating disruptions in the default and salience networks as promising targets of treatment for GAD with and without co-occurring MDD

  13. A continuous function model for path prediction of entities

    NASA Astrophysics Data System (ADS)

    Nanda, S.; Pray, R.

    2007-04-01

    As militaries across the world continue to evolve, the roles of humans in various theatres of operation are being increasingly targeted by military planners for substitution with automation. Forward observation and direction of supporting arms to neutralize threats from dynamic adversaries is one such example. However, contemporary tracking and targeting systems are incapable of serving autonomously for they do not embody the sophisticated algorithms necessary to predict the future positions of adversaries with the accuracy offered by the cognitive and analytical abilities of human operators. The need for these systems to incorporate methods characterizing such intelligence is therefore compelling. In this paper, we present a novel technique to achieve this goal by modeling the path of an entity as a continuous polynomial function of multiple variables expressed as a Taylor series with a finite number of terms. We demonstrate the method for evaluating the coefficient of each term to define this function unambiguously for any given entity, and illustrate its use to determine the entity's position at any point in time in the future.

  14. Local functional descriptors for surface comparison based binding prediction

    PubMed Central

    2012-01-01

    Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

  15. Plasma D-dimer may predict poor functional outcomes through systemic complications after aneurysmal subarachnoid hemorrhage.

    PubMed

    Fukuda, Hitoshi; Lo, Benjamin; Yamamoto, Yu; Handa, Akira; Yamamoto, Yoshiharu; Kurosaki, Yoshitaka; Yamagata, Sen

    2016-08-12

    OBJECTIVE Plasma D-dimer levels elevate during acute stages of aneurysmal subarachnoid hemorrhage (SAH) and are associated with poor functional outcomes. However, the mechanism in which D-dimer elevation on admission affects functional outcomes remains unknown. The aim of this study is to clarify whether D-dimer levels on admission are correlated with systemic complications after aneurysmal SAH, and to investigate their additive predictive value on conventional risk factors for poor functional outcomes. METHODS A total of 187 patients with aneurysmal SAH were retrospectively analyzed from a single-center, observational cohort database. Correlations of plasma D-dimer levels on admission with patient characteristics, initial presentation, neurological complications, and systemic complications were identified. The authors also evaluated the additive value of D-dimer elevation on admission for poor functional outcomes by comparing predictive models with and without D-dimer. RESULTS D-dimer elevation on admission was associated with increasing age, female sex, and severity of SAH. Patients with higher D-dimer levels had increased likelihood of nosocomial infections (OR 1.22 [95% CI 1.07-1.39], p = 0.004), serum sodium disorders (OR 1.11 [95% CI 1.01-1.23], p = 0.033), and cardiopulmonary complications (OR 1.20 [95% CI 1.04-1.37], p = 0.01) on multivariable analysis. D-dimer elevation was an independent risk factor of poor functional outcome (modified Rankin Scale Score 3-6, OR 1.50 [95% CI 1.15-1.95], p = 0.003). A novel prediction model with D-dimer had significantly better discrimination ability for poor outcomes than conventional models without D-dimer. CONCLUSIONS Elevated D-dimer levels on admission were independently correlated with systemic complication, and had an additive value for outcome prediction on conventional risk factors after aneurysmal SAH.

  16. HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction

    PubMed Central

    Zhang, Xu; You, Zhu-Hong; Huang, Yu-An; Yan, Gui-Ying

    2016-01-01

    Recently, microRNAs (miRNAs) have drawn more and more attentions because accumulating experimental studies have indicated miRNA could play critical roles in multiple biological processes as well as the development and progression of human complex diseases. Using the huge number of known heterogeneous biological datasets to predict potential associations between miRNAs and diseases is an important topic in the field of biology, medicine, and bioinformatics. In this study, considering the limitations in the previous computational methods, we developed the computational model of Heterogeneous Graph Inference for MiRNA-Disease Association prediction (HGIMDA) to uncover potential miRNA-disease associations by integrating miRNA functional similarity, disease semantic similarity, Gaussian interaction profile kernel similarity, and experimentally verified miRNA-disease associations into a heterogeneous graph. HGIMDA obtained AUCs of 0.8781 and 0.8077 based on global and local leave-one-out cross validation, respectively. Furthermore, HGIMDA was applied to three important human cancers for performance evaluation. As a result, 90% (Colon Neoplasms), 88% (Esophageal Neoplasms) and 88% (Kidney Neoplasms) of top 50 predicted miRNAs are confirmed by recent experiment reports. Furthermore, HGIMDA could be effectively applied to new diseases and new miRNAs without any known associations, which overcome the important limitations of many previous computational models. PMID:27533456

  17. Predicting habitat associations of five intertidal crab species among estuaries

    NASA Astrophysics Data System (ADS)

    Vermeiren, Peter; Sheaves, Marcus

    2014-08-01

    Intertidal crab assemblages that are active on the sediment surface of tropical estuaries during tidal exposure play an important role in many fundamental ecosystem processes. Consequently, they are critical contributors to a wide range of estuarine goods and services. However, a lack of understanding of their spatial organization within a large landscape context prevents the inclusion of intertidal crabs into generally applicable ecological models and management applications. We investigated spatial distribution patterns of intertidal crabs within and among eight dry tropical estuaries spread across a 160 km stretch of coast in North East Queensland, Australia. Habitat associations were modelled for five species based on photographic sampling in 40-80 sites per estuarine up- and downstream component: Uca seismella occurred in sites with little structure, bordered by low intertidal vegetation; Macrophthalmus japonicus occupied flat muddy sites with no structure or vegetation; Metopograpsus frontalis and Metopograpsus latifrons occupied sites covered with structure in more than 10% and 25% respectively. Finally, both Metopograpsus spp. and Metopograpsus thukuhar occupied rock walls. Habitat associations were predictable among estuaries with moderate to high sensitivity and low percentages of false positives indicating that simple, physical factors were adequate to explain the spatial distribution pattern of intertidal crabs. Results provide a necessary first step in developing generally applicable understanding of the fundamental mechanisms driving spatial niche organization of intertidal crabs within a landscape context.

  18. Mini-Nutritional-Assessment (MNA) without body mass index (BMI) predicts functional disability in elderly Taiwanese.

    PubMed

    Lee, Li-Chin; Tsai, Alan Chung-hong

    2012-01-01

    Nutritional status and functional ability are mutually dependent especially in the elderly. This study examined the functional status-predictive ability of the MNA in a cross-sectional study. We analyzed the dataset of the "Survey of Health and Living Status of the Elderly in Taiwan" (SHLSET). Subjects were 2948≥65 year-old persons who were rated with the long-form (LF) and short-form (SF) MNA with or without BMI for the risk of malnutrition, and with the Activities of Daily Living (ADL) and the Instrument Activities of Daily Living (IADL) for functional status. The ADL and IADL scores were calculated according to rated nutritional status. Receiver Operating Characteristic (ROC) curves were generated for ADL and IADL status predicted by the MNA. Logistic regression was performed to evaluate the association of rated MNA scores with ADL or IADL status. Results showed that both SF and LF of MNA-T1 and T2 were able to predict ADL and IADL disabilities. Those who were rated malnourished or at risk of malnutrition had drastically higher risk of ADL or IADL dependency compared to those who were rated normal. The SF versions performed well in rating nutritional status and predicting ADL and IADL status. Overall, MNA-T2-SF performed at least equally well as MNA-T1-SF in rating functional decline. These results suggest the MNA is able to predict functional decline of the elderly. MNA-T2, especially the SF, a version without BMI should be particularly useful in clinical, long-term care and community settings.

  19. Cutaneous Functional Units Predict Shoulder Range of Motion Recovery in Children Receiving Rehabilitation.

    PubMed

    Parry, Ingrid; Sen, Soman; Sattler-Petrocchi, Kelly; Greenhalgh, David; Palmieri, Tina

    Cutaneous functional units (CFUs) are fields of skin that functionally contribute to range of motion (ROM) at an associated joint. When replaced with scar tissue, the skin is less extensible and may result in loss of movement at the joint. Consideration of the amount of CFU affected by burn injury is increasingly being used to predict the development of burn scar contracture (BSC) in burn survivors. Previous work established that, in adults, burn rehabilitation time per CFU was the greatest predictor of preventing BSC. Our study aimed to examine the direct relationship between percent involvement of CFU and ROM achieved in children with BSC who received 6 months of rehabilitation therapy services. ROM was measured at baseline and throughout the study period using traditional methods of goniometry as well as three-dimensional motion capture during the performance of functional tasks. Burn extent and distribution were mapped using an electronic diagram to calculate the percentage of CFU affected by scarring or skin grafts. Pearson's correlations and multivariate linear regression analyses were performed to determine associations between variables. Results showed that percent CFU involvement was negatively correlated with maximal goniometric and functional shoulder ROM achieved. That is, the amount of a given CFU scarred was predictive of less ROM achieved in the associated area. Percentage of CFU involved did not significantly correlate with baseline shoulder ROM, suggesting that other factors may be associated with initial limitations in ROM. Evaluation of the percentage of CFU scarred is useful for predicting shoulder ROM recovery with rehabilitation and may be used to help guide clinical decision making and allocation of time and resource for therapy services.

  20. Efficacy of functional movement screening for predicting injuries in coast guard cadets.

    PubMed

    Knapik, Joseph J; Cosio-Lima, Ludimila M; Reynolds, Katy L; Shumway, Richard S

    2015-05-01

    Functional movement screening (FMS) examines the ability of individuals to perform highly specific movements with the aim of identifying individuals who have functional limitations or asymmetries. It is assumed that individuals who can more effectively accomplish the required movements have a lower injury risk. This study determined the ability of FMS to predict injuries in the United States Coast Guard (USCG) cadets. Seven hundred seventy male and 275 female USCG freshman cadets were administered the 7 FMS tests before the physically intense 8-week Summer Warfare Annual Basic (SWAB) training. Physical training-related injuries were recorded during SWAB training. Cumulative injury incidence was calculated at various FMS cutpoint scores. The ability of the FMS total score to predict injuries was examined by calculating sensitivity and specificity. Determination of the FMS cutpoint that maximized specificity and sensitivity was determined from the Youden's index (sensitivity + specificity - 1). For men, FMS scores ≤ 12 were associated with higher injury risk than scores >12; for women, FMS scores ≤ 15 were associated with higher injury risk than scores >15. The Youden's Index indicated that the optimal FMS cutpoint was ≤ 11 for men (22% sensitivity, 87% specificity) and ≤ 14 for women (60% sensitivity, 61% specificity). Functional movement screening demonstrated moderate prognostic accuracy for determining injury risk among female Coast Guard cadets but relatively low accuracy among male cadets. Attempting to predict injury risk based on the FMS test seems to have some limited promise based on the present and past investigations.

  1. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

    PubMed Central

    Langille, Morgan G. I.; Zaneveld, Jesse; Caporaso, J. Gregory; McDonald, Daniel; Knights, Dan; Reyes, Joshua A.; Clemente, Jose C.; Burkepile, Deron E.; Vega Thurber, Rebecca L.; Knight, Rob; Beiko, Robert G.; Huttenhower, Curtis

    2013-01-01

    Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available. PMID:23975157

  2. Probability-based prediction of activity in multiple arm muscles: implications for functional electrical stimulation.

    PubMed

    Anderson, Chad V; Fuglevand, Andrew J

    2008-07-01

    Functional electrical stimulation (FES) involves artificial activation of muscles with implanted electrodes to restore motor function in paralyzed individuals. The range of motor behaviors that can be generated by FES, however, is limited to a small set of preprogrammed movements such as hand grasp and release. A broader range of movements has not been implemented because of the substantial difficulty associated with identifying the patterns of muscle stimulation needed to elicit specified movements. To overcome this limitation in controlling FES systems, we used probabilistic methods to estimate the levels of muscle activity in the human arm during a wide range of free movements based on kinematic information of the upper limb. Conditional probability distributions were generated based on hand kinematics and associated surface electromyographic (EMG) signals from 12 arm muscles recorded during a training task involving random movements of the arm in one subject. These distributions were then used to predict in four other subjects the patterns of muscle activity associated with eight different movement tasks. On average, about 40% of the variance in the actual EMG signals could be accounted for in the predicted EMG signals. These results suggest that probabilistic methods ultimately might be used to predict the patterns of muscle stimulation needed to produce a wide array of desired movements in paralyzed individuals with FES.

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

    PubMed

    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 intervene

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

    PubMed Central

    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

  5. Examination of Associations Among Three Distinct Subjective Aging Constructs and Their Relevance for Predicting Developmental Correlates.

    PubMed

    Brothers, Allyson; Miche, Martina; Wahl, Hans-Werner; Diehl, Manfred

    2017-07-01

    This study examined (a) the empirical associations among three subjective aging (SA) constructs: felt age, attitudes toward own aging (ATOA), and awareness of age-related change (AARC); (b) the moderating role of chronological age in these associations; and (c) the predictive relevance of the SA constructs with regard to two developmental correlates: functional health and satisfaction with life. Participants were 819 adults aged 40-98 years from the United States and Germany. Parallel multiple mediation, moderated mediation, and hierarchical regression analyses were used. As hypothesized, AARC mediated the association between the global measures of SA (felt age and ATOA) and the developmental correlates. Specifically, more negative global subjective aging predicted more AARC losses, which predicted poorer health and well-being. Furthermore, this mediation pathway was moderated by chronological age, such that, with increasing age, greater AARC was more strongly related to poorer functional health (but not well-being). The multidimensional measure, AARC, accounted for a significant amount of the variance in the developmental correlates over and above the unidimensional SA constructs. A consistent pattern emerged supporting the role of domain specificity and valence. These findings support the need for conceptualizing SA across different behavioral domains and for distinguishing between positive and negative SA.

  6. Association between Preoperative Vascular Function and Postoperative Arteriovenous Fistula Development.

    PubMed

    Allon, Michael; Greene, Tom; Dember, Laura M; Vita, Joseph A; Cheung, Alfred K; Hamburg, Naomi M; Imrey, Peter B; Kaufman, James S; Robbin, Michelle L; Shiu, Yan-Ting; Terry, Christi M; Umphrey, Heidi R; Feldman, Harold I

    2016-12-01

    Arteriovenous fistula (AVF) maturation failure is the primary cause of dialysis vascular access dysfunction. To evaluate whether preoperative vascular functional properties predict postoperative AVF measurements, patients enrolled in the Hemodialysis Fistula Maturation Study underwent up to five preoperative vascular function tests (VFTs): flow-mediated dilation (FMD), nitroglycerin-mediated dilation (NMD), carotid-femoral pulse wave velocity, carotid-radial pulse wave velocity, and venous occlusion plethysmography. We used mixed effects multiple regression analyses to relate each preoperative VFT to ultrasound measurements of AVF blood flow rate and venous diameter at 1 day, 2 weeks, and 6 weeks after AVF placement. After controlling for AVF location, preoperative ultrasound measurements, and demographic factors (age, sex, race, and dialysis status), greater NMD associated with greater 6-week AVF blood flow rate and AVF diameter (per absolute 10% difference in NMD: change in blood flow rate =14.0%; 95% confidence interval [95% CI], 3.7% to 25.3%; P<0.01; change in diameter =0.45 mm; 95% CI, 0.25 to 0.65 mm; P<0.001). Greater FMD also associated with greater increases in 6-week AVF blood flow rate and AVF diameter (per absolute 10% difference in FMD: change in blood flow rate =11.6%; 95% CI, 0.6% to 23.9%; P=0.04; change in diameter =0.31 mm; 95% CI, 0.05 to 0.57 mm; P=0.02). None of the remaining VFT parameters exhibited consistent statistically significant relationships with both postoperative AVF blood flow rate and diameter. In conclusion, preoperative NMD and FMD positively associated with changes in 6-week AVF blood flow rate and diameter, suggesting that native functional arterial properties affect AVF development. Copyright © 2016 by the American Society of Nephrology.

  7. The functions of contexts in associative learning

    PubMed Central

    Urcelay, Gonzalo P.; Miller, Ralph R.

    2014-01-01

    Although contexts play many roles during training and also during testing, over the last four decades theories of learning have predominantly focused on one or the other of two families of functions served by contexts. In this selective review, we summarize recent data concerning these two functions and their interrelationship. The first function is similar to that of discrete cues, and allows contexts to elicit conditioned responses and compete with discrete events for behavioral control. The second function is modulatory, and similar to that of discrete occasion setters in that in this role contexts do not elicit conditioned responses by themselves, but rather modulate instrumental responding or responding to Pavlovian cues. We first present evidence for these two functions, and then suggest that the spacing of trials, amount of training, and contiguity are three determinants of the degree to which the context will play each function. We also conclude that these two functions are not mutually exclusive, and that future research would benefit from identifying the conditions under which their functions dominate behavioral control. We close by discussing some misconceptions concerning contexts. PMID:24614400

  8. The functions of contexts in associative learning.

    PubMed

    Urcelay, Gonzalo P; Miller, Ralph R

    2014-05-01

    Although contexts play many roles during training and also during testing, over the last four decades theories of learning have predominantly focused on one or the other of the two families of functions served by contexts. In this selective review, we summarize recent data concerning these two functions and their interrelationship. The first function is similar to that of discrete cues, and allows contexts to elicit conditioned responses and compete with discrete events for behavioral control. The second function is modulatory, and similar to that of discrete occasion setters in that in this role contexts do not elicit conditioned responses by themselves, but rather modulate instrumental responding or responding to Pavlovian cues. We first present evidence for these two functions, and then suggest that the spacing of trials, amount of training, and contiguity are three determinants of the degree to which the context will play each function. We also conclude that these two functions are not mutually exclusive, and that future research would benefit from identifying the conditions under which their functions dominate behavioral control. We close by discussing some misconceptions concerning contexts. This article is part of a Special Issue entitled: SQAB 2013: Contextual Con.

  9. Integration of relational and hierarchical network information for protein function prediction.

    PubMed

    Jiang, Xiaoyu; Nariai, Naoki; Steffen, Martin; Kasif, Simon; Kolaczyk, Eric D

    2008-08-22

    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. 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. 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 positive predictive value), and that this increase is

  10. Genome-wide association study identifies TH1 pathway genes associated with lung function in asthmatic patients

    PubMed Central

    Li, Xingnan; Hawkins, Gregory A.; Ampleford, Elizabeth J.; Moore, Wendy C.; Li, Huashi; Hastie, Annette T.; Howard, Timothy D.; Boushey, Homer A.; Busse, William W.; Calhoun, William J.; Castro, Mario; Erzurum, Serpil C.; Israel, Elliot; Lemanske, Robert F.; Szefler, Stanley J.; Wasserman, Stephen I.; Wenzel, Sally E.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

    2013-01-01

    Background Recent meta-analyses of genome-wide association studies in general populations of European descent have identified 28 loci for lung function. Objective We sought to identify novel lung function loci specifically for asthma and to confirm lung function loci identified in general populations. Methods Genome-wide association studies of lung function (percent predicted FEV1 [ppFEV1], percent predicted forced vital capacity, and FEV1/forced vital capacity ratio) were performed in 4 white populations of European descent (n = 1544), followed by meta-analyses. Results Seven of 28 previously identified lung function loci (HHIP, FAM13A, THSD4, GSTCD, NOTCH4-AGER, RARB, and ZNF323) identified in general populations were confirmed at single nucleotide polymorphism (SNP) levels (P < .05). Four of 32 loci (IL12A, IL12RB1, STAT4, and IRF2) associated with ppFEV1 (P < 10−4) belong to the TH1 or IL-12 cytokine family pathway. By using a linear additive model, these 4 TH1 pathway SNPs cumulatively explained 2.9% to 7.8% of the variance in ppFEV1 values in 4 populations (P = 3 × 10−11). Genetic scores of these 4 SNPs were associated with ppFEV1 values (P = 2 × 10−7) and the American Thoracic Society severe asthma classification (P = .005) in the Severe Asthma Research Program population. TH2 pathway genes (IL13, TSLP, IL33, and IL1RL1) conferring asthma susceptibility were not associated with lung function. Conclusion Genes involved in airway structure/remodeling are associated with lung function in both general populations and asthmatic subjects. TH1 pathway genes involved in anti-virus/bacterial infection and inflammation modify lung function in asthmatic subjects. Genes associated with lung function that might affect asthma severity are distinct from those genes associated with asthma susceptibility. PMID:23541324

  11. Genome-wide association study identifies TH1 pathway genes associated with lung function in asthmatic patients.

    PubMed

    Li, Xingnan; Hawkins, Gregory A; Ampleford, Elizabeth J; Moore, Wendy C; Li, Huashi; Hastie, Annette T; Howard, Timothy D; Boushey, Homer A; Busse, William W; Calhoun, William J; Castro, Mario; Erzurum, Serpil C; Israel, Elliot; Lemanske, Robert F; Szefler, Stanley J; Wasserman, Stephen I; Wenzel, Sally E; Peters, Stephen P; Meyers, Deborah A; Bleecker, Eugene R

    2013-08-01

    Recent meta-analyses of genome-wide association studies in general populations of European descent have identified 28 loci for lung function. We sought to identify novel lung function loci specifically for asthma and to confirm lung function loci identified in general populations. Genome-wide association studies of lung function (percent predicted FEV1 [ppFEV1], percent predicted forced vital capacity, and FEV1/forced vital capacity ratio) were performed in 4 white populations of European descent (n = 1544), followed by meta-analyses. Seven of 28 previously identified lung function loci (HHIP, FAM13A, THSD4, GSTCD, NOTCH4-AGER, RARB, and ZNF323) identified in general populations were confirmed at single nucleotide polymorphism (SNP) levels (P < .05). Four of 32 loci (IL12A, IL12RB1, STAT4, and IRF2) associated with ppFEV1 (P < 10(-4)) belong to the TH1 or IL-12 cytokine family pathway. By using a linear additive model, these 4 TH1 pathway SNPs cumulatively explained 2.9% to 7.8% of the variance in ppFEV1 values in 4 populations (P = 3 × 10(-11)). Genetic scores of these 4 SNPs were associated with ppFEV1 values (P = 2 × 10(-7)) and the American Thoracic Society severe asthma classification (P = .005) in the Severe Asthma Research Program population. TH2 pathway genes (IL13, TSLP, IL33, and IL1RL1) conferring asthma susceptibility were not associated with lung function. Genes involved in airway structure/remodeling are associated with lung function in both general populations and asthmatic subjects. TH1 pathway genes involved in anti-virus/bacterial infection and inflammation modify lung function in asthmatic subjects. Genes associated with lung function that might affect asthma severity are distinct from those genes associated with asthma susceptibility. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

  12. Predicting Functional Status Following Amputation After Lower Extremity Bypass

    PubMed Central

    Suckow, Bjoern D.; Goodney, Philip P.; Cambria, Robert A.; Bertges, Daniel J.; Eldrup-Jorgensen, Jens; Indes, Jeffrey E.; Schanzer, Andres; Stone, David H.; Kraiss, Larry W.; Cronenwett, Jack L.

    2012-01-01

    Background Some patients who undergo lower extremity bypass (LEB) for critical limb ischemia ultimately require amputation. The functional outcome achieved by these patients after amputation is not well known. Therefore, we sought to characterize the functional outcome of patients who undergo amputation after LEB, and to describe the pre- and perioperative factors associated with independent ambulation at home after lower extremity amputation. Methods Within a cohort of 3,198 patients who underwent an LEB between January, 2003 and December, 2008, we studied 436 patients who subsequently received an above-knee (AK), below-knee (BK), or minor (forefoot or toe) ipsilateral or contralateral amputation. Our main outcome measure consisted of a “good functional outcome,” defined as living at home and ambulating independently. We calculated univariate and multivariate associations among patient characteristics and our main outcome measure, as well as overall survival. Results Of the 436 patients who underwent amputation within the first year following LEB, 224 of 436 (51.4%) had a minor amputation, 105 of 436 (24.1%) had a BK amputation, and 107 of 436 (24.5%) had an AK amputation. The majority of AK (75 of 107, 72.8%) and BK amputations (72 of 105, 70.6%) occurred in the setting of bypass graft thrombosis, whereas nearly all minor amputations (200 of 224, 89.7%) occurred with a patent bypass graft. By life-table analysis at 1 year, we found that the proportion of surviving patients with a good functional outcome varied by the presence and extent of amputation (proportion surviving with good functional outcome = 88% no amputation, 81% minor amputation, 55% BK amputation, and 45% AK amputation, p = 0.001). Among those analyzed at long-term follow-up, survival was slightly lower for those who had a minor amputation when compared with those who did not receive an amputation after LEB (81 vs. 88%, p = 0.02). Survival among major amputation patients did not significantly

  13. Functional imaging in tumor-associated lymphatics

    NASA Astrophysics Data System (ADS)

    Kwon, Sunkuk; Sevick-Muraca, Eva M.

    2011-03-01

    The lymphatic system plays an important role in cancer cell dissemination; however whether lymphatic drainage pathways and function change during tumor progression and metastasis remains to be elucidated. In this report, we employed a non-invasive, dynamic near-infrared (NIR) fluorescence imaging technique for functional lymphatic imaging. Indocyanine green (ICG) was intradermally injected into tumor-free mice and mice bearing C6/LacZ rat glioma tumors in the tail or hindlimb. Our imaging data showed abnormal lymphatic drainage pathways and reduction/loss of lymphatic contractile function in mice with lymph node (LN) metastasis, indicating that cancer metastasis to the draining LNs is accompanied by transient changes of the lymphatic architectural network and its function. Therefore, functional lymphatic imaging may provide a role in the clinical staging of cancer.

  14. Striatal structure and function predict individual biases in learning to avoid pain.

    PubMed

    Eldar, Eran; Hauser, Tobias U; Dayan, Peter; Dolan, Raymond J

    2016-04-26

    Pain is an elemental inducer of avoidance. Here, we demonstrate that people differ in how they learn to avoid pain, with some individuals refraining from actions that resulted in painful outcomes, whereas others favor actions that helped prevent pain. These individual biases were best explained by differences in learning from outcome prediction errors and were associated with distinct forms of striatal responses to painful outcomes. Specifically, striatal responses to pain were modulated in a manner consistent with an aversive prediction error in individuals who learned predominantly from pain, whereas in individuals who learned predominantly from success in preventing pain, modulation was consistent with an appetitive prediction error. In contrast, striatal responses to success in preventing pain were consistent with an appetitive prediction error in both groups. Furthermore, variation in striatal structure, encompassing the region where pain prediction errors were expressed, predicted participants' predominant mode of learning, suggesting the observed learning biases may reflect stable individual traits. These results reveal functional and structural neural components underlying individual differences in avoidance learning, which may be important contributors to psychiatric disorders involving pathological harm avoidance behavior.

  15. Striatal structure and function predict individual biases in learning to avoid pain

    PubMed Central

    Eldar, Eran; Hauser, Tobias U.; Dayan, Peter; Dolan, Raymond J.

    2016-01-01

    Pain is an elemental inducer of avoidance. Here, we demonstrate that people differ in how they learn to avoid pain, with some individuals refraining from actions that resulted in painful outcomes, whereas others favor actions that helped prevent pain. These individual biases were best explained by differences in learning from outcome prediction errors and were associated with distinct forms of striatal responses to painful outcomes. Specifically, striatal responses to pain were modulated in a manner consistent with an aversive prediction error in individuals who learned predominantly from pain, whereas in individuals who learned predominantly from success in preventing pain, modulation was consistent with an appetitive prediction error. In contrast, striatal responses to success in preventing pain were consistent with an appetitive prediction error in both groups. Furthermore, variation in striatal structure, encompassing the region where pain prediction errors were expressed, predicted participants’ predominant mode of learning, suggesting the observed learning biases may reflect stable individual traits. These results reveal functional and structural neural components underlying individual differences in avoidance learning, which may be important contributors to psychiatric disorders involving pathological harm avoidance behavior. PMID:27071092

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

    PubMed

    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.

  17. Predicting performance on the Columbia Card Task: effects of personality characteristics, mood, and executive functions.

    PubMed

    Buelow, Melissa T

    2015-04-01

    Behavioral measures of risky decision making are frequently used by researchers and clinicians; however, most of these measures are strongly associated with personality characteristics and state mood. The present study sought to examine personality, mood, and executive function predictors of performance on a newer measure of decision making, the Columbia Card Task (CCT). Participants were 489 undergraduate students who completed either the hot or cold version of the CCT as well as measures of state mood, impulsive sensation seeking, behavioral inhibition and activation systems, and executive functions (Wisconsin Card Sort Task; Digit Span). Results indicated that performance on the CCT-cold was predicted by Wisconsin Card Sort Task errors, and Digit Span predicted the CCT-hot. In addition, significant correlations were found between the CCT information use variables and the predictor variables. Implications for the utility of the CCT as a clinical instrument and its relationship with other measures of decision making are discussed.

  18. The Prediction of Broadband Shock-Associated Noise Including Propagation Effects

    NASA Technical Reports Server (NTRS)

    Miller, Steven; Morris, Philip J.

    2011-01-01

    An acoustic analogy is developed based on the Euler equations for broadband shock- associated noise (BBSAN) that directly incorporates the vector Green's function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) as the mean flow. The vector Green's function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation. An adjoint vector Green's function solver is implemented to determine the vector Green's function based on a locally parallel mean flow at streamwise locations of the SRANS solution. However, the developed acoustic analogy could easily be based on any adjoint vector Green's function solver, such as one that makes no assumptions about the mean flow. The newly developed acoustic analogy can be simplified to one that uses the Green's function associated with the Helmholtz equation, which is consistent with the formulation of Morris and Miller (AIAAJ 2010). A large number of predictions are generated using three different nozzles over a wide range of fully expanded Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise labs. In addition, two models for the so-called 'fine-scale' mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include the propagation effects, especially in the upstream direction of the jet.

  19. The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements.

    PubMed

    Altenhoff, Adrian M; Škunca, Nives; Glover, Natasha; Train, Clément-Marie; Sueki, Anna; Piližota, Ivana; Gori, Kevin; Tomiczek, Bartlomiej; Müller, Steven; Redestig, Henning; Gonnet, Gaston H; Dessimoz, Christophe

    2015-01-01

    The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for 'client-side' orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org.

  20. The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements

    PubMed Central

    Altenhoff, Adrian M.; Škunca, Nives; Glover, Natasha; Train, Clément-Marie; Sueki, Anna; Piližota, Ivana; Gori, Kevin; Tomiczek, Bartlomiej; Müller, Steven; Redestig, Henning; Gonnet, Gaston H.; Dessimoz, Christophe

    2015-01-01

    The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for ‘client-side’ orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org. PMID:25399418

  1. Renal function decline predicted by left atrial expansion index in non-diabetic cohort with preserved systolic heart function.

    PubMed

    Hsiao, Shih-Hung; Chiou, Kuan-Rau

    2017-05-01

    Since natriuretic peptide and troponin are associated with renal prognosis and left atrial (LA) parameters are indicators of subclinical cardiovascular abnormalities, this study investigated whether LA expansion index can predict renal decline. This study analysed 733 (69% male) non-diabetic patients with sinus rhythm, preserved systolic function, and estimated glomerular filtration rate (eGFR) higher than 60 mL/min/1.73 m2. In all patients, echocardiograms were performed and LA expansion index was calculated. Renal function was evaluated annually. The endpoint was a downhill trend in renal function with a final eGFR of <60 mL/min/1.73 m2. Rapid renal decline was defined as an annual decline in eGFR >3 mL/min/1.73 m2. The median follow-up time was 5.2 years, and 57 patients (7.8%) had renal function declines (19 had rapid renal declines, and 38 had incidental renal dysfunction). Events were associated with left ventricular mass index, LA expansion index, and heart failure during the follow-up period. The hazard ratio was 1.426 (95% confidence interval, 1.276-1.671; P < 0.0001) per 10% decrease in LA expansion index and was independently associated with an increased event rate. Compared with the highest quartile for the LA expansion index, the lowest quartile had a 9.7-fold risk of renal function decline in the unadjusted model and a 6.9-fold risk after adjusting for left ventricular mass index and heart failure during the follow-up period. Left atrial expansion index is a useful early indicator of renal function decline and may enable the possibility of early intervention to prevent renal function from worsening. NCT01171040.

  2. Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

    PubMed

    Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

    2016-08-01

    Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms.

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

    PubMed

    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.

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

    PubMed Central

    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

    2015-01-01

    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. PMID:25567651

  5. Radiomic Texture Analysis Mapping Predicts Areas of True Functional MRI Activity

    PubMed Central

    Hassan, Islam; Kotrotsou, Aikaterini; Bakhtiari, Ali Shojaee; Thomas, Ginu A.; Weinberg, Jeffrey S.; Kumar, Ashok J.; Sawaya, Raymond; Luedi, Markus M.; Zinn, Pascal O.; Colen, Rivka R.

    2016-01-01

    Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias. PMID:27151623

  6. Prospective evaluation of Protein C and Factor VIII in prediction of cancer-associated thrombosis

    PubMed Central

    Tafur, AJ; Dale, G; Cherry, M; Wren, JD; Mansfield, AS; Comp, P; Rathbun, S; Stoner, JA

    2015-01-01

    Venous thromboembolism (VTE) is a preventable disease, yet it is one of the leading causes of death among patients with cancer. Improving risk stratification mechanisms will allow us to personalize thromboprophylaxis strategies. We sought to evaluate Collagen and Thrombin Activated Platelets (COAT-platelets) as well as protein C and factor VIII as biomarkers predictive of cancer-associated thrombosis in a prospective cohort of patients with cancer. Protein C was selected as a candidate based on bioinformatics prediction. Blood samples were collected before chemotherapy. All specimen processing was blinded to clinical data. Surveillance and adjudication of the main outcome of VTE was performed for up to 1 year. We used Cox proportional hazard regression to measure the association of biomarkers and incident events using SAS 9.2 for all statistical analysis. Death was modeled as a competing event. Among 241 patients followed for an average of 10.4 months, 15% died and 13% developed a VTE. COAT-platelets were not predictive of VTE. Low levels of pre-chemotherapy protein C (< 118 %) (HR 2.5; 95%CI 1.1–5.5) and high baseline factor VIII (> 261 % I) (HR 3.0; 95%CI 1.1–8.0) were predictive of VTE after adjusting for age, Khorana prediction risk, metastatic disease and D dimer. In addition, low protein C was predictive of overall mortality independent of age, metastatic disease and functional status (HR 2.8; 95%CI 1.3–6.0). Addition of these biomarkers to Cancer-VTE risk prediction models may add to risk stratification and patient selection to optimize thrombo-prophylaxis. PMID:26475410

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

    PubMed

    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 < 0.001; standard error of the 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.

  8. Error estimates for density-functional theory predictions of surface energy and work function

    NASA Astrophysics Data System (ADS)

    De Waele, Sam; Lejaeghere, Kurt; Sluydts, Michael; Cottenier, Stefaan

    2016-12-01

    Density-functional theory (DFT) predictions of materials properties are becoming ever more widespread. With increased use comes the demand for estimates of the accuracy of DFT results. In view of the importance of reliable surface properties, this work calculates surface energies and work functions for a large and diverse test set of crystalline solids. They are compared to experimental values by performing a linear regression, which results in a measure of the predictable and material-specific error of the theoretical result. Two of the most prevalent functionals, the local density approximation (LDA) and the Perdew-Burke-Ernzerhof parametrization of the generalized gradient approximation (PBE-GGA), are evaluated and compared. Both LDA and GGA-PBE are found to yield accurate work functions with error bars below 0.3 eV, rivaling the experimental precision. LDA also provides satisfactory estimates for the surface energy with error bars smaller than 10%, but GGA-PBE significantly underestimates the surface energy for materials with a large correlation energy.

  9. Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy

    PubMed Central

    Wang, Y.; Barth, P.

    2016-01-01

    How specific protein associations regulate the function of membrane receptors remains poorly understood. Conformational flexibility currently hinders the structure determination of several classes of membrane receptors and associated oligomers. Here we develop EFDOCK-TM, a general method to predict self-associated transmembrane protein helical (TMH) structures from sequence guided by co-evolutionary information. We show that accurate intermolecular contacts can be identified using a combination of protein sequence covariation and TMH binding surfaces predicted from sequence. When applied to diverse TMH oligomers, including receptors characterized in multiple conformational and functional states, the method reaches unprecedented near-atomic accuracy for most targets. Blind predictions of structurally uncharacterized receptor tyrosine kinase TMH oligomers provide a plausible hypothesis on the molecular mechanisms of disease-associated point mutations and binding surfaces for the rational design of selective inhibitors. The method sets the stage for uncovering novel determinants of molecular recognition and signalling in single-spanning eukaryotic membrane receptors. PMID:25995083

  10. Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Barth, P.

    2015-05-01

    How specific protein associations regulate the function of membrane receptors remains poorly understood. Conformational flexibility currently hinders the structure determination of several classes of membrane receptors and associated oligomers. Here we develop EFDOCK-TM, a general method to predict self-associated transmembrane protein helical (TMH) structures from sequence guided by co-evolutionary information. We show that accurate intermolecular contacts can be identified using a combination of protein sequence covariation and TMH binding surfaces predicted from sequence. When applied to diverse TMH oligomers, including receptors characterized in multiple conformational and functional states, the method reaches unprecedented near-atomic accuracy for most targets. Blind predictions of structurally uncharacterized receptor tyrosine kinase TMH oligomers provide a plausible hypothesis on the molecular mechanisms of disease-associated point mutations and binding surfaces for the rational design of selective inhibitors. The method sets the stage for uncovering novel determinants of molecular recognition and signalling in single-spanning eukaryotic membrane receptors.

  11. Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure

    PubMed Central

    Nilmeier, Jerome P.; Kirshner, Daniel A.; Wong, Sergio E.; Lightstone, Felice C.

    2013-01-01

    We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues – The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches. PMID:23675414

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

    PubMed

    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

  13. Resting-state functional connectivity predicts impulsivity in economic decision-making.

    PubMed

    Li, Nan; Ma, Ning; Liu, Ying; He, Xiao-Song; Sun, De-Lin; Fu, Xian-Ming; Zhang, Xiaochu; Han, Shihui; Zhang, Da-Ren

    2013-03-13

    Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (DDT) that requires choosing between an immediate smaller reward and a larger delayed reward. In experiment I, we identified four DDT-related brain networks. The money network (the striatum, posterior cingulate cortex, etc.) and the time network (the medial and dorsolateral prefrontal cortices, etc.) were associated with the valuation process; the frontoparietal network and the dorsal anterior cingulate cortex-anterior insular cortex network were related to the choice process. Moreover, we found that the resting-state functional connectivity of the brain regions in these networks was significantly correlated with participants' discounting rate, a behavioral index of impulsivity during the DDT. In experiment II, we tested an independent group of subjects and demonstrated that this resting-state functional connectivity was able to predict individuals' discounting rates. Together, these findings suggest that resting-state functional organization of the human brain may be a biomarker of impulsivity and can predict economic decision-making behavior.

  14. A Nonmonotonic Lag Function for False Alarms to Associates

    ERIC Educational Resources Information Center

    MacLeod, Colin M.; Nelson, Thomas O.

    1976-01-01

    Of all the studies examining recognition of semantically related words, none has systematically varied lag to test the straightforward prediction of a monotonic decrease in false alarms to new words semantically related to prior words. The present experiment, using semantic associates, tested this prediction. (Author)

  15. More Daytime Sleeping Predicts Less Functional Recovery Among Older People Undergoing Inpatient Post-Acute Rehabilitation

    PubMed Central

    Alessi, Cathy A.; Martin, Jennifer L.; Webber, Adam P.; Alam, Tarannum; Littner, Michael R.; Harker, Judith O.; Josephson, Karen R.

    2008-01-01

    Study Objectives: To study the association between sleep/wake patterns among older adults during inpatient post-acute rehabilitation and their immediate and long-term functional recovery Design: Prospective, observational cohort study Setting: Two inpatient post-acute rehabilitation sites (one community and one Veterans Administration) Participants: Older patients (aged ≥ 65 years, N = 245) admitted for inpatient post-acute rehabilitation Interventions: None Measurements and Results: Based on 7-day wrist actigraphy during the rehabilitation stay, mean nighttime percent sleep was only 52.2% and mean daytime percent sleep was 15.8% (16.3% based on structured behavioral observations). Using the Pittsburgh Sleep Quality Index (PSQI), participants reported their sleep was worse during rehabilitation compared to their premorbid sleep. Functional recovery between admission and discharge from rehabilitation (measured by the motor component of the Functional Independence Measure) was not significantly associated with reported sleep quality (PSQI scores) or actigraphically measured nighttime sleep. However, more daytime percent sleep (estimated by actigraphy and observations) during the rehabilitation stay was associated with less functional recovery from admission to discharge, even after adjusting for other significant predictors of functional recovery (mental status, hours of rehabilitation therapy received, rehospitalization, and reason for admission; adjusted R2 = 0.267, P < 0.0001). More daytime sleeping during rehabilitation remained a significant predictor of less functional recovery in adjusted analyses at 3-month follow-up. Conclusions: Sleep disturbance is common among older people undergoing inpatient post-acute rehabilitation. These data suggest that more daytime sleeping during the rehabilitation stay is associated with less functional recovery for up to three months after admission for rehabilitation. Citation: Alessi CA; Martin JL; Webber AP; Alam T

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

    PubMed Central

    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

  17. Problems Associated with Grid Convergence of Functionals

    NASA Technical Reports Server (NTRS)

    Salas, Manuel D.; Atkins, Harld L.

    2008-01-01

    The current use of functionals to evaluate order-of-convergence of a numerical scheme can lead to incorrect values. The problem comes about because of interplay between the errors from the evaluation of the functional, e.g., quadrature error, and from the numerical scheme discretization. Alternative procedures for deducing the order-property of a scheme are presented. The problem is studied within the context of the inviscid supersonic flow over a blunt body; however, the problem and solutions presented are not unique to this example.

  18. Neural function, injury, and stroke subtype predict treatment gains after stroke.

    PubMed

    Burke Quinlan, Erin; Dodakian, Lucy; See, Jill; McKenzie, Alison; Le, Vu; Wojnowicz, Mike; Shahbaba, Babak; Cramer, Steven C

    2015-01-01

    This study was undertaken to better understand the high variability in response seen when treating human subjects with restorative therapies poststroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains; therefore, the current study hypothesized that a multivariate approach incorporating these 3 measures would have the greatest predictive value. Patients 3 to 6 months poststroke underwent a battery of assessments before receiving 3 weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment). Among all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract [CST] injury), cortical function (greater ipsilesional motor cortex [M1] activation), and cortical connectivity (greater interhemispheric M1-M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1-M1 connectivity (r(2) = 0.44, p = 0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype; gains in patients with lacunar stroke were best predicted by a measure of intrahemispheric connectivity. Response to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision making for poststroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting the utility of lesion-specific strategies. © 2014 American Neurological Association.

  19. Comparative analysis of grapevine whole-genome gene predictions, functional annotation, categorization and integration of the predicted gene sequences

    PubMed Central

    2012-01-01

    Background The first draft assembly and gene prediction of the grapevine genome (8X base coverage) was made available to the scientific community in 2007, and functional annotation was developed on this gene prediction. Since then additional Sanger sequences were added to the 8X sequences pool and a new version of the genomic sequence with superior base coverage (12X) was produced. Results In order to more efficiently annotate the function of the genes predicted in the new assembly, it is important to build on as much of the previous work as possible, by transferring 8X annotation of the genome to the 12X version. The 8X and 12X assemblies and gene predictions of the grapevine genome were compared to answer the question, “Can we uniquely map 8X predicted genes to 12X predicted genes?” The results show that while the assemblies and gene structure predictions are too different to make a complete mapping between them, most genes (18,725) showed a one-to-one relationship between 8X predicted genes and the last version of 12X predicted genes. In addition, reshuffled genomic sequence structures appeared. These highlight regions of the genome where the gene predictions need to be taken with caution. Based on the new grapevine gene functional annotation and in-depth functional categorization, twenty eight new molecular networks have been created for VitisNet while the existing networks were updated. Conclusions The outcomes of this study provide a functional annotation of the 12X genes, an update of VitisNet, the system of the grapevine molecular networks, and a new functional categorization of genes. Data are available at the VitisNet website (http://www.sdstate.edu/ps/research/vitis/pathways.cfm). PMID:22554261

  20. Impairment in Occupational Functioning and Adult ADHD: The Predictive Utility of Executive Function (EF) Ratings Versus EF Tests

    PubMed Central

    Barkley, Russell A.; Murphy, Kevin R.

    2010-01-01

    Attention deficit hyperactivity disorder (ADHD) is associated with deficits in executive functioning (EF). ADHD in adults is also associated with impairments in major life activities, particularly occupational functioning. We investigated the extent to which EF deficits assessed by both tests and self-ratings contributed to the degree of impairment in 11 measures involving self-reported occupational problems, employer reported workplace adjustment, and clinician rated occupational adjustment. Three groups of adults were recruited as a function of their severity of ADHD: ADHD diagnosis (n = 146), clinical controls self-referring for ADHD but not diagnosed with it (n = 97), and community controls (n = 109). Groups were combined and regression analyses revealed that self-ratings of EF were significantly predictive of impairments in all 11 measures of occupational adjustment. Although several tests of EF also did so, they contributed substantially less than did the EF ratings, particularly when analyzed jointly with the ratings. We conclude that EF deficits contribute to the impairments in occupational functioning that occur in conjunction with adult ADHD. Ratings of EF in daily life contribute more to such impairments than do EF tests, perhaps because, as we hypothesize, each assesses a different level in the hierarchical organization of EF as a meta-construct. PMID:20197297

  1. “Reverse Genomics” Predicts Function of Human Conserved Noncoding Elements

    PubMed Central

    Marcovitz, Amir; Jia, Robin; Bejerano, Gill

    2016-01-01

    Evolutionary changes in cis-regulatory elements are thought to play a key role in morphological and physiological diversity across animals. Many conserved noncoding elements (CNEs) function as cis-regulatory elements, controlling gene expression levels in different biological contexts. However, determining specific associations between CNEs and related phenotypes is a challenging task. Here, we present a computational “reverse genomics” approach that predicts the phenotypic functions of human CNEs. We identify thousands of human CNEs that were lost in at least two independent mammalian lineages (IL-CNEs), and match their evolutionary profiles against a diverse set of phenotypes recently annotated across multiple mammalian species. We identify 2,759 compelling associations between human CNEs and a diverse set of mammalian phenotypes. We discuss multiple CNEs, including a predicted ear element near BMP7, a pelvic CNE in FBN1, a brain morphology element in UBE4B, and an aquatic adaptation forelimb CNE near EGR2, and provide a full list of our predictions. As more genomes are sequenced and more traits are annotated across species, we expect our method to facilitate the interpretation of noncoding mutations in human disease and expedite the discovery of individual CNEs that play key roles in human evolution and development. PMID:26744417

  2. Preoperative Renal Function Predicts Hospital Costs and Length of Stay in Coronary Artery Bypass Grafting.

    PubMed

    LaPar, Damien J; Rich, Jeffrey B; Isbell, James M; Brooks, Charles H; Crosby, Ivan K; Yarboro, Leora T; Ghanta, Ravi K; Kern, John A; Brown, Michael; Quader, Mohammed A; Speir, Alan M; Ailawadi, Gorav

    2016-02-01

    Renal failure remains a major source of morbidity after cardiac surgery. Whereas the relationship between poor renal function and worse cardiac surgical outcomes is well established, the ability to predict the impact of preoperative renal insufficiency on hospital costs and health care resource utilization remains unknown. Patient records from a statewide The Society for Thoracic Surgeons (STS) database linked with estimated cost data were evaluated for isolated coronary artery bypass graft (CABG) operations (2000 to 2012). Patients with documented preoperative renal failure/dialysis were excluded. Preoperative renal function was determined using calculated creatinine clearance (CrCl). Multivariable regression analyses utilizing restricted cubic splines evaluated the continuous relationship between CrCl and risk-adjusted outcomes. A total of 46,577 isolated CABG operations were evaluated with a median STS predicted risk of mortality score of 1.2% (interquartile range, 0.7% to 2.4%), including 9% off-pump CABG. Median CrCl was 85 mL/min (range, 2 to 120 mL/min), and median total cost was $25,011. After adjustment for preoperative risk factors, worsening CrCl (declining renal function) was highly associated with greater total costs of hospitalization (coefficient = -122, p < 0.001) and postoperative length of stay (coefficient = -0.03, p < 0.001). Furthermore, predicted total costs were incrementally increased by 10%, 20%, and 30% with worsening of CrCl from 80 mL/min to 60, 40, and 20 mL/min. As expected, decreasing CrCl was also associated with an increased risk-adjusted likelihood for hemodialysis and mortality (both p < 0.001). Preoperative renal function is highly associated with the cost of CABG. Assessment of renal function may be used to preoperatively predict cost and resource utilization. Optimizing renal function preoperatively has the potential to improve patient quality and costs by approximately 6% ($1,250) for every 10 mL/min improvement in

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

    PubMed

    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.

  4. Evaluation of MELD score and Maddrey discriminant function for mortality prediction in patients with alcoholic hepatitis.

    PubMed

    Monsanto, Pedro; Almeida, Nuno; Lrias, Clotilde; Pina, Jos Eduardo; Sofia, Carlos

    2013-01-01

    Maddrey discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis (AH). However, MELD has also been used for this purpose. We aimed to determine the predictive parameters and compare the ability of Maddrey DF and MELD to predict short-term mortality in patients with AH. Retrospective study of 45 patients admitted in our department with AH between 2000 and 2010. Demographic, clinical and laboratory parameters were collected. MELD and Maddrey DF were calculated on admission. Short-term mortality was assessed at 30 and 90 days. Student t-test, χ2 test, univariate analysis, logistic regression and receiver operating characteristic curves were performed. Thirty-day and 90-day mortality was 27% and 42%, respectively. In multivariate analysis, Maddrey DF was the only independent predictor of mortality for these two periods. Receiver operating characteristic curves for Maddrey DF revealed an excellent discriminatory ability to predict 30-day and 90-day mortality for a Maddrey DF greater than 65 and 60, respectively. Discriminatory ability to predict 30-day and 90-day mortality for MELD was low. AH remains associated with a high short-term mortality. Maddrey DF is a more valuable model than MELD to predict short-term mortality in patients with AH.

  5. Structure activity relationships: their function in biological prediction

    SciTech Connect

    Schultz, T.W.

    1982-01-01

    Quantitative structure activity relationships provide a means of ranking or predicting biological effects based on chemical structure. For each compound used to formulate a structure activity model two kinds of quantitative information are required: (1) biological activity and (2) molecular properties. Molecular properties are of three types: (1) molecular shape, (2) physiochemical parameters, and (3) abstract quantitations of molecular structure. Currently the two best descriptors are the hydrophobic parameter, log 1-octanol/water partition coefficient (log P), and the /sup 1/X/sup v/(one-chi-v) molecular connectivity index. Biological responses can be divided into three main categories: (1) non-specific effects due to membrane perturbation, (2) non-specific effects due to interaction with functional groups of proteins, and (3) specific effects due to interaction with receptors. Twenty-six synthetic fossil fuel-related nitrogen-containing aromatic compounds were examined to determine the quantitative correlation between log P and /sup 1/X/sup v/ and population growth impairment of Tetrahymena pyriformis. Nitro-containing compounds are the most active, followed by amino-containing compounds and azaarenes. Within each analog series activity increases with alkyl substitution and ring addition. The planar model log BR = 0.5564 log P + 0.3000 /sup 1/X/sup v/ -2.0138 was determined using mono-nitrogen substituted compounds. Attempts to extrapolate this model to dinitrogen-containing molecules were, for the most part, unsuccessful because of a change in mode of action from membrane perturbation to uncoupling of oxidative phosphoralation.

  6. Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

    PubMed

    Xu, Yonghui; Min, Huaqing; Wu, Qingyao; Song, Hengjie; Ye, Bicui

    2017-02-06

    Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function prediction under a usual assumption, the underlying distribution from testing data (target domain, i.e., TD) is the same as that from training data (source domain, i.e., SD). However, this assumption may be violated in real practice. To tackle this problem, in this paper, we propose a Multi-Instance Metric Transfer Learning (MIMTL) approach for genome-wide protein function prediction. In MIMTL, we first transfer the source domain distribution to the target domain distribution by utilizing the bag weights. Then, we construct a distance metric learning method with the reweighted bags. At last, we develop an alternative optimization scheme for MIMTL. Comprehensive experimental evidence on seven real-world organisms verifies the effectiveness and efficiency of the proposed MIMTL approach over several state-of-the-art methods.

  7. Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.

    PubMed

    Shihab, Hashem A; Gough, Julian; Cooper, David N; Stenson, Peter D; Barker, Gary L A; Edwards, Keith J; Day, Ian N M; Gaunt, Tom R

    2013-01-01

    The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole-genome/whole-exome sequencing technologies. Automated methods capable of accurately and reliably distinguishing between pathogenic and functionally neutral nsSNPs are therefore assuming ever-increasing importance. Here, we describe the Functional Analysis Through Hidden Markov Models (FATHMM) software and server: a species-independent method with optional species-specific weightings for the prediction of the functional effects of protein missense variants. Using a model weighted for human mutations, we obtained performance accuracies that outperformed traditional prediction methods (i.e., SIFT, PolyPhen, and PANTHER) on two separate benchmarks. Furthermore, in one benchmark, we achieve performance accuracies that outperform current state-of-the-art prediction methods (i.e., SNPs&GO and MutPred). We demonstrate that FATHMM can be efficiently applied to high-throughput/large-scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations. To illustrate this, we evaluated nsSNPs in wheat (Triticum spp.) to identify some of the important genetic variants responsible for the phenotypic differences introduced by intense selection during domestication. A Web-based implementation of FATHMM, including a high-throughput batch facility and a downloadable standalone package, is available at http://fathmm.biocompute.org.uk.

  8. Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction

    PubMed Central

    Xu, Yonghui; Min, Huaqing; Wu, Qingyao; Song, Hengjie; Ye, Bicui

    2017-01-01

    Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function prediction under a usual assumption, the underlying distribution from testing data (target domain, i.e., TD) is the same as that from training data (source domain, i.e., SD). However, this assumption may be violated in real practice. To tackle this problem, in this paper, we propose a Multi-Instance Metric Transfer Learning (MIMTL) approach for genome-wide protein function prediction. In MIMTL, we first transfer the source domain distribution to the target domain distribution by utilizing the bag weights. Then, we construct a distance metric learning method with the reweighted bags. At last, we develop an alternative optimization scheme for MIMTL. Comprehensive experimental evidence on seven real-world organisms verifies the effectiveness and efficiency of the proposed MIMTL approach over several state-of-the-art methods. PMID:28165495

  9. Executive function and theory of mind: Predictive relations from ages 2 to 4.

    PubMed

    Hughes, Claire; Ensor, Rosie

    2007-11-01

    Despite robust associations between children's theory of mind (ToM) and executive function (EF) skills, longitudinal studies examining this association remain scarce. In a socially diverse sample of 122 children (seen at ages 2, 3, and 4), this study examined (a) developmental stability of associations between ToM, EF, verbal ability, and social disadvantage; (b) continuity and change in ToM and EF; and (c) predictive relations between ToM and EF. Verbal ability and social disadvantage independently predicted changes in EF (but not ToM). Task scores improved with age and showed stable individual differences. The authors examined predictive relations between ToM and EF using partial correlations (controlling for age and verbal ability) and hierarchical regressions (that also controlled for social disadvantage and initial ToM and EF). The findings provide only partial support for the view that ToM is a prerequisite for EF but stronger support for the proposal that EF facilitates children's performance on ToM tasks. (c) 2007 APA.

  10. Predicting invasive species impacts: a community module functional response approach reveals context dependencies.

    PubMed

    Paterson, Rachel A; Dick, Jaimie T A; Pritchard, Daniel W; Ennis, Marilyn; Hatcher, Melanie J; Dunn, Alison M

    2015-03-01

    Predatory functional responses play integral roles in predator-prey dynamics, and their assessment promises greater understanding and prediction of the predatory impacts of invasive species. Other interspecific interactions, however, such as parasitism and higher-order predation, have the potential to modify predator-prey interactions and thus the predictive capability of the comparative functional response approach. We used a four-species community module (higher-order predator; focal native or invasive predators; parasites of focal predators; native prey) to compare the predatory functional responses of native Gammarus duebeni celticus and invasive Gammarus pulex amphipods towards three invertebrate prey species (Asellus aquaticus, Simulium spp., Baetis rhodani), thus, quantifying the context dependencies of parasitism and a higher-order fish predator on these functional responses. Our functional response experiments demonstrated that the invasive amphipod had a higher predatory impact (lower handling time) on two of three prey species, which reflects patterns of impact observed in the field. The community module also revealed that parasitism had context-dependent influences, for one prey species, with the potential to further reduce the predatory impact of the invasive amphipod or increase the predatory impact of the native amphipod in the presence of a higher-order fish predator. Partial consumption of prey was similar for both predators and occurred increasingly in the order A. aquaticus, Simulium spp. and B. rhodani. This was associated with increasing prey densities, but showed no context dependencies with parasitism or higher-order fish predator. This study supports the applicability of comparative functional responses as a tool to predict and assess invasive species impacts incorporating multiple context dependencies.

  11. Predicting invasive species impacts: a community module functional response approach reveals context dependencies

    PubMed Central

    Paterson, Rachel A; Dick, Jaimie T A; Pritchard, Daniel W; Ennis, Marilyn; Hatcher, Melanie J; Dunn, Alison M

    2015-01-01

    Summary Predatory functional responses play integral roles in predator–prey dynamics, and their assessment promises greater understanding and prediction of the predatory impacts of invasive species. Other interspecific interactions, however, such as parasitism and higher-order predation, have the potential to modify predator–prey interactions and thus the predictive capability of the comparative functional response approach. We used a four-species community module (higher-order predator; focal native or invasive predators; parasites of focal predators; native prey) to compare the predatory functional responses of native Gammarus duebeni celticus and invasive Gammarus pulex amphipods towards three invertebrate prey species (Asellus aquaticus, Simulium spp., Baetis rhodani), thus, quantifying the context dependencies of parasitism and a higher-order fish predator on these functional responses. Our functional response experiments demonstrated that the invasive amphipod had a higher predatory impact (lower handling time) on two of three prey species, which reflects patterns of impact observed in the field. The community module also revealed that parasitism had context-dependent influences, for one prey species, with the potential to further reduce the predatory impact of the invasive amphipod or increase the predatory impact of the native amphipod in the presence of a higher-order fish predator. Partial consumption of prey was similar for both predators and occurred increasingly in the order A. aquaticus, Simulium spp. and B. rhodani. This was associated with increasing prey densities, but showed no context dependencies with parasitism or higher-order fish predator. This study supports the applicability of comparative functional responses as a tool to predict and assess invasive species impacts incorporating multiple context dependencies. PMID:25265905

  12. Elevated heart rate predicts β cell function in non-diabetic individuals: the RISC cohort.

    PubMed

    Bonnet, Fabrice; Empana, Jean-Philippe; Natali, Andrea; Monti, Lucilla; Golay, Alain; Lalic, Katarina; Dekker, Jacqueline; Mari, Andrea; Balkau, Beverley

    2015-09-01

    Elevated heart rate has been associated with insulin resistance and incident type 2 diabetes but its relationship with β-cell function is not known. Our aim was to investigate whether baseline heart rate is associated with β-cell function and hyperglycaemia. We used the prospective RISC cohort with 1005 non-diabetic individuals who had an oral glucose tolerance test (OGTT) at baseline and after 3 years. Impaired glucose regulation was defined as a fasting plasma glucose ≥ 6.1 mmol/l or a 2-h plasma glucose ≥ 7.8 mmol/l. Insulin sensitivity was assessed by the OGIS index and insulin secretion and β-cell glucose sensitivity at both baseline and 3 years. Baseline heart rate was positively related to both fasting (P < 0.0001) and 2 h glucose levels (P = 0.02) at year 3 and predicted the presence of impaired glucose regulation at year 3 in a logistic regression model adjusting for insulin sensitivity at inclusion (OR/10 beats per min: 1.31; 95% CI (1.07-1.61); P = 0.01). Baseline heart rate was associated with lower insulin sensitivity (β = -0.11; P < .0001), a decrease in both β-cell glucose sensitivity (β = -0.11; P = 0.003) and basal insulin secretion rate (β = -0.11; P = 0.002) at 3 years in an adjusted multivariable regression model. Baseline heart rate predicted the 3-year decrease in β-cell glucose sensitivity (β = -0.10; P = 0.007) and basal insulin secretion (β = -0.12; P = 0.007). Heart rate predicts β-cell function and impaired glucose regulation at 3 years in non-diabetic individuals, independently of the level of insulin sensitivity. These findings suggest a possible effect of the sympathetic nervous system on β-cell dysfunction, which deserves further investigation. © 2015 European Society of Endocrinology.

  13. Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

    PubMed

    Khambhati, Ankit N; Bassett, Danielle S; Oommen, Brian S; Chen, Stephanie H; Lucas, Timothy H; Davis, Kathryn A; Litt, Brian

    2017-01-01

    Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 h of intracranial recordings in each of 22 neocortical epilepsy patients. Using this approach, we found: (1) subgraphs from ictal (seizure) and interictal (baseline) epochs are topologically similar, (2) interictal subgraph topology and dynamics can predict brain regions that generate seizures, and (3) subgraphs undergo slower and more coordinated fluctuations during ictal epochs compared to interictal epochs. Our observations suggest that seizures mark a critical shift away from interictal states that is driven by changes in the dynamical expression of strongly interacting components of the epileptic network.

  14. Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy

    PubMed Central

    Bassett, Danielle S.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.

    2017-01-01

    Abstract Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 h of intracranial recordings in each of 22 neocortical epilepsy patients. Using this approach, we found: (1) subgraphs from ictal (seizure) and interictal (baseline) epochs are topologically similar, (2) interictal subgraph topology and dynamics can predict brain regions that generate seizures, and (3) subgraphs undergo slower and more coordinated fluctuations during ictal epochs compared to interictal epochs. Our observations suggest that seizures mark a critical shift away from interictal states that is driven by changes in the dynamical expression of strongly interacting components of the epileptic network. PMID:28303256

  15. Amphibian gut microbiota shifts differentially in community structure but converges on habitat-specific predicted functions

    PubMed Central

    Bletz, Molly C.; Goedbloed, Daniel J.; Sanchez, Eugenia; Reinhardt, Timm; Tebbe, Christoph C.; Bhuju, Sabin; Geffers, Robert; Jarek, Michael; Vences, Miguel; Steinfartz, Sebastian

    2016-01-01

    Complex microbial communities inhabit vertebrate digestive systems but thorough understanding of the ecological dynamics and functions of host-associated microbiota within natural habitats is limited. We investigate the role of environmental conditions in shaping gut and skin microbiota under natural conditions by performing a field survey and reciprocal transfer experiments with salamander larvae inhabiting two distinct habitats (ponds and streams). We show that gut and skin microbiota are habitat-specific, demonstrating environmental factors mediate community structure. Reciprocal transfer reveals that gut microbiota, but not skin microbiota, responds differentially to environmental change. Stream-to-pond larvae shift their gut microbiota to that of pond-to-pond larvae, whereas pond-to-stream larvae change to a community structure distinct from both habitat controls. Predicted functions, however, match that of larvae from the destination habitats in both cases. Thus, microbial function can be matched without taxonomic coherence and gut microbiota appears to exhibit metagenomic plasticity. PMID:27976718

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

    PubMed

    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.

  17. Prediction Error Associated with the Perceptual Segmentation of Naturalistic Events

    ERIC Educational Resources Information Center

    Zacks, Jeffrey M.; Kurby, Christopher A.; Eisenberg, Michelle L.; Haroutunian, Nayiri

    2011-01-01

    Predicting the near future is important for survival and plays a central role in theories of perception, language processing, and learning. Prediction failures may be particularly important for initiating the updating of perceptual and memory systems and, thus, for the subjective experience of events. Here, we asked observers to make predictions…

  18. Prediction Error Associated with the Perceptual Segmentation of Naturalistic Events

    ERIC Educational Resources Information Center

    Zacks, Jeffrey M.; Kurby, Christopher A.; Eisenberg, Michelle L.; Haroutunian, Nayiri

    2011-01-01

    Predicting the near future is important for survival and plays a central role in theories of perception, language processing, and learning. Prediction failures may be particularly important for initiating the updating of perceptual and memory systems and, thus, for the subjective experience of events. Here, we asked observers to make predictions…

  19. Genome wide prediction of protein function via a generic knowledge discovery approach based on evidence integration

    PubMed Central

    Xiong, Jianghui; Rayner, Simon; Luo, Kunyi; Li, Yinghui; Chen, Shanguang

    2006-01-01

    Background The automation of many common molecular biology techniques has resulted in the accumulation of vast quantities of experimental data. One of the major challenges now facing researchers is how to process this data to yield useful information about a biological system (e.g. knowledge of genes and their products, and the biological roles of proteins, their molecular functions, localizations and interaction networks). We present a technique called Global Mapping of Unknown Proteins (GMUP) which uses the Gene Ontology Index to relate diverse sources of experimental data by creation of an abstraction layer of evidence data. This abstraction layer is used as input to a neural network which, once trained, can be used to predict function from the evidence data of unannotated proteins. The method allows us to include almost any experimental data set related to protein function, which incorporates the Gene Ontology, to our evidence data in order to seek relationships between the different sets. Results We have demonstrated the capabilities of this method in two ways. We first collected various experimental datasets associated with yeast (Saccharomyces cerevisiae) and applied the technique to a set of previously annotated open reading frames (ORFs). These ORFs were divided into training and test sets and were used to examine the accuracy of the predictions made by our method. Then we applied GMUP to previously un-annotated ORFs and made 1980, 836 and 1969 predictions corresponding to the GO Biological Process, Molecular Function and Cellular Component sub-categories respectively. We found that GMUP was particularly successful at predicting ORFs with functions associated with the ribonucleoprotein complex, protein metabolism and transportation. Conclusion This study presents a global and generic gene knowledge discovery approach based on evidence integration of various genome-scale data. It can be used to provide insight as to how certain biological processes are

  20. Earing Prediction in Cup Drawing Based on Non-Associated Flow Rule

    SciTech Connect

    Yoon, J. W.; Dick, R. E.; Stoughton, T. B.

    2007-05-17

    An anisotropic constitutive model based on Non-Associated Flow Rule (Non-AFR), which incorporates plane stress yield functions (Hill's quadratic function and Yld2000-2d by Barlat et al.), was implemented to finite element codes (ABAQUS, LS-DYNA 3D) by using User Material options. By using Non-AFR, Yld2000-2d is capable of predicting more than four ears which is possible only with Yld2004 by Barlat et al. when used with an Associated Flow Rule. A short review of the Non-Associated Flow Rule was provided. Simulation of the cup drawing process for a rigid container sheet alloy using mini-die geometry was performed to show the cup height profile (earing profile) obtained from Non-AFR. The simulation results were compared with experimental earing profile data and it was shown that the simulations using Yld2000-2d and the Non-AFR led to the excellent prediction of the earing profile.

  1. Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

    PubMed Central

    van Zanten, Martijn

    2015-01-01

    Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492

  2. Early Functional Limitations in Cognitively Normal Older Adults Predict Diagnostic Conversion to Mild Cognitive Impairment.

    PubMed

    Farias, Sarah Tomaszewski; Lau, Karen; Harvey, Danielle; Denny, Katherine G; Barba, Cheyanne; Mefford, Anthony N

    2017-06-01

    To examine whether specific types of early functional limitations in cognitively normal older adults are associated with subsequent development of mild cognitive impairment (MCI), as well as the relative predictive value of self versus informant report in predicting diagnostic conversion to MCI. As a part of a longitudinal study design, participants underwent baseline and annual multidisciplinary clinical evaluations, including a physical and neurological examination, imaging, laboratory work, and neuropsychological testing. Data used in this study were collected as part of longitudinal research at the University of California, Davis Alzheimer's Disease Center. Individuals diagnosed as having normal cognition at study baseline who had an informant who could complete informant-based ratings and at least one follow-up visit (N = 324). Participants and informants each completed the Everyday Cognition Scale (ECog), an instrument designed to measure everyday function in six cognitively relevant domains. Self- and informant-reported functional limitations on the ECog were associated with significantly greater risk of diagnostic conversion to MCI (informant: hazard ratio (HR) = 2.0, 95% confidence interval (CI) = 1.3-3.2, P = .002), with self-report having a slightly higher hazard (HR = 2.3, 95% CI = 1.4-3.6, P < .001). When controlling for baseline cognitive abilities, the effect remained significant for self- and informant-reported functional limitations. Deficits in everyday memory and executive function domains were the strongest predictors of diagnostic conversion to MCI. Detection of early functional limitations may be clinically useful in assessing the future risk of developing cognitive impairment in cognitively normal older adults. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

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

    PubMed

    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.

  4. Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction.

    PubMed

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

    2017-01-01

    Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this "guilt-by-association" (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. © 2017 by

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

    PubMed Central

    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

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

    PubMed

    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.

  7. Individual differences in common factors of emotional traits and executive functions predict functional connectivity of the amygdala.

    PubMed

    Rohr, C S; Dreyer, F R; Aderka, I M; Margulies, D S; Frisch, S; Villringer, A; Okon-Singer, H

    2015-10-15

    Evidence suggests that individual differences in emotion control are associated with frontoparietal-limbic networks and linked to emotional traits and executive functions. In a first attempt to directly target the link between emotional traits and executive functions using resting-state fMRI analysis, 43 healthy adults completed a test battery including executive tasks and emotional trait self-assessments that were subjected to a principal component analysis. Of the three factors detected, two explained 40.4% of the variance and were further investigated. Both factors suggest a relation between emotional traits and executive functions. Specifically, the first factor consisted of measures related to inhibitory control and negative affect, and the second factor was related to reward and positive affect. To investigate whether this interplay between emotional traits and executive functions is reflected in neural connectivity, we used resting-state fMRI to explore the functional connectivity of the amygdala as a starting point, and progressed to other seed-based analyses based on the initial findings. We found that the first factor predicted the strength of connectivity between brain regions known to be involved in the cognitive control of emotion, including the amygdala and the dorsolateral prefrontal cortex, whereas the second factor predicted the strength of connectivity between brain regions known to be involved in reward and attention, including the amygdala, the caudate and the thalamus. These findings suggest that individual differences in the ability to inhibit negative affect are mediated by prefrontal-limbic pathways, while the ability to be positive and use rewarding information is mediated by a network that includes the amygdala and thalamostriatal regions.

  8. Prediction of deleterious functional effects of amino acid mutations using a library of structure-based function descriptors.

    PubMed

    Herrgard, Sanna; Cammer, Stephen A; Hoffman, Brian T; Knutson, Stacy; Gallina, Marijo; Speir, Jeffrey A; Fetrow, Jacquelyn S; Baxter, Susan M

    2003-12-01

    An automated, active site-focused, computational method is described for use in predicting the effects of engineered amino acid mutations on enzyme catalytic activity. The method uses structure-based function descriptors (Fuzzy Functional Forms trade mark or FFFs trade mark ) to automatically identify enzyme functional sites in proteins. Three-dimensional sequence profiles are created from the surrounding active site structure. The computationally derived active site profile is used to analyze the effect of each amino acid change by defining three key features: proximity of the change to the active site, degree of amino acid conservation at the position in related proteins, and compatibility of the change with residues observed at that position in similar proteins. The features were analyzed using a data set of individual amino acid mutations occurring at 128 residue positions in 14 different enzymes. The results show that changes at key active site residues and at highly conserved positions are likely to have deleterious effects on the catalytic activity, and that non-conservative mutations at highly conserved residues are even more likely to be deleterious. Interestingly, the study revealed that amino acid substitutions at residues in close contact with the key active site residues are not more likely to have deleterious effects than mutations more distant from the active site. Utilization of the FFF-derived structural information yields a prediction method that is accurate in 79-83% of the test cases. The success of this method across all six EC classes suggests that it can be used generally to predict the effects of mutations and nsSNPs for enzymes. Future applications of the approach include automated, large-scale identification of deleterious nsSNPs in clinical populations and in large sets of disease-associated nsSNPs, and identification of deleterious nsSNPs in drug targets and drug metabolizing enzymes. Copyright 2003 Wiley-Liss, Inc.

  9. A density functional theory for colloids with two multiple bonding associating sites.

    PubMed

    Haghmoradi, Amin; Wang, Le; Chapman, Walter G

    2016-06-22

    Wertheim's multi-density formalism is extended for patchy colloidal fluids with two multiple bonding patches. The theory is developed as a density functional theory to predict the properties of an associating inhomogeneous fluid. The equation of state developed for this fluid depends on the size of the patch, and includes formation of cyclic, branched and linear clusters of associated species. The theory predicts the density profile and the fractions of colloids in different bonding states versus the distance from one wall as a function of bulk density and temperature. The predictions from our theory are compared with previous results for a confined fluid with four single bonding association sites. Also, comparison between the present theory and Monte Carlo simulation indicates a good agreement.

  10. Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits.

    PubMed

    Wolpe, Noham; Ingram, James N; Tsvetanov, Kamen A; Geerligs, Linda; Kievit, Rogier A; Henson, Richard N; Wolpert, Daniel M; Rowe, James B

    2016-10-03

    The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation-a reduction in the perceived intensity of sensations from self-generated compared with external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18-88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age.

  11. Systemic vascular function is associated with muscular power in adults

    USDA-ARS?s Scientific Manuscript database

    Age-associated loss of muscular strength and muscular power are critical determinants of loss of physical function and progression to disability in older adults. In this study, we examined the association of systemic vascular function and measures of muscle strength and power in older adults. Measu...

  12. A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae).

    PubMed

    Troyanskaya, Olga G; Dolinski, Kara; Owen, Art B; Altman, Russ B; Botstein, David

    2003-07-08

    Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic methods such as affinity precipitation to advanced high-throughput techniques such as gene expression microarrays. In the future, more disparate methods will be developed, further increasing the need for integrated computational analysis of data generated by these studies. We address this problem with MAGIC (Multisource Association of Genes by Integration of Clusters), a general framework that uses formal Bayesian reasoning to integrate heterogeneous types of high-throughput biological data (such as large-scale two-hybrid screens and multiple microarray analyses) for accurate gene function prediction. The system formally incorporates expert knowledge about relative accuracies of data sources to combine them within a normative framework. MAGIC provides a belief level with its output that allows the user to vary the stringency of predictions. We applied MAGIC to Saccharomyces cerevisiae genetic and physical interactions, microarray, and transcription factor binding sites data and assessed the biological relevance of gene groupings using Gene Ontology annotations produced by the Saccharomyces Genome Database. We found that by creating functional groupings based on heterogeneous data types, MAGIC improved accuracy of the groupings compared with microarray analysis alone. We describe several of the biological gene groupings identified.

  13. Processing speed and neurodevelopment in adolescent-onset psychosis: cognitive slowing predicts social function.

    PubMed

    Bachman, Peter; Niendam, Tara A; Jalbrzikowski, Maria; Jalbrzikowkski, Maria; Park, Chan Y; Daley, Melita; Cannon, Tyrone D; Bearden, Carrie E

    2012-05-01

    Onset of psychosis may be associated with abnormal adolescent neurodevelopment. Here we examined the neurocognitive profile of first-episode, adolescent onset psychosis (AOP) as compared to typically developing adolescents, and asked whether neurocognitive performance varied differentially as a function of age in the cases compared with controls. A comprehensive neuropsychological battery was administered to 35 patients experiencing a first-episode of a DSM-IV psychotic disorder and to 31 matched controls. Clinicians also rated subjects' social and role functioning, both at the time of neuropsychological assessment and 1 year later. Although patients displayed a wide range of impairments relative to controls, their most pronounced deficits included verbal memory, sensorimotor dexterity and cognitive processing speed. Among these, only processing speed showed a significant group-by-age interaction, consistent with an aberrant developmental course among AOP patients. Processing speed also accounted for substantial variance in other areas of deficit, and predicted social functioning 1 year later. AOP patients fail to show normal age-related increases in processing speed, which in turn predicts poorer functional outcomes. This pattern is consistent with the view that adolescent brain developmental processes, such as myelination, may be disrupted in these patients.

  14. Prediction of Chemical Function: Model Development and Application

    EPA Science Inventory

    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 (...

  15. firestar—advances in the prediction of functionally important residues

    PubMed Central

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L.

    2011-01-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php. PMID:21672959

  16. firestar--advances in the prediction of functionally important residues.

    PubMed

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php.

  17. Prediction of Chemical Function: Model Development and Application

    EPA Science Inventory

    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 (...

  18. Modularity in the gain and loss of genes: applications for function prediction.

    PubMed

    Ettema, T; van der Oost, J; Huynen, M

    2001-09-01

    Genes that are clustered on multiple genomes and are likely to functionally interact tend to be gained or lost together during genome evolution. Here, we demonstrate that exceptions to this pattern indicate relatively distant functional interactions between the encoded proteins. Hence, this can be used to divide predicted clusters of functionally interacting proteins into sub-clusters, and as such, to refine the prediction of their function and functional interactions.

  19. Ideal cardiovascular health predicts functional status independently of vascular events: the Northern Manhattan Study.

    PubMed

    Dhamoon, Mandip S; Dong, Chuanhui; Elkind, Mitchell S V; Sacco, Ralph L

    2015-02-12

    We hypothesized that the American Heart Association's metric of ideal cardiovascular health (CVH) predicts improved long-term functional status after adjusting for incident stroke and myocardial infarction. In the prospective, multiethnic Northern Manhattan Study, stroke-free individuals in northern Manhattan aged ≥40 years had annual assessments of the primary outcome of functional status with the Barthel index (BI), for a median of 13 years. Ideal CVH was calculated as a composite of 7 measures, each scored on a scale of 0 to 2. Primary predictors were (1) number of ideal CVH metrics, and (2) total score of all CVH metrics. Of 3219 participants, mean age was 69 years (SD 10), 63% were female, 21% were white, 25% were non-Hispanic black, and 54% were Hispanic. Twenty percent had 0 to 1 ideal CVH metrics, 32% had 2, 30% had 3, 14% had 4, and 4% had 5 to 7. Both number of ideal CVH categories and higher CVH metric scores were associated with higher mean BI scores at 5 and 10 years. 0047 Gradients persisted when results were adjusted for incident stroke and myocardial infarction, when mobility and nonmobility domains of the BI were analyzed separately, and when BI was analyzed dichotomously. At 10 years, in a fully adjusted model, differences in mean BI score were lower for poor versus ideal physical activity (3.48 points, P<0.0001) and fasting glucose (4.58 points, P<0.0001). Ideal CVH predicts functional status, even after accounting for incident vascular events. Vascular functional impairment is an important outcome that can be reduced by optimizing vascular health. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

  20. Supervised learning method for predicting chromatin boundary associated insulator elements.

    PubMed

    Bednarz, Paweł; Wilczyński, Bartek

    2014-12-01

    In eukaryotic cells, the DNA material is densely packed inside the nucleus in the form of a DNA-protein complex structure called chromatin. Since the actual conformation of the chromatin fiber defines the possible regulatory interactions between genes and their regulatory elements, it is very important to understand the mechanisms governing folding of chromatin. In this paper, we show that supervised methods for predicting chromatin boundary elements are much more effective than the currently popular unsupervised methods. Using boundary locations from published Hi-C experiments and modEncode tracks as features, we can tell the insulator elements from randomly selected background sequences with great accuracy. In addition to accurate predictions of the training boundary elements, our classifiers make new predictions. Many of them correspond to the locations of known insulator elements. The key features used for predicting boundary elements do not depend on the prediction method. Because of its miniscule size, chromatin state cannot be measured directly, we need to rely on indirect measurements, such as ChIP-Seq and fill in the gaps with computational models. Our results show that currently, at least in the model organisms, where we have many measurements including ChIP-Seq and Hi-C, we can make accurate predictions of insulator positions.

  1. Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes.

    PubMed

    Rohde, Palle Duun; Demontis, Ditte; Cuyabano, Beatriz Castro Dias; Børglum, Anders D; Sørensen, Peter

    2016-08-01

    Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case-control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies. Copyright © 2016 by the Genetics Society of America.

  2. Activity in the hippocampus and neocortical working memory regions predicts successful associative memory for temporally-discontiguous events

    PubMed Central

    Hales, J. B.; Brewer, J. B.

    2010-01-01

    Models of mnemonic function suggest that the hippocampus binds temporally-discontiguous events in memory (Wallenstein, G.V., Eichenbaum, H., & Hasselmo, M.E., (1998). The hippocampus as an associator of discontiguous events. Trends Neurosci, 21 (8), 317–323), which has been supported by recent studies in humans. Less is known, however, about the involvement of working memory in bridging the temporal gap between to-be-associated events. In this study, subsequent memory for associations between temporally-discontiguous stimuli was examined using functional magnetic resonance imaging. In the scanner, subjects were instructed to remember sequentially-presented images. Occasionally, a plus-sign was presented during the interstimulus-interval between two images, instructing subjects to associate the two images as a pair. Following the scan, subjects identified remembered images and their pairs. Images following the plus-sign were separated into trials in which items were later recognized and the pair remembered, recognized and the pair forgotten, or not recognized. Blood-oxygen-level-dependent responses were measured to identify regions where response amplitude predicted subsequent associative- or item-memory. Distinct neocortical regions were involved in each memory condition, where activity in bilateral frontal and parietal regions predicted memory for associative-information and bilateral occipital and medial frontal regions for item-information. While activity in posterior regions of the medial temporal lobe showed an intermediate response predicting memory for both conditions, bilateral hippocampal activity only predicted associative memory. PMID:20667491

  3. Influencing factors on color and product-function association.

    PubMed

    Ko, Ya-Hsien

    2011-06-01

    The associations of age, sex, and matching types with color and product-function were examined in a real-world product scenario (shampoo) among 128 volunteers (M age = 29.3 yr.; SD = 15.6). A pilot study identified eight popular colors and eight product-functions. The association between color and product-function was explored in the main sample. Responses suggested seven pairings of color/product-functions: Red/Hot oil treatment, Yellow/Bright and shiny hair, Green/Herbal extracts, Blue/Deep cleaning, Purple/Soothing, Black/Antiseptic, and White/Anti-dandruff. Analyses indicated that adult participants required more repetitions for retention, as did memorization with random pairing compared to participant-selected pairings. There were statistically significant correlations of responses to colors and product functions. With known color/product-function associations, manufacturers might promote their products more effectively. It is suggested that the associations might be sex- or culture-specific.

  4. Associative and predictive biomarkers of dementia in HIV-1–infected patients

    PubMed Central

    Bandaru, V.V.R.; McArthur, J.C.; Sacktor, N.; Cutler, R.G.; Knapp, E.L.; Mattson, M.P.; Haughey, N.J.

    2015-01-01

    Background Infection with HIV can result in a debilitating CNS disorder known as HIV dementia (HIV-D). Since the advent of highly active antiretroviral therapy (HAART), the incidence of HIV-D has declined, but the prevalence continues to increase. In this new era of HIV-D, traditional biomarkers such as CSF viral load and monocyte chemotactic protein 1 levels are less likely to be associated with dementia in patients on HAART and biomarkers that can predict HIV-D have not yet been identified. Objective To identify biomarkers that are associated with and can predict HIV-D. Methods We grouped patients with HIV based on changes in cognitive status over a 1-year period and analyzed sphingolipid, sterol, triglyceride, antioxidant, and lipid peroxidation levels in CSF. Results We found that increased levels of the vitamin E and triglyceride C52 predicted the onset or worsening of dementia. Elevated levels of sphingomyelin were associated with inactive dementia. Elevated levels of ceramide and the accumulation of 4-hydroxynonenals were associated with active dementia. Conclusions We interpret these findings to indicate that early in the pathogenesis of HIV dementia, there is an up-regulation of endogenous antioxidant defenses in brain. The failure of this attempted neuroprotective mechanism leads to the accumulation of sphingomyelin and moderate cognitive dysfunction. The breakdown of this enlarged pool of sphingomyelin to ceramide and the accumulation of highly reactive aldehydes are associated with declining cognitive function. Thus, elevations in endogenous protective mechanisms may identify patients who are at increased risk of the development of HIV dementia. PMID:17470750

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

    PubMed

    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.

  6. Prediction of poor graft function by means of gastric tonometry in patients undergoing liver transplantation.

    PubMed

    Perilli, Valter; Aceto, Paola; Modesti, Cristina; Vitale, Francesca; Ciocchetti, Pierpaolo; Sacco, Teresa; Adduci, Alessia; Lai, Carlo; Avolio, Alfonso W; Sollazzi, Liliana

    INTRODUCTION. Splanchnic hypoperfusion appears to play a key role in the failure of functional recovery of the graft after orthotopic liver transplantation (LT). The aim of this study was to determine if alterations of tonometric parameters, which are related to splanchnic perfusion, could predict poor graft function in patients undergoing LT. After Ethics Committee approval, 68 patients undergoing LT were enrolled. In all the patients, regional-arterial CO2 gradient (Pr-aCO2) was recorded; in addition, the difference between Pr-aCO2 recorded at anhepatic phase (T1) and at the end of surgery (T2) (T2- T1 = ΔPr-aCO2) was calculated. Poor graft function was determined on the basis of Toronto's classification 72 hours after LT. Student t-test and logistic regression analysis were used for statistical purpose. Results. ΔPr-aCO2 was significantly greater in patients with poor graft function (3.5 ± 13.2) compared to patients with good graft function (-5.8 ± 12.3) (p = 0.014). The logistic regression analysis showed that the ΔPr-aCO2 was able to predict the onset of poor graft function (p = 0.037). A value of ΔPr-aCO2 ≥ -4 was associated with poor graft function with a sensibility of 93.3% and a specificity of 42.3%. CONCLUSION. Our study suggests that the change of Pr-aCO2 may be a valuable index of graft dysfunction. Gastric tonometry might give early prognostic information on the graft outcome, and it may aid clinicians in planning a more strict follow-up and proper interventions in order to improve graft survival.

  7. The Functional Integration in the Sensory-Motor System Predicts Aging in Healthy Older Adults.

    PubMed

    He, Hui; Luo, Cheng; Chang, Xin; Shan, Yan; Cao, Weifang; Gong, Jinnan; Klugah-Brown, Benjamin; Bobes, Maria A; Biswal, Bharat; Yao, Dezhong

    2016-01-01

    Healthy aging is typically accompanied by a decrease in the motor capacity. Although the disrupted neural representations and performance of movement have been observed in older age in previous studies, the relationship between the functional integration of sensory-motor (SM) system and aging could be further investigated. In this study, we examine the impact of healthy aging on the resting-state functional connectivity (rsFC) of the SM system, and investigate as to how aging is affecting the rsFC in SM network. The SM network was identified and evaluated in 52 healthy older adults and 51 younger adults using two common data analytic approaches: independent component analysis and seed-based functional connectivity (seed at bilateral M1 and S1). We then evaluated whether the altered rsFC of the SM network could delineate trajectories of the age of older adults using a machine learning methodology. Compared with the younger adults, the older demonstrated reduced functional integration with increasing age in the mid-posterior insula of SM network and increased rsFC among the sensorimotor cortex. Moreover, the reduction in the rsFC of mid-posterior insula is associated with the age of older adults. Critically, the analysis based on two-aspect connectivity-based prediction frameworks revealed that the age of older adults could be reliably predicted by this reduced rsFC. These findings further indicated that healthy aging has a marked influence on the SM system that would be associated with a reorganization of SM system with aging. Our findings provide further insight into changes in sensorimotor function in the aging brain.

  8. The Functional Integration in the Sensory-Motor System Predicts Aging in Healthy Older Adults

    PubMed Central

    He, Hui; Luo, Cheng; Chang, Xin; Shan, Yan; Cao, Weifang; Gong, Jinnan; Klugah-Brown, Benjamin; Bobes, Maria A.; Biswal, Bharat; Yao, Dezhong

    2017-01-01

    Healthy aging is typically accompanied by a decrease in the motor capacity. Although the disrupted neural representations and performance of movement have been observed in older age in previous studies, the relationship between the functional integration of sensory-motor (SM) system and aging could be further investigated. In this study, we examine the impact of healthy aging on the resting-state functional connectivity (rsFC) of the SM system, and investigate as to how aging is affecting the rsFC in SM network. The SM network was identified and evaluated in 52 healthy older adults and 51 younger adults using two common data analytic approaches: independent component analysis and seed-based functional connectivity (seed at bilateral M1 and S1). We then evaluated whether the altered rsFC of the SM network could delineate trajectories of the age of older adults using a machine learning methodology. Compared with the younger adults, the older demonstrated reduced functional integration with increasing age in the mid-posterior insula of SM network and increased rsFC among the sensorimotor cortex. Moreover, the reduction in the rsFC of mid-posterior insula is associated with the age of older adults. Critically, the analysis based on two-aspect connectivity-based prediction frameworks revealed that the age of older adults could be reliably predicted by this reduced rsFC. These findings further indicated that healthy aging has a marked influence on the SM system that would be associated with a reorganization of SM system with aging. Our findings provide further insight into changes in sensorimotor function in the aging brain. PMID:28111548

  9. Pretransplant thymic function predicts acute rejection in antithymocyte globulin-treated renal transplant recipients.

    PubMed

    Bamoulid, Jamal; Courivaud, Cécile; Crepin, Thomas; Carron, Clémence; Gaiffe, Emilie; Roubiou, Caroline; Laheurte, Caroline; Moulin, Bruno; Frimat, Luc; Rieu, Philippe; Mousson, Christiane; Durrbach, Antoine; Heng, Anne-Elisabeth; Rebibou, Jean-Michel; Saas, Philippe; Ducloux, Didier

    2016-05-01

    Lack of clear identification of patients at high risk of acute rejection hampers the ability to individualize immunosuppressive therapy. Here we studied whether thymic function may predict acute rejection in antithymocyte globulin (ATG)-treated renal transplant recipients in 482 patients prospectively studied during the first year post-transplant of which 86 patients experienced acute rejection. Only CD45RA(+)CD31(+)CD4(+) T cell (recent thymic emigrant [RTE]) frequency (RTE%) was marginally associated with acute rejection in the whole population. This T-cell subset accounts for 26% of CD4(+) T cells. Pretransplant RTE% was significantly associated with acute rejection in ATG-treated patients (hazard ratio, 1.04; 95% confidence interval, 1.01-1.08) for each increased percent in RTE/CD4(+) T cells), but not in anti-CD25 monoclonal (αCD25 mAb)-treated patients. Acute rejection was significantly more frequent in ATG-treated patients with high pretransplant RTE% (31.2% vs. 16.4%) or absolute number of RTE/mm(3) (31.7 vs. 16.1). This difference was not found in αCD25 monclonal antibody-treated patients. Highest values of both RTE% (>31%, hazard ratio, 2.50; 95% confidence interval, 1.09-5.74) and RTE/mm(3) (>200/mm(3), hazard ratio, 3.71; 95% confidence interval, 1.59-8.70) were predictive of acute rejection in ATG-treated patients but not in patients having received αCD25 monoclonal antibody). Results were confirmed in a retrospective cohort using T-cell receptor excision circle levels as a marker of thymic function. Thus, pretransplant thymic function predicts acute rejection in ATG-treated patients. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

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

    PubMed

    Le, T T Yen; 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.

  11. Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

    PubMed Central

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

  12. Cloud prediction of protein structure and function with PredictProtein for Debian.

    PubMed

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

  13. Prediction of Membership in Rehabilitation Counseling Professional Associations

    ERIC Educational Resources Information Center

    Phillips, Brian N.; Leahy, Michael J.

    2012-01-01

    Declining membership is a concerning yet poorly understood issue affecting professional associations across disciplines (Bauman, 2008). Rehabilitation counseling association membership is in decline even while number of certified rehabilitation counselors continues to increase (Leahy, 2009). Factors influencing rehabilitation counseling…

  14. Prediction of Membership in Rehabilitation Counseling Professional Associations

    ERIC Educational Resources Information Center

    Phillips, Brian N.; Leahy, Michael J.

    2012-01-01

    Declining membership is a concerning yet poorly understood issue affecting professional associations across disciplines (Bauman, 2008). Rehabilitation counseling association membership is in decline even while number of certified rehabilitation counselors continues to increase (Leahy, 2009). Factors influencing rehabilitation counseling…

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

    PubMed

    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.

  16. A Bayesian Method to Incorporate Hundreds of Functional Characteristics with Association Evidence to Improve Variant Prioritization

    PubMed Central

    Gagliano, Sarah A.; Barnes, Michael R.

    2014-01-01

    The increasing quantity and quality of functional genomic information motivate the assessment and integration of these data with association data, including data originating from genome-wide association studies (GWAS). We used previously described GWAS signals (“hits”) to train a regularized logistic model in order to predict SNP causality on the basis of a large multivariate functional dataset. We show how this model can be used to derive Bayes factors for integrating functional and association data into a combined Bayesian analysis. Functional characteristics were obtained from the Encyclopedia of DNA Elements (ENCODE), from published expression quantitative trait loci (eQTL), and from other sources of genome-wide characteristics. We trained the model using all GWAS signals combined, and also using phenotype specific signals for autoimmune, brain-related, cancer, and cardiovascular disorders. The non-phenotype specific and the autoimmune GWAS signals gave the most reliable results. We found SNPs with higher probabilities of causality from functional characteristics showed an enrichment of more significant p-values compared to all GWAS SNPs in three large GWAS studies of complex traits. We investigated the ability of our Bayesian method to improve the identification of true causal signals in a psoriasis GWAS dataset and found that combining functional data with association data improves the ability to prioritise novel hits. We used the predictions from the penalized logistic regression model to calculate Bayes factors relating to functional characteristics and supply these online alongside resources to integrate these data with association data. PMID:24844982

  17. Developmental trajectories of acculturation in Hispanic adolescents: associations with family functioning and adolescent risk behavior.

    PubMed

    Schwartz, Seth J; Des Rosiers, Sabrina; Huang, Shi; Zamboanga, Byron L; Unger, Jennifer B; Knight, George P; Pantin, Hilda; Szapocznik, José

    2013-01-01

    This study examined longitudinal acculturation patterns, and their associations with family functioning and adolescent risk behaviors, in Hispanic immigrant families. A sample of 266 Hispanic adolescents (Mage  = 13.4) and their primary parents completed measures of acculturation, family functioning, and adolescent conduct problems, substance use, and sexual behavior at five timepoints. Mixture models yielded three trajectory classes apiece for adolescent and parent acculturation. Assimilated adolescents reported the poorest family functioning, but adolescent assimilation negatively predicted adolescent cigarette smoking, sexual activity, and unprotected sex indirectly through family functioning. Follow-up analyses indicated that discrepancies between adolescent and parent family functioning reports predicted these adolescent outcomes. Results are discussed regarding acculturation trajectories, adolescent risk behavior, and the mediating role of family functioning.

  18. Developmental Trajectories of Acculturation in Hispanic Adolescents: Associations With Family Functioning and Adolescent Risk Behavior

    PubMed Central

    Schwartz, Seth J.; Rosiers, Sabrina Des; Huang, Shi; Zamboanga, Byron L.; Unger, Jennifer B.; Knight, George P.; Pantin, Hilda; Szapocznik, José

    2012-01-01

    The present study examined longitudinal acculturation patterns, and their associations with family functioning and adolescent risk behaviors, in Hispanic immigrant families. A sample of 266 Hispanic adolescents (mean age 13.4) and their primary parents completed measures of acculturation, family functioning, and adolescent conduct problems, substance use, and sexual behavior at five timepoints. Mixture models yielded three trajectory classes apiece for adolescent and parent acculturation. Assimilated adolescents reported the poorest family functioning, but adolescent assimilation negatively predicted adolescent cigarette smoking, sexual activity, and unprotected sex indirectly through family functioning. Follow-up analyses indicated that discrepancies between adolescent and parent family functioning reports predicted these adolescent outcomes. Results are discussed regarding acculturation trajectories, adolescent risk behavior, and the mediating role of family functioning. PMID:23848416

  19. Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence.

    PubMed

    Schlagenhauf, Florian; Rapp, Michael A; Huys, Quentin J M; Beck, Anne; Wüstenberg, Torsten; Deserno, Lorenz; Buchholz, Hans-Georg; Kalbitzer, Jan; Buchert, Ralph; Bauer, Michael; Kienast, Thorsten; Cumming, Paul; Plotkin, Michail; Kumakura, Yoshitaka; Grace, Anthony A; Dolan, Raymond J; Heinz, Andreas

    2013-06-01

    Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with (1) functional magnetic resonance imaging during a reversal learning task and (2) in a subsample of 17 subjects also with positron emission tomography using 6-[(18) F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA K inapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving relate to ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity.

  20. The prediction of EEG signals using a feedback-structured adaptive rational function filter.

    PubMed

    Kim, H S; Kim, T S; Choi, Y H; Park, S H

    2000-08-01

    In this article, we present a feedback-structured adaptive rational function filter based on a recursive modified Gram-Schmidt algorithm and apply it to the prediction of an EEG signal that has nonlinear and nonstationary characteristics. For the evaluation of the prediction performance, the proposed filter is compared with other methods, where a single-step prediction and a multi-step prediction are considered for a short-term prediction, and the prediction performance is assessed in normalized mean square error. The experimental results show that the proposed filter shows better performance than other methods considered for the short-term prediction of EEG signals.

  1. Automated methods of predicting the function of biological sequences using GO and BLAST

    PubMed Central

    Jones, Craig E; Baumann, Ute; Brown, Alfred L

    2005-01-01

    Background With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with high accuracy. Our aim is to demonstrate how accuracy benchmarking can be used in a decision-making process evaluating competing designs of biological function predictors. We utilise the Gene Ontology, GO, a directed acyclic graph of functional terms, to annotate sequences with functional information describing their biological context. Initially we examine the effect on accuracy scores of increasing the allowed distance between predicted and a test set of curator assigned terms. Next we evaluate several annotator methods using accuracy benchmarking. Given an unannotated sequence we use the Basic Local Alignment Search Tool, BLAST, to find similar sequences that have already been assigned GO terms by curators. A number of methods were developed that utilise terms associated with the best five matching sequences. These methods were compared against a benchmark method of simply using terms associated with the best BLAST-matched sequence (best BLAST approach). Results The precision and recall of estimates increases rapidly as the amount of distance permitted between a predicted term and a correct term assignment increases. Accuracy benchmarking allows a comparison of annotation methods. A covering graph approach performs poorly, except where the term assignment rate is high. A term distance concordance approach has a similar accuracy to the best BLAST approach, demonstrating lower precision but higher recall. However, a discriminant function method has higher precision and recall than the best BLAST approach and other methods shown here. Conclusion Allowing term predictions to be counted correct if closely related to a correct term decreases the reliability of the accuracy score. As such we recommend using accuracy measures that require exact matching of predicted terms with curator assigned

  2. Automated methods of predicting the function of biological sequences using GO and BLAST.

    PubMed

    Jones, Craig E; Baumann, Ute; Brown, Alfred L

    2005-11-15

    With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with high accuracy. Our aim is to demonstrate how accuracy benchmarking can be used in a decision-making process evaluating competing designs of biological function predictors. We utilise the Gene Ontology, GO, a directed acyclic graph of functional terms, to annotate sequences with functional information describing their biological context. Initially we examine the effect on accuracy scores of increasing the allowed distance between predicted and a test set of curator assigned terms. Next we evaluate several annotator methods using accuracy benchmarking. Given an unannotated sequence we use the Basic Local Alignment Search Tool, BLAST, to find similar sequences that have already been assigned GO terms by curators. A number of methods were developed that utilise terms associated with the best five matching sequences. These methods were compared against a benchmark method of simply using terms associated with the best BLAST-matched sequence (best BLAST approach). The precision and recall of estimates increases rapidly as the amount of distance permitted between a predicted term and a correct term assignment increases. Accuracy benchmarking allows a comparison of annotation methods. A covering graph approach performs poorly, except where the term assignment rate is high. A term distance concordance approach has a similar accuracy to the best BLAST approach, demonstrating lower precision but higher recall. However, a discriminant function method has higher precision and recall than the best BLAST approach and other methods shown here. Allowing term predictions to be counted correct if closely related to a correct term decreases the reliability of the accuracy score. As such we recommend using accuracy measures that require exact matching of predicted terms with curator assigned terms. Furthermore, we conclude

  3. Predicting outcome after arteriovenous malformation-associated intracerebral hemorrhage with the original ICH score.

    PubMed

    Appelboom, Geoffrey; Hwang, Brian Y; Bruce, Samuel S; Piazza, Matthew A; Kellner, Christopher P; Meyers, Philip M; Connolly, E Sander

    2012-12-01

    To evaluate the predictive ability of the original ICH Score (oICH) in a large independent cohort of patients with arteriovenous malformation-associated intracerebral hemorrhage (AVM-ICH), an important cause of intracerebral hemorrhage (ICH) that is associated with significantly different epidemiology, clinical course, and outcome compared with primary ICH. During the period 1997-2009, 91 patients were admitted to Columbia Medical Center with acute AVM-ICH. Demographic and admission clinical and radiographic variables were obtained for 84 patients through retrospective chart review. Admission oICH and Spetzler-Martin grading scale (SMGS) were calculated. Outcome was assessed at 3 months using the modified Rankin Scale (mRS). Maximum Youden Indices were used to identify cutoffs for age and ICH volume that are associated with optimal predictive accuracy for an unfavorable outcome (mRS ≥ 3). Receiver operating characteristic (ROC) analysis was used to evaluate the predictive performance of oICH, and oICH with new age and ICH cutoff points (new AVM-ICH score based on original ICH Score [AVM-oICH]). The mean age was 35 years ± 14, and mean ICH volume was 22 mL ± 20. At 3-month follow-up, 3 (4%) patients were dead, and 15 (18%) had an unfavorable outcome. Two of the patients who died had oICH of 3, and one had oICH of 5. ICH volume of 37 mL and age of 41 years were identified as optimal cutoffs for predicting an unfavorable outcome. oICH and AVM-oICH showed good predictive accuracies with area under the curve of 0.914 and 0.891 (P = 0.422). AVM-oICH and oICH had similarly high sensitivities (0.889 and 0.944; P = 1.00), but the former had significantly greater specificity (0.879 vs. 0.682; P < 0.001). oICH is a valid clinical grading scale with high predictive accuracy for functional outcome after AVM-ICH. It is unclear whether the score is appropriate for risk stratification with regard to mortality because of the low risk of death associated with AVM-ICH. Simple

  4. Transdiagnostic Associations Between Functional Brain Network Integrity and Cognition.

    PubMed

    Sheffield, Julia M; Kandala, Sridhar; Tamminga, Carol A; Pearlson, Godfrey D; Keshavan, Matcheri S; Sweeney, John A; Clementz, Brett A; Lerman-Sinkoff, Dov B; Hill, S Kristian; Barch, Deanna M

    2017-06-01

    Cognitive impairment occurs across the psychosis spectrum and is associated with functional outcome. However, it is unknown whether these shared manifestations of cognitive dysfunction across diagnostic categories also reflect shared neurobiological mechanisms or whether the source of impairment differs. To examine whether the general cognitive deficit observed across psychotic disorders is similarly associated with functional integrity of 2 brain networks widely implicated in supporting many cognitive domains. A total of 201 healthy control participants and 375 patients with psychotic disorders from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were studied from September 29, 2007, to May 31, 2011. The B-SNIP recruited healthy controls and stable outpatients from 6 sites: Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Detroit, Michigan; and Hartford, Connecticut. All participants underwent cognitive testing and resting-state functional magnetic resonance imaging. Data analysis was performed from April 28, 2015, to February 21, 2017. The Brief Assessment of Cognition in Schizophrenia was used to measure cognitive ability. A principal axis factor analysis on the Brief Assessment of Cognition in Schizophrenia battery yielded a single factor (54% variance explained) that served as the measure of general cognitive ability. Functional network integrity measures included global and local efficiency of the whole brain, cingulo-opercular network (CON), frontoparietal network, and auditory network and exploratory analyses of all networks from the Power atlas. Group differences in network measures, associations between cognition and network measures, and mediation models were tested. The final sample for the current study included 201 healthy controls, 143 patients with schizophrenia, 103 patients with schizoaffective disorder, and 129 patients with psychotic bipolar disorder (mean [SD] age, 35.1 [12.0] years

  5. Obesity-Associated Biomarkers and Executive Function in Children

    PubMed Central

    Miller, Alison L.; Jong, Hannah; 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. PMID:25310758

  6. Prediction of potential disease-associated microRNAs based on random walk.

    PubMed

    Xuan, Ping; Han, Ke; Guo, Yahong; Li, Jin; Li, Xia; Zhong, Yingli; Zhang, Zhaogong; Ding, Jian

    2015-06-01

    Identifying microRNAs associated with diseases (disease miRNAs) is helpful for exploring the pathogenesis of diseases. Because miRNAs fulfill function via the regulation of their target genes and because the current number of experimentally validated targets is insufficient, some existing methods have inferred potential disease miRNAs based on the predicted targets. It is difficult for these methods to achieve excellent performance due to the high false-positive and false-negative rates for the target prediction results. Alternatively, several methods have constructed a network composed of miRNAs based on their associated diseases and have exploited the information within the network to predict the disease miRNAs. However, these methods have failed to take into account the prior information regarding the network nodes and the respective local topological structures of the different categories of nodes. Therefore, it is essential to develop a method that exploits the more useful information to predict reliable disease miRNA candidates. miRNAs with similar functions are normally associated with similar diseases and vice versa. Therefore, the functional similarity between a pair of miRNAs is calculated based on their associated diseases to construct a miRNA network. We present a new prediction method based on random walk on the network. For the diseases with some known related miRNAs, the network nodes are divided into labeled nodes and unlabeled nodes, and the transition matrices are established for the two categories of nodes. Furthermore, different categories of nodes have different transition weights. In this way, the prior information of nodes can be completely exploited. Simultaneously, the various ranges of topologies around the different categories of nodes are integrated. In addition, how far the walker can go away from the labeled nodes is controlled by restarting the walking. This is helpful for relieving the negative effect of noisy data. For the diseases

  7. Enhanced functional connectivity between sensorimotor and visual cortex predicts covariation bias in spider phobia.

    PubMed

    Wiemer, Julian; Pauli, Paul

    2016-12-01

    The overestimation of the relationship between fear-relevant stimuli and aversive consequences, a so called covariation bias, might contribute to the maintenance of anxiety disorders. In a recent fMRI study, we confronted spider phobia and healthy participants with pictures of spiders, mushrooms and puppies, randomly followed by painful electric stimuli (US). Spider phobics overestimated the spider-US association and displayed enhanced activity in US-related sensorimotor cortex (paracentral lobule, PCL). Here, we report results from an additional functional connectivity analysis. Within spider phobics but not in healthy controls, USs after spiders led to enhanced connectivity between PCL and left prefrontal cortex (PFC). Most importantly, covariation bias in spider phobia was predicted by connectivity between PCL and visual cortex, insula, primary sensorimotor cortex and secondary somatosensory cortex. Reduced covariation bias was predicted by connectivity between PCL and PFC. In response to spider pictures, the amygdala was functionally connected to somatosensory and visual areas. These results suggest that synchronous activity of sensory cortices may promote fear-sustaining associative memory bias, while right PFC might help to reduce bias. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    PubMed

    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.

  9. Discriminant function of perinatal risk that predicts early neonatal morbidity: its validity and reliability.

    PubMed

    Zapata-Vázquez, Rita Esther; Rodríguez-Carvajal, Luis Alfonso; Sierra-Basto, Gilberto; Alonzo-Vázquez, Felipe Manuel; Echeverría-Eguíluz, Manuel

    2003-01-01

    This study aimed to identify significant perinatal risk factors associated with neonatal morbidity to construct a scoring system to aid in distinguishing between healthy and ill neonates. Validity and reliability of the scoring system were determined. We conducted a screening test and used logistic regression to analyze data from a cohort of 387 neonates and to determine the relationship between risk factors and morbidity. Twenty nine factors of perinatal risk were studied. Logistic regression and discriminant analysis were performed to assess risk for morbidity. This system was developed and validated prospectively on 238 new neonates. Risk factors that demonstrated association with morbidity by logistic regression were chronic maternal illness, premature rupture of membranes (PROM), amniotic fluid, low Apgar score at 5 min, obstetric trauma, hypertension, neonatal resuscitation, breathing pattern at 6 h after delivery, birth weight, and gestational age. Discriminant function obtained from discriminant analysis had sensitivity of 68% and specificity of 93%, while positive and negative predictive values were 88 and 86%, respectively. Area below receiver operating characteristic (ROC) curve was 0.86 (standard error [SE]: 0.02). In the validity study, these values were maintained without significant differences. Kappa statistic between two physicians was calculated at 0.84 (p < 0.001). Evidence indicated that discriminant function is a useful tool to assess initial neonatal risk, allowing pediatricians to predict morbidity prior to discharge of neonates.

  10. A density functional theory for association of fluid molecules with a functionalized surface: fluid-wall single and double bonding.

    PubMed

    Haghmoradi, Amin; Wang, Le; Chapman, Walter G

    2017-02-01

    In this manuscript we extend Wertheim's two-density formalism beyond its first order to model a system of fluid molecules with a single association site close to a planar hard wall with association sites on its surface in a density functional theory framework. The association sites of the fluid molecules are small enough that they can form only one bond, while the wall association sites are large enough to bond with more than one fluid molecule. The effects of temperature and of bulk fluid and wall site densities on the fluid density profile, extent of association, and competition between single and double bonding of fluid segments at the wall sites versus distance from the wall are presented. The theory predictions are compared with new Monte Carlo simulation results and they are in good agreement. The theory captures the surface coverage over wide ranges of temperature and bulk density by introducing the effect of steric hindrance in fluid association at a wall site.

  11. Early prediction of functional outcome using dynamic contrast enhanced magnetic resonance imaging in experimental stroke.

    PubMed

    Huang, Wei-Yuan; Wu, Gang; Li, Jian-Jun; Geng, Dao-Ying; Tan, Wen-Li; Yu, Xiang-Rong

    2016-09-01

    Early prediction of functional outcome in cerebral ischemia stroke using MRI remains a challenge. The aim of this study was to evaluate the predictive value of dynamic contrast-enhanced (DCE) MRI in terms of functional outcome of ischemia stroke. Right middle cerebral artery occlusion (MCAO) was performed in male SD rats (n=50), followed by withdrawal of the occluding filament after 3 (n = 10), 4 (n = 10), 5 (n = 10), 6 (n = 10) or 7 (n = 10) h to establish ischemia and reperfusion stroke. DCE and conventional MRI were performed in each animal 60 ± 15 min before and after reperfusion. The outcome was assessed by the modified Neurological Severity Scores (mNSS) (before reperfusion and at 72 h after reperfusion) and the infarct volume. Comparisons of functional prognosis and DCE parameters (K(trans), Ve and Kep) were performed using binary logistic regression and operating characteristic (ROC) analysis. DCE parameters results indicated that blood brain barrier (BBB) permeability increased with prolonged reperfusion timing. Using binary logistic regression analysis on stroke characteristics (reperfusion timing, infarct volume) and BBB permeability parameters (drK(trans)subcortex, drK(trans)cortex, drVesubcortex, drVecortex, drKepsubcortex and drKepcortex) as covariates , the results demonstrated that reperfusion timing, infarct volume, drK(trans)subcortex and drKepsubcortex were independent factors that were associated with prognosis (OR=0.01, OR=0.23, OR=245.23, OR=1.29). ROC analysis indicated that a drK(trans)subcortex threshold of 0.88 with a sensitivity of 95.7% and a specificity of 85.2% and a drKepsubcortex threshold of -0.25 with a sensitivity of 69.6% and a specificity of 70.4% for differentiation between favourable and unfavourable prognosis. Quantitative DCE-MRI can be used to predict the functional outcomes of cerebral ischemia injury. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Functional network changes in hippocampal CA1 after status epilepticus predict spatial memory deficits in rats.

    PubMed

    Tyler, Anna L; Mahoney, J Matthew; Richard, Gregory R; Holmes, Gregory L; Lenck-Santini, Pierre-Pascal; Scott, Rod C

    2012-08-15

    Status epilepticus (SE) is a common neurological emergency, which has been associated with subsequent cognitive impairments. Neuronal death in hippocampal CA1 is thought to be an important mechanism of these impairments. However, it is also possible that functional interactions between surviving neurons are important. In this study we recorded in vivo single-unit activity in the CA1 hippocampal region of rats while they performed a spatial memory task. From these data we constructed functional networks describing pyramidal cell interactions. To build the networks, we used maximum entropy algorithms previously applied only to in vitro data. We show that several months following SE pyramidal neurons display excessive neuronal synchrony and less neuronal reactivation during rest compared with those in healthy controls. Both effects predict rat performance in a spatial memory task. These results provide a physiological mechanism for SE-induced cognitive impairment and highlight the importance of the systems-level perspective in investigating spatial cognition.

  13. PINALOG: a novel approach to align protein interaction networks--implications for complex detection and function prediction.

    PubMed

    Phan, Hang T T; Sternberg, Michael J E

    2012-05-01

    Analysis of protein-protein interaction networks (PPINs) at the system level has become increasingly important in understanding biological processes. Comparison of the interactomes of different species not only provides a better understanding of species evolution but also helps with detecting conserved functional components and in function prediction. Method and Here we report a PPIN alignment method, called PINALOG, which combines information from protein sequence, function and network topology. Alignment of human and yeast PPINs reveals several conserved subnetworks between them that participate in similar biological processes, notably the proteasome and transcription related processes. PINALOG has been tested for its power in protein complex prediction as well as function prediction. Comparison with PSI-BLAST in predicting protein function in the twilight zone also shows that PINALOG is valuable in predicting protein function. The PINALOG web-server is freely available from http://www.sbg.bio.ic.ac.uk/~pinalog. The PINALOG program and associated data are available from the Download section of the web-server. m.sternberg@imperial.ac.uk Supplementary data are available at Bioinformatics online.

  14. Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite.

    PubMed

    Siwo, Geoffrey H; Tan, Asako; Button-Simons, Katrina A; Samarakoon, Upeka; Checkley, Lisa A; Pinapati, Richard S; Ferdig, Michael T

    2015-02-22

    The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt's biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds. To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ's expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping. This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be

  15. Self-predictions of prospective memory in HIV-associated neurocognitive disorders: evidence of a metamemory deficit.

    PubMed

    Casaletto, Kaitlin Blackstone; Doyle, Katie L; Weber, Erica; Woods, Steven Paul

    2014-12-01

    HIV-associated neurocognitive disorders (HAND) are associated with deficits in prospective memory (PM; "remembering to remember"), conferring risk of daily functioning declines. However, self-perceptions of PM functioning are not reliably associated with PM performance in HIV, suggesting a possible deficit in awareness of PM abilities (meta-PM). Our study examined meta-PM in HAND and its correlates using self-predictions of laboratory-based PM performance. Performance-based PM abilities, self-reported prediction of PM performance, and PM complaints in everyday life were assessed in 49 individuals with HAND, 93 HIV+ without HAND (HIV+ noHAND), and 121 seronegative adults (HIV-). After controlling for group-level differences, HAND was associated with a greater number of PM symptoms in everyday life and worse PM performance when compared with both HIV+ noHAND and HIV- samples. Although HAND individuals reported somewhat lower predictions regarding their laboratory PM performance relative to the other study groups, they nevertheless exhibited significantly greater inaccurate overconfidence in time-based PM abilities. Within the HAND group, overconfidence in time-based meta-PM was associated with executive dysfunction and antiretroviral (ARV) nonadherence. HAND individuals evidenced a moderate deficit in awareness of PM functioning characterized by overconfidence in time-based PM abilities. Overconfidence in PM may result in absence of compensatory strategy use, and lead to increased errors in daily functioning (e.g., ARV nonadherence).

  16. Self-Predictions of Prospective Memory in HIV-Associated Neurocognitive Disorders: Evidence of a Metamemory Deficit

    PubMed Central

    Casaletto, Kaitlin Blackstone; Doyle, Katie L.; Weber, Erica; Woods, Steven Paul; Heaton, Robert K.; Grant, Igor; Atkinson, J. Hampton; Ellis, Ronald J.; Letendre, Scott; Marcotte, Thomas D.; Marquie-Beck, Jennifer; Sherman, Melanie; Ellis, Ronald J.; Letendre, Scott; McCutchan, J. Allen; Best, Brookie; Schrier, Rachel; Rosario, Debra; Heaton, Robert K.; Atkinson, J. Hampton; Woods, Steven Paul; D, Psy; Marcotte, Thomas D.; Cherner, Mariana; Moore, David J.; Dawson, Matthew; Fennema-Notestine, Christine; Buchsbaum, Monte S.; Hesselink, John; Archibald, Sarah L.; Brown, Gregory; Buxton, Richard; Dale, Anders; Liu, Thomas; Masliah, Eliezer; Achim, Cristian; Smith, David M.; Richman, Douglas; McCutchan, J. Allen; Cherner, Mariana; Achim, Cristian; Lipton, Stuart; Atkinson, J. Hampton; Marquie-Beck, Jennifer; Gamst, Anthony C.; Cushman, Clint; Abramson, Ian; Vaida, Florin; Deutsch, Reena; Umlauf, Anya

    2014-01-01

    HIV-associated neurocognitive disorders (HAND) are associated with deficits in prospective memory (PM; “remembering to remember”), conferring risk of daily functioning declines. However, self-perceptions of PM functioning are not reliably associated with PM performance in HIV, suggesting a possible deficit in awareness of PM abilities (meta-PM). Our study examined meta-PM in HAND and its correlates using self-predictions of laboratory-based PM performance. Performance-based PM abilities, self-reported prediction of PM performance, and PM complaints in everyday life were assessed in 49 individuals with HAND, 93 HIV+ without HAND (HIV+ noHAND), and 121 seronegative adults (HIV−). After controlling for group-level differences, HAND was associated with a greater number of PM symptoms in everyday life and worse PM performance when compared with both HIV+ noHAND and HIV− samples. Although HAND individuals reported somewhat lower predictions regarding their laboratory PM performance relative to the other study groups, they nevertheless exhibited significantly greater inaccurate overconfidence in time-based PM abilities. Within the HAND group, overconfidence in time-based meta-PM was associated with executive dysfunction and antiretroviral (ARV) nonadherence. HAND individuals evidenced a moderate deficit in awareness of PM functioning characterized by overconfidence in time-based PM abilities. Overconfidence in PM may result in absence of compensatory strategy use, and lead to increased errors in daily functioning (e.g., ARV nonadherence). PMID:25404005

  17. Prediction tool for thrombi associated with peripherally inserted central catheters.

    PubMed

    Seeley, Maria A; Santiago, Mary; Shott, Susan

    2007-01-01

    The upper extremity deep vein thrombosis rate is increasing at the same time that the rate for insertions of peripherally inserted central catheters is on the rise. There is little information on whether the established risk factors for lower extremity deep vein thromboses are effective to predict the occurrence of upper extremity deep vein thrombosis. The purpose of this study was to identify patients at highest risk for upper extremity deep vein thrombosis in order to initiate effective prophylaxis. A retrospective review was undertaken of medical records of all patients with peripherally inserted central catheters inserted in a 6-month period at a Midwestern US hospital. Of the 233 charts reviewed, 17 (7.3%) recorded an upper extremity deep vein thrombosis during the patient's hospital stay. Of the multiple factors identified with deep vein thrombosis in the literature, a weighted risk factor measure, the upper extremity deep vein thrombosis prediction tool, was developed. Sensitivity of the instrument for upper extremity deep vein thrombosis is high (88%), as are its specificity (82%) and negative predictive value (99%), whereas the positive predictive value is low (28%). The total percentage of cases correctly classified is 82%. Further testing is indicated on a larger sample to extend the validity of this instrument.

  18. Prediction of regional functional impairment following experimental stroke via connectome analysis.

    PubMed

    Schmitt, O; Badurek, S; Liu, W; Wang, Y; Rabiller, G; Kanoke, A; Eipert, P; Liu, J

    2017-04-13

    Recent advances in functional connectivity suggest that shared neuronal activation patterns define brain networks linking anatomically separate brain regions. We sought to investigate how cortical stroke disrupts multiple brain regions in processing spatial information. We conducted a connectome investigation at the mesoscale-level using the neuroVIISAS-framework, enabling the analysis of directed and weighted connectivity in bilateral hemispheres of cortical and subcortical brain regions. We found that spatial-exploration induced brain activation mapped by Fos, a proxy of neuronal activity, was differentially affected by stroke in a region-specific manner. The extent of hypoactivation following spatial exploration is inversely correlated with the spatial distance between the region of interest and region damaged by stroke, in particular within the parietal association and the primary somatosensory cortex, suggesting that the closer a region is to a stroke lesion, the more it would be affected during functional activation. Connectome modelling with 43 network parameters failed to reliably predict regions of hypoactivation in stroke rats exploring a novel environment, despite a modest correlation found for the centrality and hubness parameters in the home-caged animals. Further investigation in the inhibitory versus excitatory neuronal networks and microcircuit connectivity is warranted to improve the accuracy of predictability in post-stroke functional impairment.

  19. Prenatal diagnosis of Pierre Robin Sequence: accuracy and ability to predict phenotype and functional severity.

    PubMed

    Lind, Katia; Aubry, Marie-Cécile; Belarbi, Nadia; Chalouhi, Christel; Couly, Gérard; Benachi, Alexandra; Lyonnet, Stanislas; Abadie, Véronique

    2015-09-01

    To assess the outcome of fetuses who had sonographic features suggestive of Pierre Robin Sequence (PRS). All prenatal ultrasounds that mentioned 'posterior cleft palate', or 'micro or retrognathia' or 'PRS' over 13 and 20 years, respectively, at two obstetrical centers were reviewed. Medical records for children with isolated PRS monitored over 20 years at a PRS referral center for prenatal anomalies and the severity of neonatal feeding and respiratory functional disorders were utilized for comparison. From a prenatal ultrasound database of 166 000 cases, 157 had one or more of the sonographic signs suggestive of PRS and had follow-up available. Of them, 33 (21%) had confirmed PRS, 9 (6%) were normal and 115 (73%) had chromosomal aberrations, associated malformations or neurological anomalies. Visualization of a posterior cleft palate in addition to retro-micrognathia had a positive predictive value of 100% for PRS. The distribution of functional severity grades was similar in cases suspected prenatally as in 238 cases of PRS followed in the referral center in Necker Hospital. Only a minority of cases of fetal retrognathia have complete PRS; the majority have other severe conditions. Prenatal prediction of functional severity of isolated PRS is not possible. © 2015 John Wiley & Sons, Ltd.

  20. Predictability and irreversibility of genetic changes associated with flower color evolution in Penstemon barbatus.

    PubMed

    Wessinger, Carolyn A; Rausher, Mark D

    2014-04-01

    Two outstanding questions in evolutionary biology are whether, and how often, the genetic basis of phenotypic evolution is predictable; and whether genetic change constrains evolutionary reversibility. We address these questions by studying the genetic basis of red flower color in Penstemon barbatus. The production of red flowers often involves the inactivation of one or both of two anthocyanin pathway genes, Flavonoid 3',5'-hydroxylase (F3'5'h) and Flavonoid 3'-hydroxylase (F3'h). We used gene expression and enzyme function assays to determine that redundant inactivating mutations to F3'5'h underlie the evolution of red flowers in P. barbatus. Comparison of our results to previously characterized shifts from blue to red flowers suggests that the genetic change associated with the evolution of red flowers is predictable: when it involves elimination of F3'5'H activity, functional inactivation or deletion of this gene tends to occur; however, when it involves elimination of F3'H activity, tissue-specific regulatory substitutions occur and the gene is not functionally inactivated. This pattern is consistent with emerging data from physiological experiments indicating that F3'h may have pleiotropic effects and is thus subject to purifying selection. The multiple, redundant inactivating mutations to F3'5'h suggest that reversal to blue-purple flowers in this group would be unlikely. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

  1. Prediction of Functional Outcome in Individuals at Clinical High Risk for Psychosis

    PubMed Central

    Carrión, Ricardo E.; McLaughlin, Danielle; Goldberg, Terry E.; Auther, Andrea M.; Olsen, Ruth H.; Olvet, Doreen M.; Correll, Christoph U.; Cornblatt, Barbara A.

    2014-01-01

    Importance A major public health concern associated with schizophrenia and psychotic disorders is the long-term disability that involves impaired cognition, lack of social support, and an inability to function independently in the community. A critical goal of early detection and intervention studies in psychosis is therefore to understand the factors leading to this often profound impairment. Objective To develop a predictive model of functional (social and role) outcome in a clinical high-risk sample for psychosis. Design Prospective, naturalistic, longitudinal 3- to 5-year follow-up study. Setting The Recognition and Prevention Program in New York, a research clinic located in the Zucker Hillside Hospital in New York. Participants One hundred one treatment-seeking patients at clinical high risk for psychosis. Ninety-two (91%) were followed up prospectively for a mean (SD) of 3 (1.6) years. Intervention Neurocognitive and clinical assessment. Main Outcomes and Measures The primary outcome variables were social and role functioning at the last follow-up visit. Results Poor social outcome was predicted by reduced processing speed (odds ratio [OR], 1.38; 95% CI, 1.050-1.823; P = .02), impaired social functioning at baseline (OR, 1.85; 95% CI, 1.258-2.732; P = .002), and total disorganized symptoms (OR, 5.06; 95% CI, 1.548-16.527; P = .007). Reduced performance on tests for verbal memory (OR, 1.74; 95% CI, 1.169-2.594; P = .006), role functioning at baseline (OR, 1.34; 95% CI, 1.053-1.711; P = .02), and motor disturbances (OR, 1.77; 95% CI, 1.060-2.969; P = .03) predicted role outcome. The areas under the curve for the social and role prediction models were 0.824 (95% CI, 0.736-0.913; P < .001) and 0.77 (95% CI, 0.68-0.87; P < .001), respectively, demonstrating a high discriminative ability. In addition, poor functional outcomes were not entirely dependent on the development of psychosis, because 40.3% and 45.5% of nonconverters at clinical high risk had poor social

  2. Myocardial Extracellular Volume Estimation by CMR Predicts Functional Recovery Following Acute MI.

    PubMed

    Kidambi, Ananth; Motwani, Manish; Uddin, Akhlaque; Ripley, David P; McDiarmid, Adam K; Swoboda, Peter P; Broadbent, David A; Musa, Tarique Al; Erhayiem, Bara; Leader, Joshua; Croisille, Pierre; Clarysse, Patrick; Greenwood, John P; Plein, Sven

    2017-09-01

    In the setting of reperfused acute myocardial infarction (AMI), the authors sought to compare prediction of contractile recovery by infarct extracellular volume (ECV), as measured by T1-mapping cardiac magnetic resonance (CMR), with late gadolinium enhancement (LGE) transmural extent. The transmural extent of myocardial infarction as assessed by LGE CMR is a strong predictor of functional recovery, but accuracy of the technique may be reduced in AMI. ECV mapping by CMR can provide a continuous measure associated with the severity of tissue damage within infarcted myocardium. Thirty-nine patients underwent acute (day 2) and convalescent (3 months) CMR scans following AMI. Cine imaging, tissue tagging, T2-weighted imaging, modified Look-Locker inversion T1 mapping natively and 15 min post-gadolinium-contrast administration, and LGE imaging were performed. The ability of acute infarct ECV and acute transmural extent of LGE to predict convalescent wall motion, ejection fraction (EF), and strain were compared per-segment and per-patient. Per-segment, acute ECV and LGE transmural extent were associated with convalescent wall motion score (p < 0.01; p < 0.01, respectively). ECV had higher accuracy than LGE extent to predict improved wall motion (area under receiver-operating characteristics curve 0.77 vs. 0.66; p = 0.02). Infarct ECV ≤0.5 had sensitivity 81% and specificity 65% for prediction of improvement in segmental function; LGE transmural extent ≤0.5 had sensitivity 61% and specificity 71%. Per-patient, ECV and LGE correlated with convalescent wall motion score (r = 0.45; p < 0.01; r = 0.41; p = 0.02, respectively) and convalescent EF (p < 0.01; p = 0.04). ECV and LGE extent were not significantly correlated (r = 0.34; p = 0.07). In multivariable linear regression analysis, acute infarct ECV was independently associated with convalescent infarct strain and EF (p = 0.03; p = 0.04), whereas