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Sample records for predicts functional association

  1. 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/.

  2. 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.

  3. 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.

  4. 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.

  5. 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…

  6. Integrated protein function prediction by mining function associations, sequences, and protein–protein and gene–gene interaction networks

    PubMed Central

    Cao, Renzhi; Cheng, Jianlin

    2016-01-01

    Motivations 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. Results 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. PMID:26370280

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. Protein function prediction using domain families

    PubMed Central

    2013-01-01

    Here we assessed the use of domain families for predicting the functions of whole proteins. These 'functional families' (FunFams) were derived using a protocol that combines sequence clustering with supervised cluster evaluation, relying on available high-quality Gene Ontology (GO) annotation data in the latter step. In essence, the protocol groups domain sequences belonging to the same superfamily into families based on the GO annotations of their parent proteins. An initial test based on enzyme sequences confirmed that the FunFams resemble enzyme (domain) families much better than do families produced by sequence clustering alone. For the CAFA 2011 experiment, we further associated the FunFams with GO terms probabilistically. All target proteins were first submitted to domain superfamily assignment, followed by FunFam assignment and, eventually, function assignment. The latter included an integration step for multi-domain target proteins. The CAFA results put our domain-based approach among the top ten of 31 competing groups and 56 prediction methods, confirming that it outperforms simple pairwise whole-protein sequence comparisons. PMID:23514456

  1. Protein molecular function prediction by Bayesian phylogenomics.

    PubMed

    Engelhardt, Barbara E; Jordan, Michael I; Muratore, Kathryn E; Brenner, Steven E

    2005-10-01

    We present a statistical graphical model to infer specific molecular function for unannotated protein sequences using homology. Based on phylogenomic principles, SIFTER (Statistical Inference of Function Through Evolutionary Relationships) accurately predicts molecular function for members of a protein family given a reconciled phylogeny and available function annotations, even when the data are sparse or noisy. Our method produced specific and consistent molecular function predictions across 100 Pfam families in comparison to the Gene Ontology annotation database, BLAST, GOtcha, and Orthostrapper. We performed a more detailed exploration of functional predictions on the adenosine-5'-monophosphate/adenosine deaminase family and the lactate/malate dehydrogenase family, in the former case comparing the predictions against a gold standard set of published functional characterizations. Given function annotations for 3% of the proteins in the deaminase family, SIFTER achieves 96% accuracy in predicting molecular function for experimentally characterized proteins as reported in the literature. The accuracy of SIFTER on this dataset is a significant improvement over other currently available methods such as BLAST (75%), GeneQuiz (64%), GOtcha (89%), and Orthostrapper (11%). We also experimentally characterized the adenosine deaminase from Plasmodium falciparum, confirming SIFTER's prediction. The results illustrate the predictive power of exploiting a statistical model of function evolution in phylogenomic problems. A software implementation of SIFTER is available from the authors.

  2. 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. ...

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  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. 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

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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...

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. GAPIT: genome association and prediction integrated tool

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  16. 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

  17. 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

  18. 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

  19. 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.

  20. CombFunc: predicting protein function using heterogeneous data sources

    PubMed Central

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

    2012-01-01

    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. PMID:22641853

  1. 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…

  2. 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

  3. 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.

  4. 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

  5. Concomitant prediction of function and fold at the domain level with GO-based profiles

    PubMed Central

    2013-01-01

    Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required. We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function. PMID:23514233

  6. 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.

  7. 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.

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

    PubMed Central

    2010-01-01

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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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…

  16. 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

  17. 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.

  18. 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

  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 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.

  1. A Statistical Model of Protein Sequence Similarity and Function Similarity Reveals Overly-Specific Function Predictions

    PubMed Central

    Kolker, Eugene

    2009-01-01

    Background Predicting protein function from primary sequence is an important open problem in modern biology. Not only are there many thousands of proteins of unknown function, current approaches for predicting function must be improved upon. One problem in particular is overly-specific function predictions which we address here with a new statistical model of the relationship between protein sequence similarity and protein function similarity. Methodology Our statistical model is based on sets of proteins with experimentally validated functions and numeric measures of function specificity and function similarity derived from the Gene Ontology. The model predicts the similarity of function between two proteins given their amino acid sequence similarity measured by statistics from the BLAST sequence alignment algorithm. A novel aspect of our model is that it predicts the degree of function similarity shared between two proteins over a continuous range of sequence similarity, facilitating prediction of function with an appropriate level of specificity. Significance Our model shows nearly exact function similarity for proteins with high sequence similarity (bit score >244.7, e-value >1e−62, non-redundant NCBI protein database (NRDB)) and only small likelihood of specific function match for proteins with low sequence similarity (bit score <54.6, e-value <1e−05, NRDB). For sequence similarity ranges in between our annotation model shows an increasing relationship between function similarity and sequence similarity, but with considerable variability. We applied the model to a large set of proteins of unknown function, and predicted functions for thousands of these proteins ranging from general to very specific. We also applied the model to a data set of proteins with previously assigned, specific functions that were electronically based. We show that, on average, these prior function predictions are more specific (quite possibly overly-specific) compared to

  2. 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

  3. 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...

  4. 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.

  5. 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.

  6. 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…

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. Predicting Gene-Disease Associations Using Multiple Species Data

    DTIC Science & Technology

    2011-10-20

    regulatory networks from only positive and unlabeled data. BMC Bioinformatics, 11, 2010. [4] Ernesto Estrada and Desmond J. Higham. Network properties revealed...David Warde-Farley, Chris Grouios, and Quaid Morris . GeneMANIA: a real-time multiple association network integration algorithm for predicting gene

  12. 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…

  13. 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

  14. 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.

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

    PubMed Central

    2012-01-01

    Background 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. Results 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. Conclusions 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

  16. 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

  17. 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

  18. ESG: extended similarity group method for automated protein function prediction

    PubMed Central

    Chitale, Meghana; Hawkins, Troy; Park, Changsoon; Kihara, Daisuke

    2009-01-01

    Motivation: Importance of accurate automatic protein function prediction is ever increasing in the face of a large number of newly sequenced genomes and proteomics data that are awaiting biological interpretation. Conventional methods have focused on high sequence similarity-based annotation transfer which relies on the concept of homology. However, many cases have been reported that simple transfer of function from top hits of a homology search causes erroneous annotation. New methods are required to handle the sequence similarity in a more robust way to combine together signals from strongly and weakly similar proteins for effectively predicting function for unknown proteins with high reliability. Results: We present the extended similarity group (ESG) method, which performs iterative sequence database searches and annotates a query sequence with Gene Ontology terms. Each annotation is assigned with probability based on its relative similarity score with the multiple-level neighbors in the protein similarity graph. We will depict how the statistical framework of ESG improves the prediction accuracy by iteratively taking into account the neighborhood of query protein in the sequence similarity space. ESG outperforms conventional PSI-BLAST and the protein function prediction (PFP) algorithm. It is found that the iterative search is effective in capturing multiple-domains in a query protein, enabling accurately predicting several functions which originate from different domains. Availability: ESG web server is available for automated protein function prediction at http://dragon.bio.purdue.edu/ESG/ Contact: cspark@cau.ac.kr; dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19435743

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

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

    PubMed Central

    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. PMID:25848497

  6. 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/.

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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

  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. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  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. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. PROSNET: INTEGRATING HOMOLOGY WITH MOLECULAR NETWORKS FOR PROTEIN FUNCTION PREDICTION

    PubMed Central

    Wang, Sheng; Qu, Meng

    2016-01-01

    Automated annotation of protein function has become a critical task in the post-genomic era. Network-based approaches and homology-based approaches have been widely used and recently tested in large-scale community-wide assessment experiments. It is natural to integrate network data with homology information to further improve the predictive performance. However, integrating these two heterogeneous, high-dimensional and noisy datasets is non-trivial. In this work, we introduce a novel protein function prediction algorithm ProSNet. An integrated heterogeneous network is first built to include molecular networks of multiple species and link together homologous proteins across multiple species. Based on this integrated network, a dimensionality reduction algorithm is introduced to obtain compact low-dimensional vectors to encode proteins in the network. Finally, we develop machine learning classification algorithms that take the vectors as input and make predictions by transferring annotations both within each species and across different species. Extensive experiments on five major species demonstrate that our integration of homology with molecular networks substantially improves the predictive performance over existing approaches. PMID:27896959

  14. 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.

  15. 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

  16. 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

  17. 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

  18. An application of site response functions to ground motion prediction

    NASA Astrophysics Data System (ADS)

    Tsuda, K.; Archuleta, R.; Steidl, J.; Koketsu, K.

    2006-12-01

    The prediction of ground motion from large future earthquakes is very important for hazard mitigation in urban areas of Japan. Because the observed ground motions are affected by three factors; the seismic source, attenuation (quality factor) of seismic wave propagation inside the earth, and the effects of the local surface geology, understanding each factor is essential for the ground motion prediction. The effect of surface geology (local soil conditions) on ground motions was documented as early as the 1906 San Francisco earthquake. The correlation between soil type and the degree of damage was again recognized in the 1923 Kanto earthquake. Additionally, accelerometer records from almost all recent large events also have reinforced the role of site effects in the level of strong shaking. Because most cities in Japan are located on thick sedimentary basins, accounting for site response is essential for realistic predictions of ground motion. However, predicting ground motion has uncertainties that arise from all three factors: source, path, and site. The analysis of well-recorded data from dense seismograph arrays can reduce these uncertainties for ground motion prediction. The new technique presented here provides a site response correlation function for estimation of the spatial distribution of site response. This function is based on the known site responses at instrumented sites and is used to estimate the site response at a site for which there is no instrumental records. We initially predict the level of ground motion by using this estimate with the assumption of linear wave propagation. This method is applied to the data from a relatively dense seismic array located near the city of Sendai, Japan by using moderate sized earthquakes with small ground motion levels to estimate linear site response. The array consists of 29 stations: 20 managed by Tohoku Institute of Technology, 6 by Building Research Institute, and 3 by NIED within an area of 20 x 30 km

  19. 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.

  20. Computational Prediction of Protein Function Based on Weighted Mapping of Domains and GO Terms

    PubMed Central

    Teng, Zhixia; Guo, Maozu; Dai, Qiguo; Wang, Chunyu; Li, Jin; Liu, Xiaoyan

    2014-01-01

    In this paper, we propose a novel method, SeekFun, to predict protein function based on weighted mapping of domains and GO terms. Firstly, a weighted mapping of domains and GO terms is constructed according to GO annotations and domain composition of the proteins. The association strength between domain and GO term is weighted by symmetrical conditional probability. Secondly, the mapping is extended along the true paths of the terms based on GO hierarchy. Finally, the terms associated with resident domains are transferred to host protein and real annotations of the host protein are determined by association strengths. Our careful comparisons demonstrate that SeekFun outperforms the concerned methods on most occasions. SeekFun provides a flexible and effective way for protein function prediction. It benefits from the well-constructed mapping of domains and GO terms, as well as the reasonable strategy for inferring annotations of protein from those of its domains. PMID:24868539

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. GOPred: GO Molecular Function Prediction by Combined Classifiers

    PubMed Central

    Saraç, Ömer Sinan; Atalay, Volkan; Cetin-Atalay, Rengul

    2010-01-01

    Functional protein annotation is an important matter for in vivo and in silico biology. Several computational methods have been proposed that make use of a wide range of features such as motifs, domains, homology, structure and physicochemical properties. There is no single method that performs best in all functional classification problems because information obtained using any of these features depends on the function to be assigned to the protein. In this study, we portray a novel approach that combines different methods to better represent protein function. First, we formulated the function annotation problem as a classification problem defined on 300 different Gene Ontology (GO) terms from molecular function aspect. We presented a method to form positive and negative training examples while taking into account the directed acyclic graph (DAG) structure and evidence codes of GO. We applied three different methods and their combinations. Results show that combining different methods improves prediction accuracy in most cases. The proposed method, GOPred, is available as an online computational annotation tool (http://kinaz.fen.bilkent.edu.tr/gopred). PMID:20824206

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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].

  1. 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

  2. Relationship functioning and home and work demands predict individual differences in diurnal cortisol patterns in women.

    PubMed

    Adam, E K; Gunnar, M R

    2001-02-01

    In 70 middle-class mothers of 2-year-old children, individual differences in mothers' morning cortisol levels, cortisol decreases across the day and average cortisol levels were predicted from demographic and medical control variables, maternal relationship functioning and home and work demands. For two days, salivary cortisol levels were measured in the morning immediately after wakeup, four times in the afternoon, and in the evening immediately prior to bedtime. Hierarchical linear modeling (HLM) growth curve analyses were used to estimate the intercept (early morning level), slope (steepness of decline in cortisol values across the day), and the average height of each mother's cortisol curve across the waking hours. HLM and multiple regression techniques were then used to predict individual differences in these parameters from the variables of interest. Time of day accounted for 72% of the variation in mothers' observed cortisol values across the day. After controlling for demographic and medical variables, positive relationship functioning was associated with higher morning cortisol levels and a steeper decline in cortisol across the day, while greater hours of maternal employment and a greater number of children in the household were associated with lower morning cortisol values and a less steep decline in cortisol levels across the day. Variables predicting higher morning values also predicted higher average cortisol levels, while variables predicting lower morning cortisol predicted lower average cortisol levels. The full model including selected control, relationship functioning and home and work demand variables accounted for 40% of the variance in mothers' morning cortisol values, 43% of the variance in cortisol slopes and 35% of the variability in mothers' average cortisol levels. This study presents the first evidence of associations between psychological variables and individual differences in the organization of cortisol levels across the waking day

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  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. 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.

  16. A novel neural response algorithm for protein function prediction

    PubMed Central

    2012-01-01

    Background Large amounts of data are being generated by high-throughput genome sequencing methods. But the rate of the experimental functional characterization falls far behind. To fill the gap between the number of sequences and their annotations, fast and accurate automated annotation methods are required. Many methods, such as GOblet, GOFigure, and Gotcha, are designed based on the BLAST search. Unfortunately, the sequence coverage of these methods is low as they cannot detect the remote homologues. Adding to this, the lack of annotation specificity advocates the need to improve automated protein function prediction. Results We designed a novel automated protein functional assignment method based on the neural response algorithm, which simulates the neuronal behavior of the visual cortex in the human brain. Firstly, we predict the most similar target protein for a given query protein and thereby assign its GO term to the query sequence. When assessed on test set, our method ranked the actual leaf GO term among the top 5 probable GO terms with accuracy of 86.93%. Conclusions The proposed algorithm is the first instance of neural response algorithm being used in the biological domain. The use of HMM profiles along with the secondary structure information to define the neural response gives our method an edge over other available methods on annotation accuracy. Results of the 5-fold cross validation and the comparison with PFP and FFPred servers indicate the prominent performance by our method. The program, the dataset, and help files are available at http://www.jjwanglab.org/NRProF/. PMID:23046521

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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

  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. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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)

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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…

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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…

  3. Systemic vascular function is associated with muscular power in adults

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. 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.

  5. 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

  6. 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

  7. 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.

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins

    PubMed Central

    2012-01-01

    Background Advancements in function prediction algorithms are enabling large scale computational annotation for newly sequenced genomes. With the increase in the number of functionally well characterized proteins it has been observed that there are many proteins involved in more than one function. These proteins characterized as moonlighting proteins show varied functional behavior depending on the cell type, localization in the cell, oligomerization, multiple binding sites, etc. The functional diversity shown by moonlighting proteins may have significant impact on the traditional sequence based function prediction methods. Here we investigate how well diverse functions of moonlighting proteins can be predicted by some existing function prediction methods. Results We have analyzed the performances of three major sequence based function prediction methods, PSI-BLAST, the Protein Function Prediction (PFP), and the Extended Similarity Group (ESG) on predicting diverse functions of moonlighting proteins. In predicting discrete functions of a set of 19 experimentally identified moonlighting proteins, PFP showed overall highest recall among the three methods. Although ESG showed the highest precision, its recall was lower than PSI-BLAST. Recall by PSI-BLAST greatly improved when BLOSUM45 was used instead of BLOSUM62. Conclusion We have analyzed the performances of PFP, ESG, and PSI-BLAST in predicting the functional diversity of moonlighting proteins. PFP shows overall better performance in predicting diverse moonlighting functions as compared with PSI-BLAST and ESG. Recall by PSI-BLAST greatly improved when BLOSUM45 was used. This analysis indicates that considering weakly similar sequences in prediction enhances the performance of sequence based AFP methods in predicting functional diversity of moonlighting proteins. The current study will also motivate development of novel computational frameworks for automatic identification of such proteins. PMID:23173871

  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. 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

  1. 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.

  2. 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).

  3. 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

  4. Predicting minimum-bias trigger-associated dijet correlations in p-p collisions

    NASA Astrophysics Data System (ADS)

    Trainor, Thomas A.

    2015-08-01

    A method is derived to predict the structure of dijet-related hard components of trigger-associated (TA) hadron correlations from p-p collisions based on measured fragmentation functions (FFs) from {e}+-{e}- or p-\\bar{p} collisions and a minimum-bias (MB) jet or scattered-parton spectrum from p-\\bar{p} collisions. The method is based on the probability chain rule and Bayes’ theorem and relates a trigger-parton-associated-fragment system from reconstructed dijets to a trigger-hadron-associated hadron system from p-p data. The method is tested in this study by comparisons of FF TA structure with preliminary p-p TA data but can also be applied to p-A, d-A and A-A collisions over a range of energies. Quantitative comparisons of measured TA correlations with FF-derived predictions may confirm a quantum chromodynamics MB dijet mechanism for certain spectrum and correlation structures whose origins are currently questioned and have been attributed by some to collective expansion (flows).

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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 (...

  10. 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.

  11. 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.

  12. 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

  13. On Parameter Differentiation for Integral Representations of Associated Legendre Functions

    NASA Astrophysics Data System (ADS)

    Cohl, Howard S.

    2011-05-01

    For integral representations of associated Legendre functions in terms of modified Bessel functions, we establish justification for differentiation under the integral sign with respect to parameters. With this justification, derivatives for associated Legendre functions of the first and second kind with respect to the degree are evaluated at odd-half-integer degrees, for general complex-orders, and derivatives with respect to the order are evaluated at integer-orders, for general complex-degrees. We also discuss the properties of the complex function f: C\\{-1,1}→C given by f(z)=z/((z+1)1/2(z-1)1/2).

  14. 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.

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-01-29

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

  17. 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.

  18. 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

  19. 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

  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. 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.

  2. Functional relevance for associations between osteoporosis and genetic variants

    PubMed Central

    Tan, Li-Jun; Wang, Peng; Chen, Xiang-Ding; Zhu, Li-Hua; Zeng, Qin; Hu, Yuan; Deng, Hong-Wen

    2017-01-01

    Osteoporosis is characterized by increased bone loss and deterioration of bone microarchitecture, which will lead to reduced bone strength and increased risk of fragility fractures. Previous studies have identified many genetic loci associated with osteoporosis, but functional mechanisms underlying the associations have rarely been explored. In order to explore the potential molecular functional mechanisms underlying the associations for osteoporosis, we performed integrative analyses by using the publically available datasets and resources. We searched 128 identified osteoporosis associated SNPs (P<10−6), and 8 SNPs exert cis-regulation effects on 11 eQTL target genes. Among the 8 SNPs, 2 SNPs (RPL31 rs2278729 and LRP5 rs3736228) were confirmed to impact the expression of 3 genes (RPL31, CPT1A and MTL5) that were differentially expressed between human subjects of high BMD group and low BMD group. All of the functional evidence suggested the important functional mechanisms underlying the associations of the 2 SNPs (rs2278729 and rs3736228) and 3 genes (RPL31, CPT1A and MTL5) with osteoporosis. This study may provide novel insights into the functional mechanisms underlying the osteoporosis associated genetic variants, which will help us to comprehend the potential mechanisms underlying the genetic association for osteoporosis. PMID:28369098

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  4. Do Executive Functions Predict Binge-Drinking Patterns? Evidence from a Longitudinal Study in Young Adulthood

    PubMed Central

    Bø, Ragnhild; Billieux, Joël; Gjerde, Line C.; Eilertsen, Espen M.; Landrø, Nils I.

    2017-01-01

    Background: Impairments in executive functions (EFs) are related to binge drinking in young adulthood, but research on how EFs influence future binge drinking is lacking. The aim of the current report is therefore to investigate the association between various EFs and later severity of, and change in, binge drinking over a prolonged period during young adulthood. Methods: At baseline, 121 students reported on their alcohol habits (Alcohol use disorder identification test; Alcohol use questionnaire). Concurrently, EFs [working memory, reversal, set-shifting, response inhibition, response monitoring and decision-making (with ambiguity and implicit risk)] were assessed. Eighteen months later, information on alcohol habits for 103 of the participants were gathered. Data were analyzed by means of multilevel regression modeling. Results: Future severity of binge drinking was uniquely predicted by performance on the Information sampling task, assessing risky decision-making (β = -1.86, 95% CI: -3.69, -0.04). None of the study variables predicted severity or change in binge drinking. Conclusion: Future severity of binge drinking was associated with making risky decisions in the prospect for gain, suggesting reward hypersensitivity. Future studies should aim at clarifying whether there is a causal association between decision-making style and binge drinking. Performance on all executive tasks was unrelated to change in binge drinking patterns; however, the finding was limited by overall small changes, and needs to be confirmed with longer follow-up periods.

  5. PRODH gene is associated with executive function in schizophrenic families.

    PubMed

    Li, Tao; Ma, Xiaohong; Hu, Xun; Wang, Yingcheng; Yan, Chengying; Meng, Huaqing; Liu, Xiehe; Toulopoulou, Timothea; Murray, Robin M; Collier, David A

    2008-07-05

    The aim of this study was to investigate the relationship between polymorphisms in the PRODH and COMT genes and selected neurocognitive functions. Six SNPs in PRODH and two SNPs in COMT were genotyped in 167 first-episode schizophrenic families who had been assessed by a set of 14 neuropsychological tests. Neuropsychological measures were selected as quantitative traits for association analysis. The haplotype of SNPs PRODH 1945T/C and PRODH 1852G/A was associated with impaired performance on the Tower of Hanoi, a problem-solving task mainly reflecting planning capacity. There was no significant evidence for association with any other neuropsychological traits for other SNPs or haplotypes of paired SNPs in the two genes. This study takes previous findings of association between PRODH and schizophrenia further by associating variation within the gene with performance on a neurocognitive trait characteristic of the illness. It fails to confirm previous reports of an association between COMT and cognitive function.

  6. Diagnostic Methods for Predicting Performance Impairment Associated With Combat Stress

    DTIC Science & Technology

    2004-12-01

    physiological stress index. The design of the study allows us to compare TCD, salivary cortisol, and subjective state as predictors of subsequent...provide a suitable environment for correlating changes in brain physiology with vigilance performance over a prolonged period of time. The Transcranial...may produce multiple, independent changes in physiological and psychological functioning, changes that cannot be adequately described in terms of

  7. 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.

  8. A triangular property of the associated Legendre functions

    NASA Technical Reports Server (NTRS)

    Fineschi, S.; Landi Degl'innocenti, E.

    1990-01-01

    A mathematical formula is introduced and proved which relates the associated Legendre functions with given nonnegative integral indices. The application of this formula in simplifying the calculation of collisional electron-atom cross sections higher than the dipole is mentioned. A proof of the stated identity using the Gegenbauer polynomials and their generating function is given.

  9. Correlating observed odds ratios from lung cancer case-control studies to SNP functional scores predicted by bioinformatic tools

    PubMed Central

    Zhu, Yong; Hoffman, Aaron; Wu, Xifeng; Zhang, Heping; Zhang, Yawei; Leaderer, Derek; Zheng, Tongzhang

    2008-01-01

    Bioinformatic tools are widely utilized to predict functional single nucleotide polymorphisms (SNPs) for genotyping in molecular epidemiological studies. However, the extent to which these approaches are mirrored by epidemiological findings has not been fully explored. In this study, we first surveyed SNPs examined in case-control studies of lung cancer, the most extensively-studied cancer type. We then computed SNP functional scores using four popular bioinformatics tools: SIFT, PolyPhen, SNPs3D, and PMut, and determined their predictive potential using the odds ratios (ORs) reported. Spearman’s correlation coefficient (r) for the association with SNP score from SIFT, PolyPhen, SNPs3D, and PMut, and the summary ORs were r = −0.36 (p = 0.007), r = 0.25 (p = 0.068), r = −0.20 (p = 0.205), and r = −0.12 (p = 0.370) respectively. By creating a combined score using information from all four tools we were able to achieve a correlation coefficient of r = 0.51 (p < 0.001). These results indicate that scores of predicted functionality could explain a certain fraction of the lung cancer risk detected in genetic association studies and more accurate predictions may be obtained by combining information from a variety of tools. Our findings suggest that bioinformatic tools are useful in predicting SNP functionality and may facilitate future genetic epidemiological studies. PMID:18191955

  10. Improved association in a classical density functional theory for water

    SciTech Connect

    Krebs, Eric J.; Schulte, Jeff B.; Roundy, David

    2014-03-28

    We present a modification to our recently published statistical associating fluid theory-based classical density functional theory for water. We have recently developed and tested a functional for the averaged radial distribution function at contact of the hard-sphere fluid that is dramatically more accurate at interfaces than earlier approximations. We now incorporate this improved functional into the association term of our free energy functional for water, improving its description of hydrogen bonding. We examine the effect of this improvement by studying two hard solutes (a hard hydrophobic rod and a hard sphere) and a Lennard-Jones approximation of a krypton atom solute. The improved functional leads to a moderate change in the density profile and a large decrease in the number of hydrogen bonds broken in the vicinity of the hard solutes. We find an improvement of the partial radial distribution for a krypton atom in water when compared with experiment.

  11. Computational strategies for predicting the potential risks associated with nanotechnology.

    PubMed

    Barnard, Amanda S

    2009-10-01

    For the move from nanoscience to nanotechnology to be sustainable, it is important that the issues surrounding possible 'nano-hazards' be addressed before commercialization. The global push for more environmentally friendly, biodegradable products, means the introduction of the nanoparticles contained within these products into the ecosystem is an inevitability. When this happens, it is desirable to know how the hazardous properties may be affected, and what the potential hazards are. In this article, a number of strategies will be discussed, combining the desirable aspects of theory, simulation, experiment and observation, and leading to predictions for incorporation into preventative frameworks. Particular attention will be given to the role of theory and computation, and how it intersects with the participants from complementary fields.

  12. Locally Epistatic Genomic Relationship Matrices for Genomic Association and Prediction

    PubMed Central

    Akdemir, Deniz; Jannink, Jean-Luc

    2015-01-01

    In plant and animal breeding studies a distinction is made between the genetic value (additive plus epistatic genetic effects) and the breeding value (additive genetic effects) of an individual since it is expected that some of the epistatic genetic effects will be lost due to recombination. In this article, we argue that the breeder can take advantage of the epistatic marker effects in regions of low recombination. The models introduced here aim to estimate local epistatic line heritability by using genetic map information and combining local additive and epistatic effects. To this end, we have used semiparametric mixed models with multiple local genomic relationship matrices with hierarchical designs. Elastic-net postprocessing was used to introduce sparsity. Our models produce good predictive performance along with useful explanatory information. PMID:25614606

  13. 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

  14. Executive Function Predicts Artificial Language Learning in Children and Adults

    ERIC Educational Resources Information Center

    Kapa, Leah Lynn

    2013-01-01

    Prior research has established an executive function advantage among bilinguals as compared to monolingual peers. These non-linguistic cognitive advantages are largely assumed to result from the experience of managing two linguistic systems. However, the possibility remains that the relationship between bilingualism and executive function is…

  15. Timing Correlations in Proteins Predict Functional Modules and Dynamic Allostery.

    PubMed

    Lin, Milo M

    2016-04-20

    How protein structure encodes functionality is not fully understood. For example, long-range intraprotein communication can occur without measurable conformational change and is often not captured by existing structural correlation functions. It is shown here that important functional information is encoded in the timing of protein motions, rather than motion itself. I introduce the conditional activity function to quantify such timing correlations among the degrees of freedom within proteins. For three proteins, the conditional activities between side-chain dihedral angles were computed using the output of microseconds-long atomistic simulations. The new approach demonstrates that a sparse fraction of side-chain pairs are dynamically correlated over long distances (spanning protein lengths up to 7 nm), in sharp contrast to structural correlations, which are short-ranged (<1 nm). Regions of high self- and inter-side-chain dynamical correlations are found, corresponding to experimentally determined functional modules and allosteric connections, respectively.

  16. Identification of associations between small molecule drugs and miRNAs based on functional similarity

    PubMed Central

    Dai, EnYu; Yang, Feng; Wang, Shuyuan; Chen, Xiaowen; Yang, Lei; Wang, Yuwen; Jiang, Wei

    2016-01-01

    MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that regulate gene expression at post-transcriptional level. Increasing evidences show aberrant expression of miRNAs in varieties of diseases. Targeting the dysregulated miRNAs with small molecule drugs has become a novel therapy for many human diseases, especially cancer. Here, we proposed a novel computational approach to identify associations between small molecules and miRNAs based on functional similarity of differentially expressed genes. At the significance level of p < 0.01, we constructed the small molecule and miRNA functional similarity network involving 111 small molecules and 20 miRNAs. Moreover, we also predicted associations between drugs and diseases through integrating our identified small molecule-miRNA associations with experimentally validated disease related miRNAs. As a result, we identified 2265 associations between FDA approved drugs and diseases, in which ~35% associations have been validated by comprehensive literature reviews. For breast cancer, we identified 19 potential drugs, in which 12 drugs were supported by previous studies. In addition, we performed survival analysis for the patients from TCGA and GEO database, which indicated that the associated miRNAs of 4 drugs might be good prognosis markers in breast cancer. Collectively, this study proposed a novel approach to predict small molecule and miRNA associations based on functional similarity, which may pave a new way for miRNA-targeted therapy and drug repositioning. PMID:27232942

  17. DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

    SciTech Connect

    McDermott, Jason E.; Costa, Michelle N.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.

    2011-01-20

    A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks that are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a

  18. Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm

    PubMed Central

    Yu, Hua; Chen, Xiaojun; Lu, Lu

    2017-01-01

    Identification of the associations between microRNA molecules and human diseases from large-scale heterogeneous biological data is an important step for understanding the pathogenesis of diseases in microRNA level. However, experimental verification of microRNA-disease associations is expensive and time-consuming. To overcome the drawbacks of conventional experimental methods, we presented a combinatorial prioritization algorithm to predict the microRNA-disease associations. Importantly, our method can be used to predict microRNAs (diseases) associated with the diseases (microRNAs) without the known associated microRNAs (diseases). The predictive performance of our proposed approach was evaluated and verified by the internal cross-validations and external independent validations based on standard association datasets. The results demonstrate that our proposed method achieves the impressive performance for predicting the microRNA-disease association with the Area Under receiver operation characteristic Curve (AUC), 86.93%, which is indeed outperform the previous prediction methods. Particularly, we observed that the ensemble-based method by integrating the predictions of multiple algorithms can give more reliable and robust prediction than the single algorithm, with the AUC score improved to 92.26%. We applied our combinatorial prioritization algorithm to lung neoplasms and breast neoplasms, and revealed their top 30 microRNA candidates, which are in consistent with the published literatures and databases. PMID:28317855

  19. Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm

    NASA Astrophysics Data System (ADS)

    Yu, Hua; Chen, Xiaojun; Lu, Lu

    2017-03-01

    Identification of the associations between microRNA molecules and human diseases from large-scale heterogeneous biological data is an important step for understanding the pathogenesis of diseases in microRNA level. However, experimental verification of microRNA-disease associations is expensive and time-consuming. To overcome the drawbacks of conventional experimental methods, we presented a combinatorial prioritization algorithm to predict the microRNA-disease associations. Importantly, our method can be used to predict microRNAs (diseases) associated with the diseases (microRNAs) without the known associated microRNAs (diseases). The predictive performance of our proposed approach was evaluated and verified by the internal cross-validations and external independent validations based on standard association datasets. The results demonstrate that our proposed method achieves the impressive performance for predicting the microRNA-disease association with the Area Under receiver operation characteristic Curve (AUC), 86.93%, which is indeed outperform the previous prediction methods. Particularly, we observed that the ensemble-based method by integrating the predictions of multiple algorithms can give more reliable and robust prediction than the single algorithm, with the AUC score improved to 92.26%. We applied our combinatorial prioritization algorithm to lung neoplasms and breast neoplasms, and revealed their top 30 microRNA candidates, which are in consistent with the published literatures and databases.

  20. Predicting Future Years of Life, Health, and Functional Ability

    PubMed Central

    Diehr, Paula; Diehr, Michael; Arnold, Alice; Yee, Laura M.; Odden, Michelle C.; Hirsch, Calvin H; Thielke, Stephen; Psaty, Bruce M.; Johnson, W. Craig; Kizer, MD, Jorge R.; Newman, Anne

    2015-01-01

    Objective: To create personalized estimates of future health and ability status for older adults. Method: Data came from the Cardiovascular Health Study (CHS), a large longitudinal study. Outcomes included years of life, years of healthy life (based on self-rated health), years of able life (based on activities of daily living), and years of healthy and able life. We developed regression estimates using the demographic and health characteristics that best predicted the four outcomes. Internal and external validity were assessed. Results: A prediction equation based on 11 variables accounted for about 40% of the variability for each outcome. Internal validity was excellent, and external validity was satisfactory. The resulting CHS Healthy Life Calculator (CHSHLC) is available at http://healthylifecalculator.org. Conclusion: CHSHLC provides a well-documented estimate of future years of healthy and able life for older adults, who may use it in planning for the future. PMID:28138467

  1. Novelty seeking is related to individual risk preference and brain activation associated with risk prediction during decision making

    PubMed Central

    Wang, Ying; Liu, Ying; Yang, Lizhuang; Gu, Feng; Li, Xiaoming; Zha, Rujing; Wei, Zhengde; Pei, Yakun; Zhang, Peng; Zhou, Yifeng; Zhang, Xiaochu

    2015-01-01

    Novelty seeking (NS) is a personality trait reflecting excitement in response to novel stimuli. High NS is usually a predictor of risky behaviour such as drug abuse. However, the relationships between NS and risk-related cognitive processes, including individual risk preference and the brain activation associated with risk prediction, remain elusive. In this fMRI study, participants completed the Tridimensional Personality Questionnaire to measure NS and performed a probabilistic decision making task. Using a mathematical model, we estimated individual risk preference. Brain regions associated with risk prediction were determined via fMRI. The NS score showed a positive correlation with risk preference and a negative correlation with the activation elicited by risk prediction in the right posterior insula (r-PI), left anterior insula (l-AI), right striatum (r-striatum) and supplementary motor area (SMA). Within these brain regions, only the activation associated with risk prediction in the r-PI showed a correlation with NS after controlling for the effect of risk preference. Resting-state functional connectivity between the r-PI and r-striatum/l-AI was negatively correlated with NS. Our results suggest that high NS may be associated with less aversion to risk and that the r-PI plays an important role in relating risk prediction to NS. PMID:26065910

  2. Intrinsic functional connectivity predicts individual differences in distractibility.

    PubMed

    Poole, Victoria N; Robinson, Meghan E; Singleton, Omar; DeGutis, Joseph; Milberg, William P; McGlinchey, Regina E; Salat, David H; Esterman, Michael

    2016-06-01

    Distractor suppression, the ability to filter and ignore task-irrelevant information, is critical for efficient task performance. While successful distractor suppression relies on a balance of activity in neural networks responsible for attention maintenance (dorsal attention network; DAN), reorientation (ventral attention network; VAN), and internal thought (default mode network, DMN), the degree to which intrinsic connectivity within and between these networks contributes to individual differences in distractor suppression ability is not well-characterized. For the purposes of understanding these interactions, the current study collected resting-state fMRI data from 32 Veterans and, several months later (7±5 months apart), performance on the additional singleton paradigm, a measure of distractor suppression. Using multivariate support vector regression models composed of resting state connectivity between regions of the DAN, VAN, and DMN, and a leave-one-subject-out cross-validation procedure, we were able to predict an individual's task performance, yielding a significant correlation between the actual and predicted distractor suppression (r=0.48, p=0.0053). Network-level analyses revealed that greater within-network DMN connectivity was predictive of better distractor suppression, while greater connectivity between the DMN and attention networks was predictive of poorer distractor suppression. The strongest connection hubs were determined to be the right frontal eye field and temporoparietal junction of the DAN and VAN, respectively, and medial (ventromedial prefrontal and posterior cingulate cortices) and bilateral prefrontal regions of the DMN. These results are amongst a small but growing number of studies demonstrating that resting state connectivity is related to stable individual differences in cognitive ability, and suggest that greater integrity and independence of the DMN is related to better attentional ability.

  3. Predicting functional capacity during treadmill testing independent of exercise protocol.

    PubMed

    Foster, C; Crowe, A J; Daines, E; Dumit, M; Green, M A; Lettau, S; Thompson, N N; Weymier, J

    1996-06-01

    Clinically useful estimates of VO2max from treadmill tests (GXT) may be made using protocol-specific equations. In many cases, GXT may proceed more effectively if the clinician is free to adjust speed and grade independent of a specific protocol. We sought to determine whether VO2max could be predicted from the estimated steady-state VO2 of the terminal exercise stage. Seventy clinically stable individuals performed GXT with direct measurement of VO2. Exercise was incremented each minute to optimize clinical examination. Measured VO2max was compared to the estimated steady-state VO2 of the terminal stage based on ACSM equations. Equations for walking or running were used based on the patient's observed method of ambulation. The measured VO2max was always less than the ACSM estimate, with a regular relationship between measured and estimated VO2max. No handrail support: VO2max = 0.869.ACSM -0.07; R2 = 0.955, SEE = 4.8 ml.min-1.kg-1 (N = 30). With handrail support: VO2max = 0.694.ACSM + 3.33; R2 = 0.833, SEE = 4.4 ml.min-1.kg-1 (N = 40). The equations were cross-validated with 20 patients. The correlation between predicted and observed values was r = 0.98 and 0.97 without and with handrail support, respectively. The mean absolute prediction error (3.1 and 4.1 ml.min-1.kg-1) were similar to protocol-specific equations. We conclude that VO2max can be predicted independent of treadmill protocol with approximately the same error as protocol-specific equations.

  4. Numerical prediction of turbulent oscillating flow and associated heat transfer

    NASA Technical Reports Server (NTRS)

    Koehler, W. J.; Patankar, S. V.; Ibele, W. E.

    1991-01-01

    A crucial point for further development of engines is the optimization of its heat exchangers which operate under oscillatory flow conditions. It has been found that the most important thermodynamic uncertainties in the Stirling engine designs for space power are in the heat transfer between gas and metal in all engine components and in the pressure drop across the heat exchanger components. So far, performance codes cannot predict the power output of a Stirling engine reasonably enough if used for a wide variety of engines. Thus, there is a strong need for better performance codes. However, a performance code is not concerned with the details of the flow. This information must be provided externally. While analytical relationships exist for laminar oscillating flow, there has been hardly any information about transitional and turbulent oscillating flow, which could be introduced into the performance codes. In 1986, a survey by Seume and Simon revealed that most Stirling engine heat exchangers operate in the transitional and turbulent regime. Consequently, research has since focused on the unresolved issue of transitional and turbulent oscillating flow and heat transfer. Since 1988, the University of Minnesota oscillating flow facility has obtained experimental data about transitional and turbulent oscillating flow. However, since the experiments in this field are extremely difficult, lengthy, and expensive, it is advantageous to numerically simulate the flow and heat transfer accurately from first principles. Work done at the University of Minnesota on the development of such a numerical simulation is summarized.

  5. Predicting supernova associated to gamma-ray burst 130427a

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Ruffini, R.; Kovacevic, M.; Bianco, C. L.; Enderli, M.; Muccino, M.; Penacchioni, A. V.; Pisani, G. B.; Rueda, J. A.

    2015-07-01

    Binary systems constituted by a neutron star and a massive star are not rare in the universe. The Induced Gravitational Gamma-ray Burst (IGC) paradigm interprets Gamma-ray bursts as the outcome of a neutron star that collapses into a black hole due to the accretion of the ejecta coming from its companion massive star that underwent a supernova event. GRB 130427A is one of the most luminous GRBs ever observed, of which isotropic energy exceeds 1054 erg. And it is within one of the few GRBs obtained optical, X-ray and GeV spectra simultaneously for hundreds of seconds, which provides an unique opportunity so far to understand the multi-wavelength observation within the IGC paradigm, our data analysis found low Lorentz factor blackbody emission in the Episode 3 and its X-ray light curve overlaps typical IGC Golden Sample, which comply to the IGC mechanisms. We consider these findings as clues of GRB 130427A belonging to the IGC GRBs. We predicted on GCN the emergence of a supernova on May 2, 2013, which was later successfully detected on May 13, 2013.

  6. Regulation and Function of Cytokines that Predict Prostate Cancer Metastasis

    DTIC Science & Technology

    2011-08-01

    Professor, Medicine Uro -Oncology Research Program Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Center 8750 Beverly Blvd...Department of Medicine Uro -Oncology Research Program Leland Chung, Director Neil A. Bhowmick, Ph.D. Associate Professor of Medicine

  7. Pupil diameter tracks changes in control state predicted by the adaptive gain theory of locus coeruleus function.

    PubMed

    Gilzenrat, Mark S; Nieuwenhuis, Sander; Jepma, Marieke; Cohen, Jonathan D

    2010-05-01

    An important dimension of cognitive control is the adaptive regulation of the balance between exploitation (pursuing known sources of reward) and exploration (seeking new ones) in response to changes in task utility. Recent studies have suggested that the locus coeruleus-norepinephrine system may play an important role in this function and that pupil diameter can be used to index locus coeruleus activity. On the basis of this, we reasoned that pupil diameter may correlate closely with control state and associated changes in behavior. Specifically, we predicted that increases in baseline pupil diameter would be associated with decreases in task utility and disengagement from the task (exploration), whereas reduced baseline diameter (but increases in task-evoked dilations) would be associated with task engagement (exploitation). Findings in three experiments were consistent with these predictions, suggesting that pupillometry may be useful as an index of both control state and, indirectly, locus coeruleus function.

  8. Functional dynamics of hippocampal glutamate during associative learning assessed with in vivo (1)H functional magnetic resonance spectroscopy.

    PubMed

    Stanley, Jeffrey A; Burgess, Ashley; Khatib, Dalal; Ramaseshan, Karthik; Arshad, Muzamil; Wu, Helen; Diwadkar, Vaibhav A

    2017-03-29

    fMRI has provided vibrant characterization of regional and network responses associated with associative learning and memory; however, their relationship to functional neurochemistry is unclear. Here, we introduce a novel application of in vivo proton functional magnetic resonance spectroscopy ((1)H fMRS) to investigate the dynamics of hippocampal glutamate during paired-associated learning and memory in healthy young adults. We show that the temporal dynamics of glutamate differed significantly during processes of memory consolidation and retrieval. Moreover, learning proficiency was predictive of the temporal dynamics of glutamate such that fast learners were characterized by a significant increase in glutamate levels early in learning, whereas this increase was only observed later in slow learners. The observed functional dynamics of glutamate provides a novel in vivo marker of brain function. Previously demonstrated N-methyl-D-aspartate (NMDA) receptor mediated synaptic plasticity during associative memory formation may be expressed in glutamate dynamics, which the novel application of (1)H MRS is sensitive to. The novel application of (1)H fMRS can provide highly innovative vistas for characterizing brain function in vivo, with significant implications for studying glutamatergic neurotransmission in health and disorders such as schizophrenia.

  9. Disease Prediction based on Functional Connectomes using a Scalable and Spatially-Informed Support Vector Machine

    PubMed Central

    Watanabe, Takanori; Kessler, Daniel; Scott, Clayton; Angstadt, Michael; Sripada, Chandra

    2014-01-01

    Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D “connectome space,” offering an additional layer of interpretability that could provide new insights about various disease processes. PMID:24704268

  10. Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine.

    PubMed

    Watanabe, Takanori; Kessler, Daniel; Scott, Clayton; Angstadt, Michael; Sripada, Chandra

    2014-08-01

    Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to a strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D "connectome space," offering an additional layer of interpretability that could provide new insights about various disease processes.

  11. Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF

    PubMed Central

    Ashley, Shanna L.; Xia, Meng; Murray, Susan; O’Dwyer, David N.; Grant, Ethan; White, Eric S.; Flaherty, Kevin R.; Martinez, Fernando J.

    2016-01-01

    Rationale Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF) would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF. Methods Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer) array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC) curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC) when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold. Results A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2), cathepsin-S (Cath-S), legumain (LGMN) and soluble vascular endothelial growth factor receptor 2 (VEGFsR2), but low levels of inducible T cell costimulator (ICOS) or trypsin 3 (TRY3)] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2) was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2–126.7, P = 0.006). Conclusion This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression. PMID:27490795

  12. Do Executive Function Deficits Predict Later Substance Use Disorders Among Adolescents and Young Adults?

    PubMed Central

    Wilens, Timothy E.; Martelon, MaryKate; Fried, Ronna; Petty, Carter; Bateman, Clancey; Biederman, Joseph

    2010-01-01

    Objective There is increasing interest regarding the risk and overlap of executive function deficits (EFDs) in stable cigarette smoking and substance use disorders (SUD). Therefore, we examined whether earlier EFD was a risk factor for subsequent cigarette smoking and SUD and further explored the relationship between EFD and SUD. Method We assessed 435 subjects at the five-year follow-up (232 cases of ADHD; mean age ± SD: 15.4 ± 3.43 and 203 controls: 16.3 ± 3.42 years) and again four to five years later as part of a prospective family study of ADHD youth. Individuals were assessed by structured psychiatric interview for psychopathology and SUD. EFD was categorically defined in an individual that had at least 2 out of 6 abnormal neuropsychological tests of executive functioning. Results At the final follow-up period, ADHD was found to be a significant predictor of stable cigarette smoking (p<0.01) and SUD into late adolescence and young adult years (p<0.01). However, EFDs were not associated with an increase in subsequent substance use outcomes. New onset stable cigarette smoking, but not SUD, was associated with subsequent EFD (p<0.01). Conclusions Our results do not support the hypothesis that EFDs predicts later stable cigarette smoking or SUD in children with ADHD growing up. However, stable cigarette smoking is associated with subsequent EFD. PMID:21241951

  13. Predictability Effects on Durations of Content and Function Words in Conversational English

    SciTech Connect

    Bell, Alan; Brenier, Jason; Gregory, Michelle L.; girand, cynthia; Jurafsky, Daniel

    2009-01-01

    Content and function word duration are affected differently by their frequency and predictability. Regression analyses of conversational speech show that content words are shorter when they are more frequent, but function words are not. Repeated content words are shorter, but function words are not. Furthermore, function words have shorter pronunciations, after controlling for frequency and predictability. both content and function words are strongly affected by predictability from the word following them, and only very frequent function words show sensitivity to predictability from the preceding word. The results support the view that content and function words are accessed by different production mechanisms. We argue that words’ form differences due to frequency or repetition stem from their faster or slower lexical access, mediated by a general mechanism that coordinates the pace of higher-level planning and the execution of the articulatory plan.

  14. Computational prediction of functional abortive RNA in E. coli.

    PubMed

    Marcus, Jeremy I; Hassoun, Soha; Nair, Nikhil U

    2017-03-24

    Failure by RNA polymerase to break contacts with promoter DNA results in release of bound RNA and re-initiation of transcription. These abortive RNAs were assumed to be non-functional but have recently been shown to affect termination in bacteriophage T7. Little is known about the functional role of these RNA in other genetic models. Using a computational approach, we investigated whether abortive RNA could exert function in E. coli. Fragments generated from 3780 transcription units were used as query sequences within their respective transcription units to search for possible binding sites. Sites that fell within known regulatory features were then ranked based upon the free energy of hybridization to the abortive. We further hypothesize about mechanisms of regulatory action for a select number of likely matches. Future experimental validation of these putative abortive-mRNA pairs may confirm our findings and promote exploration of functional abortive RNAs (faRNAs) in natural and synthetic systems.

  15. Temperamental exuberance and executive function predict propensity for risk-taking in childhood

    PubMed Central

    Lahat, Ayelet; Degnan, Kathryn A.; White, Lauren K.; McDermott, Jennifer Martin; Henderson, Heather A.; Lejuez, C. W.; Fox, Nathan A.

    2015-01-01

    The present study takes a multilevel approach to examine developmental trajectories in risk-taking propensity. We examined the moderating role of specific executive function components, attention shifting and inhibitory control, on the link between exuberant temperament in infancy and propensity for risk-taking in childhood. Risk-taking was assessed using a task previously associated with sensation seeking and antisocial behaviors. Two hundred and ninety one infants were brought into the lab and behaviors reflecting exuberance were observed at 4, 9, 24, and 36 months of age. Executive function was assessed at 48 months of age. Risk-taking propensity was measured when children were 60 months of age. The results indicate that exuberance and attention shifting, but not inhibitory control, significantly interact to predict propensity for risk-taking. Exuberance was positively associated with risk-taking propensity among children relatively low in attention shifting but unrelated for children high in attention shifting. These findings illustrate the multifinality of developmental outcomes for temperamentally exuberant young children and point to the distinct regulatory influences of different executive functions for children of differing temperaments. Attention shifting likely affords a child the ability to consider both positive and negative consequences, and moderates the relation between early exuberance and risk-taking propensity. PMID:22781858

  16. Link functions in multi-locus genetic models: implications for testing, prediction, and interpretation.

    PubMed

    Clayton, David

    2012-05-01

    "Complex" diseases are, by definition, influenced by multiple causes, both genetic and environmental, and statistical work on the joint action of multiple risk factors has, for more than 40 years, been dominated by the generalized linear model (GLM). In genetics, models for dichotomous traits have traditionally been approached via the model of an underlying, normally distributed, liability. This corresponds to the GLM with binomial errors and a probit link function. Elsewhere in epidemiology, however, the logistic regression model, a GLM with logit link function, has been the tool of choice, largely because of its convenient properties in case-control studies. The choice of link function has usually been dictated by mathematical convenience, but it has some important implications in (a) the choice of association test statistic in the presence of existing strong risk factors, (b) the ability to predict disease from genotype given its heritability, and (c) the definition, and interpretation of epistasis (or epistacy). These issues are reviewed, and a new association test proposed.

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

    PubMed Central

    Ursache, Alexandra; Raver, C. Cybele

    2015-01-01

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

  18. Iowa Gambling Task Performance and Executive Function Predict Low-income Urban Preadolescents' Risky Behaviors.

    PubMed

    Ursache, Alexandra; Raver, C Cybele

    2015-06-01

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

  19. Aerobic exercise interacts with neurotrophic factors to predict cognitive functioning in adolescents.

    PubMed

    Lee, Tatia M C; Wong, Mark Lawrence; Lau, Benson Wui-Man; Lee, Jada Chia-Di; Yau, Suk-Yu; So, Kwok-Fai

    2014-01-01

    Recent findings have suggested that aerobic exercise may have a positive effect on brain functioning, in addition to its well-recognized beneficial effects on human physiology. This study confirmed the cognitive effects of aerobic exercise on the human brain. It also examined the relationships between exercise and the serum levels of neurotrophic factors (BDNF, IGI-1, and VEGF). A total of 91 healthy teens who exercised regularly participated in this study. A between-group design was adopted to compare cognitive functioning subserved by the frontal and temporal brain regions and the serum levels of neurotrophic factors between 45 regular exercisers and 46 matched controls. The exercisers performed significantly better than the controls on the frontal and temporal functioning parameters measured. This beneficial cognitive effect was region-specific because no such positive cognitive effect on task-tapping occipital functioning was observed. With respect to the serum levels of the neurotrophic factors, a negative correlation between neurotrophic factors (BDNF and VEGF) with frontal and medial-temporal lobe function was revealed. Furthermore, the levels of BDNF and VEGF interacted with exercise status in predicting frontal and temporal lobe function. This is the first report of the interaction effects of exercise and neurotrophic factors on cognitive functioning. Herein, we report preliminary evidence of the beneficial effects of regular aerobic exercise in improving cognitive functions in teens. These beneficial effects are region-specific and are associated with the serum levels of neurotrophic factors. Our findings lay the path for future studies looking at ways to translate these beneficial effects to therapeutic strategies for adolescents.

  20. Deterioration in Renal Function Is Associated With Increased Arterial Stiffness

    PubMed Central

    2014-01-01

    BACKGROUND Higher levels of baseline pulse wave velocity (PWV) have been associated with longitudinal decline in renal function in patients with kidney disease. We examined longitudinal decline in renal function in relation to levels of PWV. We hypothesized that longitudinal decline in renal function in a community-based, nonclinic sample would be associated with higher levels of PWV. METHODS We conducted a 4–5 year longitudinal study with 482 community-living individuals free from acute stroke, dementia, and end-stage renal disease (mean age = 60.9 years; 59% women; 93.2% white; 10% with diabetes mellitus; mean estimated glomerular filtration rate (eGFR) = 79.2ml/min/1.73 m2). Multiple linear regression analyses were used to examine the association between changes in renal function (eGFR and serum creatinine) from baseline to follow-up and PWV levels at follow-up, the outcome measure. Regression coefficients were adjusted for age, sex, education, race/ethnicity, weight, activity level, mean arterial pressure, treatment of hypertension, and cardiovascular risk factors. RESULTS With adjustment for covariables, decline in renal function was associated with higher levels of PWV over a mean follow-up of 4.68 years. CONCLUSIONS Decline in renal functioning from baseline levels measured 4–5 years before measurement of PWV is related to higher levels of PWV in a community sample. PMID:24080989

  1. Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage

    NASA Astrophysics Data System (ADS)

    Bogachev, Mikhail I.; Kayumov, Airat R.; Markelov, Oleg A.; Bunde, Armin

    2016-02-01

    Structural, localization and functional properties of unknown proteins are often being predicted from their primary polypeptide chains using sequence alignment with already characterized proteins and consequent molecular modeling. Here we suggest an approach to predict various structural and structure-associated properties of proteins directly from the mass distributions of their proteolytic cleavage fragments. For amino-acid-specific cleavages, the distributions of fragment masses are determined by the distributions of inter-amino-acid intervals in the protein, that in turn apparently reflect its structural and structure-related features. Large-scale computer simulations revealed that for transmembrane proteins, either α-helical or β -barrel secondary structure could be predicted with about 90% accuracy after thermolysin cleavage. Moreover, 3/4 intrinsically disordered proteins could be correctly distinguished from proteins with fixed three-dimensional structure belonging to all four SCOP structural classes by combining 3–4 different cleavages. Additionally, in some cases the protein cellular localization (cytosolic or membrane-associated) and its host organism (Firmicute or Proteobacteria) could be predicted with around 80% accuracy. In contrast to cytosolic proteins, for membrane-associated proteins exhibiting specific structural conformations, their monotopic or transmembrane localization and functional group (ATP-binding, transporters, sensors and so on) could be also predicted with high accuracy and particular robustness against missing cleavages.

  2. Statistical prediction of protein structural, localization and functional properties by the analysis of its fragment mass distributions after proteolytic cleavage

    PubMed Central

    Bogachev, Mikhail I.; Kayumov, Airat R.; Markelov, Oleg A.; Bunde, Armin

    2016-01-01

    Structural, localization and functional properties of unknown proteins are often being predicted from their primary polypeptide chains using sequence alignment with already characterized proteins and consequent molecular modeling. Here we suggest an approach to predict various structural and structure-associated properties of proteins directly from the mass distributions of their proteolytic cleavage fragments. For amino-acid-specific cleavages, the distributions of fragment masses are determined by the distributions of inter-amino-acid intervals in the protein, that in turn apparently reflect its structural and structure-related features. Large-scale computer simulations revealed that for transmembrane proteins, either α-helical or β -barrel secondary structure could be predicted with about 90% accuracy after thermolysin cleavage. Moreover, 3/4 intrinsically disordered proteins could be correctly distinguished from proteins with fixed three-dimensional structure belonging to all four SCOP structural classes by combining 3–4 different cleavages. Additionally, in some cases the protein cellular localization (cytosolic or membrane-associated) and its host organism (Firmicute or Proteobacteria) could be predicted with around 80% accuracy. In contrast to cytosolic proteins, for membrane-associated proteins exhibiting specific structural conformations, their monotopic or transmembrane localization and functional group (ATP-binding, transporters, sensors and so on) could be also predicted with high accuracy and particular robustness against missing cleavages. PMID:26924271

  3. Translating Lung Function Genome-Wide Association Study (GWAS) Findings: New Insights for Lung Biology.

    PubMed

    Kheirallah, A K; Miller, S; Hall, I P; Sayers, I

    2016-01-01

    Chronic respiratory diseases are a major cause of worldwide mortality and morbidity. Although hereditary severe deficiency of α1 antitrypsin (A1AD) has been established to cause emphysema, A1AD accounts for only ∼ 1% of Chronic Obstructive Pulmonary Disease (COPD) cases. Genome-wide association studies (GWAS) have been successful at detecting multiple loci harboring variants predicting the variation in lung function measures and risk of COPD. However, GWAS are incapable of distinguishing causal from noncausal variants. Several approaches can be used for functional translation of genetic findings. These approaches have the scope to identify underlying alleles and pathways that are important in lung function and COPD. Computational methods aim at effective functional variant prediction by combining experimentally generated regulatory information with associated region of the human genome. Classically, GWAS association follow-up concentrated on manipulation of a single gene. However association data has identified genetic variants in >50 loci predicting disease risk or lung function. Therefore there is a clear precedent for experiments that interrogate multiple candidate genes in parallel, which is now possible with genome editing technology. Gene expression profiling can be used for effective discovery of biological pathways underpinning gene function. This information may be used for informed decisions about cellular assays post genetic manipulation. Investigating respiratory phenotypes in human lung tissue and specific gene knockout mice is a valuable in vivo approach that can complement in vitro work. Herein, we review state-of-the-art in silico, in vivo, and in vitro approaches that may be used to accelerate functional translation of genetic findings.

  4. Predictive model for delayed graft function based on easily available pre-renal transplant variables.

    PubMed

    Zaza, Gianluigi; Ferraro, Pietro Manuel; Tessari, Gianpaolo; Sandrini, Silvio; Scolari, Maria Piera; Capelli, Irene; Minetti, Enrico; Gesualdo, Loreto; Girolomoni, Giampiero; Gambaro, Giovanni; Lupo, Antonio; Boschiero, Luigino

    2015-03-01

    Identification of pre-transplant factors influencing delayed graft function (DGF) could have an important clinical impact. This could allow clinicians to early identify dialyzed chronic kidney disease (CKD) patients eligible for special transplant programs, preventive therapeutic strategies and specific post-transplant immunosuppressive treatments. To achieve these objectives, we retrospectively analyzed main demographic and clinical features, follow-up events and outcomes registered in a large dedicated dataset including 2,755 patients compiled collaboratively by four Italian renal/transplant units. The years of transplant ranged from 1984 to 2012. Statistical analysis clearly demonstrated that some recipients' characteristics at the time of transplantation (age and body weight) and dialysis-related variables (modality and duration) were significantly associated with DGF development (p ≤ 0.001). The area under the receiver-operating characteristic (ROC) curve of the final model based on the four identified variables predicting DGF was 0.63 (95 % CI 0.61, 0.65). Additionally, deciles of the score were significantly associated with the incidence of DGF (p value for trend <0.001). Therefore, in conclusion, in our study we identified a pre-operative predictive model for DGF, based on inexpensive and easily available variables, potentially useful in routine clinical practice in most of the Italian and European dialysis units.

  5. Nebulon: a system for the inference of functional relationships of gene products from the rearrangement of predicted operons

    PubMed Central

    Janga, Sarath Chandra; Collado-Vides, Julio; Moreno-Hagelsieb, Gabriel

    2005-01-01

    Since operons are unstable across Prokaryotes, it has been suggested that perhaps they re-combine in a conservative manner. Thus, genes belonging to a given operon in one genome might re-associate in other genomes revealing functional relationships among gene products. We developed a system to build networks of functional relationships of gene products based on their organization into operons in any available genome. The operon predictions are based on inter-genic distances. Our system can use different kinds of thresholds to accept a functional relationship, either related to the prediction of operons, or to the number of non-redundant genomes that support the associations. We also work by shells, meaning that we decide on the number of linking iterations to allow for the complementation of related gene sets. The method shows high reliability benchmarked against knowledge-bases of functional interactions. We also illustrate the use of Nebulon in finding new members of regulons, and of other functional groups of genes. Operon rearrangements produce thousands of high-quality new interactions per prokaryotic genome, and thousands of confirmations per genome to other predictions, making it another important tool for the inference of functional interactions from genomic context. PMID:15867197

  6. Property Predictions for Nitrate Salts with Nitroxy-Functionalized Cations

    DTIC Science & Technology

    2011-05-01

    unstable”* to be employed as rocket propellant ingredients (Dunn, 1952; Naoum and Ulrich , 1929; Medard, 1954; Urbanski, 1965). The EQBR and SERDP efforts...from models that combine the B3LYP hybrid functional ( Becke , 1993; Lee et al., 1988; Stephens et al., 1994; Vosko et al., 1980) with a 6-31+G(d,p), 6...1989, 122, 1963–1967. Becke , A. D. Density-Functional Thermochemistry. 3. The Role of Exact Exchange. Journal of Chemical Physics 1993, 98, 5648

  7. Predictive Effects of Lung function test on Postoperative Pneumonia in Squamous Esophageal Cancer.

    PubMed

    Wei, Ran; Dong, Wei; Shen, Hongchang; Ni, Yang; Zhang, Tiehong; Wang, Yibing; Du, Jiajun

    2016-03-23

    Pulmonary function tests had prospective implications for postoperative pneumonia, which occurred frequently after esophagectomy. Understanding factors that were associated with pulmonary infection may help in patient selection and postoperative management. We performed a retrospective review of 2 independent cohorts including 216 patients who underwent esophagectomy between November 2011 and May 2014, aiming at identifying predictors of primary pneumonia. Univariate analysis was used to identify potential covariates for the development of primary pneumonia. Adjustments for multiple comparisons were made using False Discovery Rate (FDR) (Holm-Bonferroni method). Multivariable logistic regression analysis was used to identify independent predictors and construct a regression model based on a training cohort (n = 166) and then the regression model was validated using an independent cohort (n = 50). It showed that low PEF (hazard ratio 0.97, P = 0.009) was independent risk factors for the development of primary pneumonia in multivariate analyses and had a predictive effect for primary pneumonia (AUC = 0.691 and 0.851 for training and validation data set, respectively). Therefore, PEF has clinical value in predicting postoperative pneumonia after esophagectomy and it may serve as an indicator of preoperative lung function training.

  8. Density functional theory for inhomogeneous associating chain fluids.

    PubMed

    Bryk, P; Sokołowski, S; Pizio, O

    2006-07-14

    We propose a nonlocal density functional theory for associating chain molecules. The chains are modeled as tangent spheres, which interact via Lennard-Jones (12,6) attractive interactions. A selected segment contains additional, short-ranged, highly directional interaction sites. The theory incorporates an accurate treatment of the chain molecules via the intramolecular potential formalism and should accurately describe systems with strongly varying external fields, e.g., attractive walls. Within our approach we investigate the structure of the liquid-vapor interface and capillary condensation of a simple model of associating chains with only one associating site placed on the first segment. In general, the properties of inhomogeneous associating chains depend on the association energy. Similar to the bulk systems we find the behavior of associating chains of a given length to be in between that for the nonassociating chains of the same length and that for the nonassociating chains twice as large.

  9. Predicting Adaptive Functioning of Mentally Retarded Persons in Community Settings.

    ERIC Educational Resources Information Center

    Hull, John T.; Thompson, Joy C.

    1980-01-01

    The impact of a variety of individual, residential, and community variables on adaptive functioning of 369 retarded persons (18 to 73 years old) was examined using a multiple regression analysis. Individual characteristics (especially IQ) accounted for 21 percent of the variance, while environmental variables, primarily those related to…

  10. Cognitive Function and Prediction of Dementia in Old Age.

    ERIC Educational Resources Information Center

    La Rue, Asenath; Jarvik, Lissy F.

    1987-01-01

    Examined longitudinal changes in cognitive functioning for aging twins. Found that those who were considered demented in old age had achieved lower test scores 20 years prior to diagnosis and experienced greater declines in vocabulary and forward digit span over time than those without dementia. Suggests that dementia may develop very slowly.…

  11. Variability in functional brain networks predicts expertise during action observation.

    PubMed

    Amoruso, Lucía; Ibáñez, Agustín; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; Sigman, Mariano; García, Adolfo M; Fraiman, Ricardo; Fraiman, Daniel

    2017-02-01

    Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research.

  12. Predicting verbal fluency using Word Reading: Implications for premorbid functioning.

    PubMed

    Davis, Andrew S; Finch, W Holmes; Drapeau, Christopher; Nogin, Margarita; E Moss, Lauren; Moore, Brittney

    2016-01-01

    The estimation of premorbid general intellectual functioning using word reading tests has a rich history of validation and is a common assessment practice for neuropsychologists. What is less well-researched is the approach used to estimate premorbid functioning of non-intellectual domains, such as executive functions, including verbal fluency. The current study evaluated this relationship with 41 adult college students who completed the Word Reading subtest of the Wechsler Individual Achievement Test-Second Edition (WIAT-II) and the Verbal Fluency test from the Delis-Kaplan Executive Function System (D-KEFS). Path analysis indicated that only Letter Fluency (a measure of phonemic fluency) was statistically significantly related to Word Reading and the relationship was somewhat weak. The relationship between Category Fluency (a measure of semantic fluency) and Category Switching (a measure of verbal fluency cognitive set-shifting) to Word Reading was nonsignificant. Participants also completed the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III), and as expected a strong relationship was found between Word Reading and the Verbal IQ (VIQ), Performance IQ (PIQ), and Full Scale Intelligence Quotient (FSIQ). Results of this study strongly suggest that caution be exercised when extrapolating an estimate of premorbid verbal fluency abilities from measures of word reading.

  13. PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.

    PubMed

    You, Zhu-Hong; Huang, Zhi-An; Zhu, Zexuan; Yan, Gui-Ying; Li, Zheng-Wei; Wen, Zhenkun; Chen, Xing

    2017-03-24

    In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases. Instead of only depending on expensive and time-consuming biological experiments, computational prediction models are effective by predicting potential miRNA-disease associations, prioritizing candidate miRNAs for the investigated diseases, and selecting those miRNAs with higher association probabilities for further experimental validation. In this study, Path-Based MiRNA-Disease Association (PBMDA) prediction model was proposed by integrating known human miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases. This model constructed a heterogeneous graph consisting of three interlinked sub-graphs and further adopted depth-first search algorithm to infer potential miRNA-disease associations. As a result, PBMDA achieved reliable performance in the frameworks of both local and global LOOCV (AUCs of 0.8341 and 0.9169, respectively) and 5-fold cross validation (average AUC of 0.9172). In the cases studies of three important human diseases, 88% (Esophageal Neoplasms), 88% (Kidney Neoplasms) and 90% (Colon Neoplasms) of top-50 predicted miRNAs have been manually confirmed by previous experimental reports from literatures. Through the comparison performance between PBMDA and other previous models in case studies, the reliable performance also demonstrates that PBMDA could serve as a powerful computational tool

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

    PubMed Central

    Han, Jie; Wang, Xiaona; Ye, Ping; Cao, Ruihua; Yang, Xu; Xiao, Wenkai; Zhang, Yun; Bai, Yongyi; Wu, Hongmei

    2016-01-01

    Objectives Despite growing evidence that arterial stiffness has important predictive value for cardiovascular disease in patients with advanced stages of chronic kidney disease, the predictive significance of arterial stiffness in individuals with mildly impaired renal function has not been established. The aim of this study was to evaluate the predictive value of arterial stiffness on cardiovascular disease in this specific population. Materials and methods We analyzed measurements of arterial stiffness (carotid–femoral pulse-wave velocity [cf-PWV]) and the incidence of major adverse cardiovascular events (MACEs) in 1,499 subjects from a 4.8-year longitudinal study. Results A multivariate Cox proportional-hazard regression analysis showed that in individuals with normal renal function (estimated glomerular filtration rate [eGFR] ≥90 mL/min/1.73 m2), the baseline cf-PWV was not associated with occurrence of MACEs (hazard ratio 1.398, 95% confidence interval 0.748–2.613; P=0.293). In individuals with mildly impaired renal function (eGFR <90 mL/min/1.73 m2), a higher baseline cf-PWV level was associated with a higher risk of MACEs (hazard ratio 2.334, 95% confidence interval 1.082–5.036; P=0.031). Conclusion Arterial stiffness is a moderate and independent predictive factor for MACEs in individuals with mildly impaired renal function (eGFR <90 mL/min/1.73 m2). PMID:27621605

  15. Ability of Lower-Extremity Injury Severity Scores to Predict Functional Outcome After Limb Salvage

    PubMed Central

    Ly, Thuan V.; Travison, Thomas G.; Castillo, Renan C.; Bosse, Michael J.; MacKenzie, Ellen J.

    2008-01-01

    Background: Lower-extremity injury severity scoring systems were developed to assist surgeons in decision-making regarding whether to amputate or perform limb salvage after high-energy trauma to the lower extremity. These scoring systems have been shown to not be good predictors of limb amputation or salvage. This study was performed to evaluate the clinical utility of the five commonly used lower-extremity injury severity scoring systems as predictors of final functional outcome. Methods: We analyzed data from a cohort of patients who participated in a multicenter prospective study of clinical and functional outcomes after high-energy lower-extremity trauma. Injury severity was assessed with use of the Mangled Extremity Severity Score; the Limb Salvage Index; the Predictive Salvage Index; the Nerve Injury, Ischemia, Soft-Tissue Injury, Skeletal Injury, Shock, and Age of Patient Score; and the Hannover Fracture Scale-98. Functional outcomes were measured with use of the physical and psychosocial domains of the Sickness Impact Profile at both six months and two years following hospital discharge. Four hundred and seven subjects for whom the reconstruction regimen was considered successful at six months were included in the analysis. We used partial correlation statistics and multiple linear regression models to quantify the association between injury severity scores and Sickness Impact Profile outcomes with the subjects' ages held constant. Results: The mean age of the patients was thirty-six years (interquartile range, twenty-six to forty-four years); 75.2% were male and 24.8% were female. The median Sickness Impact Profile scores were 15.2 and 6.0 points at six and twenty-four months, respectively. The analysis showed that none of the scoring systems were predictive of the Sickness Impact Profile outcomes at six or twenty-four months to any reasonable degree. Likewise, none were predictive of patient recovery between six and twenty-four months postoperatively as

  16. Prediction of synergistic transcription factors by function conservation

    PubMed Central

    Hu, Zihua; Hu, Boyu; Collins, James F

    2007-01-01

    Background Previous methods employed for the identification of synergistic transcription factors (TFs) are based on either TF enrichment from co-regulated genes or phylogenetic footprinting. Despite the success of these methods, both have limitations. Results We propose a new strategy to identify synergistic TFs by function conservation. Rather than aligning the regulatory sequences from orthologous genes and then identifying conserved TF binding sites (TFBSs) in the alignment, we developed computational approaches to implement the novel strategy. These methods include combinatorial TFBS enrichment utilizing distance constraints followed by enrichment of overlapping orthologous genes from human and mouse, whose regulatory sequences contain the enriched TFBS combinations. Subsequently, integration of function conservation from both TFBS and overlapping orthologous genes was achieved by correlation analyses. These techniques have been used for genome-wide promoter analyses, which have led to the identification of 51 homotypic TF combinations; the validity of these approaches has been exemplified by both known TF-TF interactions and function coherence analyses. We further provide computational evidence that our novel methods were able to identify synergistic TFs to a much greater extent than phylogenetic footprinting. Conclusion Function conservation based on the concordance of combinatorial TFBS enrichment along with enrichment of overlapping orthologous genes has been proven to be a successful means for the identification of synergistic TFs. This approach avoids the limitations of phylogenetic footprinting as it does not depend upon sequence alignment. It utilizes existing gene annotation data, such as those available in GO, thus providing an alternative method for functional TF discovery and annotation. PMID:18053230

  17. Pre-transplant Evaluation of Donor Urinary Biomarkers can Predict Reduced Graft Function After Deceased Donor Kidney Transplantation

    PubMed Central

    Koo, Tai Yeon; Jeong, Jong Cheol; Lee, Yonggu; Ko, Kwang-Pil; Lee, Kyoung-Bun; Lee, Sik; Park, Suk Joo; Park, Jae Berm; Han, Miyeon; Lim, Hye Jin; Ahn, Curie; Yang, Jaeseok

    2016-01-01

    Abstract Several recipient biomarkers are reported to predict graft dysfunction, but these are not useful in decision making for the acceptance or allocation of deceased donor kidneys; thus, it is necessary to develop donor biomarkers predictive of graft dysfunction. To address this issue, we prospectively enrolled 94 deceased donors and their 109 recipients who underwent transplantation between 2010 and 2013 at 4 Korean transplantation centers. We investigated the predictive values of donor urinary neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and L-type fatty acid binding protein (L-FABP) for reduced graft function (RGF). We also developed a prediction model of RGF using these donor biomarkers. RGF was defined as delayed or slow graft function. Multiple logistic regression analysis was used to generate a prediction model, which was internally validated using a bootstrapping method. Multiple linear regression analysis was used to assess the association of biomarkers with 1-year graft function. Notably, donor urinary NGAL levels were associated with donor AKI (P = 0.014), and donor urinary NGAL and L-FABP were predictive for RGF, with area under the receiver-operating characteristic curves (AUROC) of 0.758 and 0.704 for NGAL and L-FABP, respectively. The best-fit model including donor urinary NGAL, L-FABP, and serum creatinine conveyed a better predictive value for RGF than donor serum creatinine alone (P = 0.02). In addition, we generated a scoring method to predict RGF based on donor urinary NGAL, L-FABP, and serum creatinine levels. Diagnostic performance of the RGF prediction score (AUROC 0.808) was significantly better than that of the DGF calculator (AUROC 0.627) and the kidney donor profile index (AUROC 0.606). Donor urinary L-FABP levels were also predictive of 1-year graft function (P = 0.005). Collectively, these findings suggest donor urinary NGAL and L-FABP to be useful biomarkers for RGF, and support

  18. Phytoplankton traits predict ecosystem function in a global set of lakes.

    PubMed

    Zwart, Jacob A; Solomon, Christopher T; Jones, Stuart E

    2015-08-01

    Predicting ecosystem function from environmental conditions is a central goal of ecosystem ecology. However, many traditional ecosystem models are tailored for specific regions or ecosystem types, requiring several regional models to predict the same function. Alternatively, trait-based approaches have been effectively used to predict community structure in both terrestrial and aquatic environments and ecosystem function in a limited number of terrestrial examples. Here, we test the efficacy of a trait-based model in predicting gross primary production (GPP) in lake ecosystems. We incorporated data from >1000 United States lakes along with laboratory-generated phytoplankton trait data to build a trait-based model of GPP and then validated the model with GPP observations from a separate set of globally distributed lakes. The trait-based model performed as well as or outperformed two ecosystem models both spatially and temporally, demonstrating the efficacy of trait-based models for predicting ecosystem function over a range of environmental conditions.

  19. Genomic islands predict functional adaptation in marine actinobacteria

    SciTech Connect

    Penn, Kevin; Jenkins, Caroline; Nett, Markus; Udwary, Daniel; Gontang, Erin; McGlinchey, Ryan; Foster, Brian; Lapidus, Alla; Podell, Sheila; Allen, Eric; Moore, Bradley; Jensen, Paul

    2009-04-01

    Linking functional traits to bacterial phylogeny remains a fundamental but elusive goal of microbial ecology 1. Without this information, it becomes impossible to resolve meaningful units of diversity and the mechanisms by which bacteria interact with each other and adapt to environmental change. Ecological adaptations among bacterial populations have been linked to genomic islands, strain-specific regions of DNA that house functionally adaptive traits 2. In the case of environmental bacteria, these traits are largely inferred from bioinformatic or gene expression analyses 2, thus leaving few examples in which the functions of island genes have been experimentally characterized. Here we report the complete genome sequences of Salinispora tropica and S. arenicola, the first cultured, obligate marine Actinobacteria 3. These two species inhabit benthic marine environments and dedicate 8-10percent of their genomes to the biosynthesis of secondary metabolites. Despite a close phylogenetic relationship, 25 of 37 secondary metabolic pathways are species-specific and located within 21 genomic islands, thus providing new evidence linking secondary metabolism to ecological adaptation. Species-specific differences are also observed in CRISPR sequences, suggesting that variations in phage immunity provide fitness advantages that contribute to the cosmopolitan distribution of S. arenicola 4. The two Salinispora genomes have evolved by complex processes that include the duplication and acquisition of secondary metabolite genes, the products of which provide immediate opportunities for molecular diversification and ecological adaptation. Evidence that secondary metabolic pathways are exchanged by Horizontal Gene Transfer (HGT) yet are fixed among globally distributed populations 5 supports a functional role for their products and suggests that pathway acquisition represents a previously unrecognized force driving bacterial diversification

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

    PubMed

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

    2010-08-01

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

  1. GENETIC ASSOCIATION BETWEEN HUMAN CHITINASES AND LUNG FUNCTION IN COPD

    PubMed Central

    Aminuddin, F.; Akhabir, L.; Stefanowicz, D.; Paré, P.D.; Connett, J.E.; Anthonisen, N.R.; Fahy, J.V.; Seibold, M.A.; Burchard, E.G.; Eng, C.; Gulsvik, A.; Bakke, P.; Cho, M. H.; Litonjua, A.; Lomas, D.A.; Anderson, W. H.; Beaty, T.H.; Crapo, J.D.; Silverman, E.K.; Sandford, A.J.

    2013-01-01

    Two primary chitinases have been identified in humans – acid mammalian chitinase (AMCase) and chitotriosidase (CHIT1). Mammalian chitinases have been observed to affect the host’s immune response. The aim of this study was to test for association between genetic variation in the chitinases and phenotypes related to Chronic Obstructive Pulmonary Disease (COPD). Polymorphisms in the chitinase genes were selected based on previous associations with respiratory diseases. Polymorphisms that were associated with lung function level or rate of decline in the Lung Health Study (LHS) cohort were analyzed for association with COPD affection status in four other COPD case-control populations. Chitinase activity and protein levels were also related to genotypes. In the Caucasian LHS population, the baseline forced expiratory volume in one second (FEV1) was significantly different between the AA and GG genotypic groups of the AMCase rs3818822 polymorphism. Subjects with the GG genotype had higher AMCase protein and chitinase activity compared with AA homozygotes. For CHIT1 rs2494303, a significant association was observed between rate of decline in FEV1 and the different genotypes. In the African American LHS population, CHIT1 rs2494303 and AMCase G339T genotypes were associated with rate of decline in FEV1. Although a significant effect of chitinase gene alleles was found on lung function level and decline in the LHS, we were unable to replicate the associations with COPD affection status in the other COPD study groups. PMID:22200767

  2. Some properties of multiple orthogonal polynomials associated with Macdonald functions

    NASA Astrophysics Data System (ADS)

    Coussement, Els; van Assche, Walter

    2001-08-01

    Multiple orthogonal polynomials corresponding to two weights on [0,[infinity]) associated with modified Bessel functions (Macdonald functions) K[nu] and K[nu]+1 were introduced in Van Assche, Yakubovich (Integral Transforms Special Funct. 9 (2000) 229-244) and recently also studied by Ben Cheikh, Douak (Meth. Appl. Anal., to appear). We obtain explicit formulas for type I vector polynomials (An,n,Bn,n) and (An+1,n,Bn+1,n) and for type II polynomials Pn,n and Pn+1,n. We also obtain generating functions for types I and II polynomials.

  3. Distinct Quantitative Computed Tomography Emphysema Patterns Are Associated with Physiology and Function in Smokers

    PubMed Central

    San José Estépar, Raúl; Mendoza, Carlos S.; Hersh, Craig P.; Laird, Nan; Crapo, James D.; Lynch, David A.; Silverman, Edwin K.; Washko, George R.

    2013-01-01

    Rationale: Emphysema occurs in distinct pathologic patterns, but little is known about the epidemiologic associations of these patterns. Standard quantitative measures of emphysema from computed tomography (CT) do not distinguish between distinct patterns of parenchymal destruction. Objectives: To study the epidemiologic associations of distinct emphysema patterns with measures of lung-related physiology, function, and health care use in smokers. Methods: Using a local histogram-based assessment of lung density, we quantified distinct patterns of low attenuation in 9,313 smokers in the COPDGene Study. To determine if such patterns provide novel insights into chronic obstructive pulmonary disease epidemiology, we tested for their association with measures of physiology, function, and health care use. Measurements and Main Results: Compared with percentage of low-attenuation area less than −950 Hounsfield units (%LAA-950), local histogram-based measures of distinct CT low-attenuation patterns are more predictive of measures of lung function, dyspnea, quality of life, and health care use. These patterns are strongly associated with a wide array of measures of respiratory physiology and function, and most of these associations remain highly significant (P < 0.005) after adjusting for %LAA-950. In smokers without evidence of chronic obstructive pulmonary disease, the mild centrilobular disease pattern is associated with lower FEV1 and worse functional status (P < 0.005). Conclusions: Measures of distinct CT emphysema patterns provide novel information about the relationship between emphysema and key measures of physiology, physical function, and health care use. Measures of mild emphysema in smokers with preserved lung function can be extracted from CT scans and are significantly associated with functional measures. PMID:23980521

  4. Intrinsic functional connectivity between amygdala and hippocampus during rest predicts enhanced memory under stress.

    PubMed

    de Voogd, Lycia D; Klumpers, Floris; Fernández, Guillén; Hermans, Erno J

    2017-01-01

    Declarative memories of stressful events are less prone to forgetting than mundane events. Animal research has demonstrated that such stress effects on consolidation of hippocampal-dependent memories require the amygdala. In humans, it has been shown that during learning, increased amygdala-hippocampal interactions are related to more efficient memory encoding. Animal models predict that following learning, amygdala-hippocampal interactions are instrumental to strengthening the consolidation of such declarative memories. Whether this is the case in humans is unknown and remains to be empirically verified. To test this, we analyzed data from a sample of 120 healthy male participants who performed an incidental encoding task and subsequently underwent resting-state functional MRI in a stressful and a neutral context. Stress was assessed by measures of salivary cortisol, blood pressure, heart rate, and subjective ratings. Memory was tested afterwards outside of the scanner. Our data show that memory was stronger in the stress context compared to the neutral context and that stress-induced cortisol responses were associated with this memory enhancement. Interestingly, amygdala-hippocampal connectivity during post-encoding awake rest regardless of context (stress or neutral) was associated with the enhanced memory performance under stress. Thus, our findings are in line with a role for intrinsic functional connectivity during rest between the amygdala and the hippocampus in the state effects of stress on strengthening memory.

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

    PubMed Central

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

    2017-01-01

    The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity. PMID:28335492

  6. I-TASSER: a unified platform for automated protein structure and function prediction.

    PubMed

    Roy, Ambrish; Kucukural, Alper; Zhang, Yang

    2010-04-01

    The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.

  7. Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards

    PubMed Central

    Plitt, Mark; Barnes, Kelly Anne; Martin, Alex

    2014-01-01

    Objectives Autism spectrum disorders (ASD) are diagnosed based on early-manifesting clinical symptoms, including markedly impaired social communication. We assessed the viability of resting-state functional MRI (rs-fMRI) connectivity measures as diagnostic biomarkers for ASD and investigated which connectivity features are predictive of a diagnosis. Methods Rs-fMRI scans from 59 high functioning males with ASD and 59 age- and IQ-matched typically developing (TD) males were used to build a series of machine learning classifiers. Classification features were obtained using 3 sets of brain regions. Another set of classifiers was built from participants' scores on behavioral metrics. An additional age and IQ-matched cohort of 178 individuals (89 ASD; 89 TD) from the Autism Brain Imaging Data Exchange (ABIDE) open-access dataset (http://fcon_1000.projects.nitrc.org/indi/abide/) were included for replication. Results High classification accuracy was achieved through several rs-fMRI methods (peak accuracy 76.67%). However, classification via behavioral measures consistently surpassed rs-fMRI classifiers (peak accuracy 95.19%). The class probability estimates, P(ASD|fMRI data), from brain-based classifiers significantly correlated with scores on a measure of social functioning, the Social Responsiveness Scale (SRS), as did the most informative features from 2 of the 3 sets of brain-based features. The most informative connections predominantly originated from regions strongly associated with social functioning. Conclusions While individuals can be classified as having ASD with statistically significant accuracy from their rs-fMRI scans alone, this method falls short of biomarker standards. Classification methods provided further evidence that ASD functional connectivity is characterized by dysfunction of large-scale functional networks, particularly those involved in social information processing. PMID:25685703

  8. Predicting C-H/pi interactions with nonlocal density functional theory.

    PubMed

    Hooper, Joe; Cooper, Valentino R; Thonhauser, Timo; Romero, Nichols A; Zerilli, Frank; Langreth, David C

    2008-04-21

    We examine the performance of a recently developed nonlocal density functional in predicting a model noncovalent interaction, namely the weak bond between an aromatic pi system and an aliphatic C--H group. The new functional is a significant improvement over traditional density functionals, providing results which compare favorably to high-level quantum-chemistry techniques, but at considerably lower computational cost. Interaction energies in several model C--H/pi systems are in good general agreement with coupled-cluster calculations, though equilibrium distances are consistently overpredicted when using the revPBE functional for exchange. The new functional predicts changes in energy upon addition of halogen substituents correctly.

  9. Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation.

    PubMed

    Yeo, B T Thomas; Tandi, Jesisca; Chee, Michael W L

    2015-05-01

    Significant inter-individual differences in vigilance decline following sleep deprivation exist. We characterized functional connectivity in 68 healthy young adult participants in rested wakefulness and following a night of total sleep deprivation. After whole brain signal regression, functionally connected cortical networks during the well-rested state exhibited reduced correlation following sleep deprivation, suggesting that highly integrated brain regions become less integrated during sleep deprivation. In contrast, anti-correlations in the well-rested state became less so following sleep deprivation, suggesting that highly segregated networks become less segregated during sleep deprivation. Subjects more resilient to vigilance decline following sleep deprivation showed stronger anti-correlations among several networks. The weaker anti-correlations overlapped with connectivity alterations following sleep deprivation. Resilient individuals thus evidence clearer separation of highly segregated cortical networks in the well-rested state. In contrast to corticocortical connectivity, subcortical-cortical connectivity was comparable across resilient and vulnerable groups despite prominent state-related changes in both groups. Because sleep deprivation results in a significant elevation of whole brain signal amplitude, the aforesaid signal changes and group contrasts may be masked in analyses omitting their regression, suggesting possible value in regressing whole brain signal in certain experimental contexts.

  10. Gait patterns associated with thyroid function: The Rotterdam Study

    PubMed Central

    Bano, Arjola; Chaker, Layal; Darweesh, Sirwan K. L.; Korevaar, Tim I. M.; Mattace-Raso, Francesco U. S.; Dehghan, Abbas; Franco, Oscar H.; van der Geest, Jos N.; Ikram, M. Arfan; Peeters, Robin P.

    2016-01-01

    Gait is an important health indicator and poor gait is strongly associated with disability and risk of falls. Thyroid dysfunction is suggested as a potential determinant of gait deterioration, but this has not been explored in a population-based study. We therefore investigated the association of thyroid function with gait patterns in 2645 participants from the Rotterdam Study with data available on TSH (thyroid-stimulating hormone), FT4 (free thyroxine) and gait, without known thyroid disease or dementia. The primary outcome was Global gait (standardized Z-score), while secondary outcomes included gait domains (Rhythm, Variability, Phases, Pace, Base of support, Tandem, Turning) and velocity. Gait was assessed by electronic walkway. Multivariable regression models revealed an inverted U-shaped association of TSH (p < 0.001), but no association of FT4 concentrations with Global gait (p = 0.2). TSH levels were positively associated with Base of support (p = 0.01) and followed an inverted U-shaped curve with Tandem (p = 0.002) and velocity (p = 0.02). Clinical and subclinical hypothyroidism were associated with worse Global gait than euthyroidism (β = −0.61; CI = −1.03, −0.18; p = 0.004 and β = −0.13; CI = −0.26, −0.00; p = 0.04, respectively). In euthyroid participants, higher thyroid function was associated with worse gait patterns. In conclusion, both low and high thyroid function are associated with alterations in Global gait, Tandem, Base of support and velocity. PMID:27966590

  11. Associations among False Belief Understanding, Counterfactual Reasoning, and Executive Function

    ERIC Educational Resources Information Center

    Guajardo, Nicole R.; Parker, Jessica; Turley-Ames, Kandi

    2009-01-01

    The primary purposes of the present study were to clarify previous work on the association between counterfactual thinking and false belief performance to determine (1) whether these two variables are related and (2) if so, whether executive function skills mediate the relationship. A total of 92 3-, 4-, and 5-year-olds completed false belief,…

  12. Vascular function in diabetic individuals in association with particulate matter

    EPA Science Inventory

    Rationale: Exposure to ambient air pollution has been shown to be associated with cardiovascular effects, especially in people with chronic diseases such as diabetes. The purpose of this study was to analyze the short-term effects of air pollution on vascular function in two pane...

  13. Analogue Functional Analysis of Movements Associated with Tardive Dyskinesia

    ERIC Educational Resources Information Center

    Valdovinos, Maria G.; Roberts, Celeste; Kennedy, Craig H.

    2004-01-01

    We studied whether movements associated with tardive dyskinesia (TD) served operant functions in 2 men with developmental disabilities. We found that TD-related movements occurred more frequently in the alone and attention conditions and less frequently in control and demand conditions. Our findings suggest that TD-related movements may not be…

  14. Testing for Differential Item Functioning with Measures of Partial Association

    ERIC Educational Resources Information Center

    Woods, Carol M.

    2009-01-01

    Differential item functioning (DIF) occurs when an item on a test or questionnaire has different measurement properties for one group of people versus another, irrespective of mean differences on the construct. There are many methods available for DIF assessment. The present article is focused on indices of partial association. A family of average…

  15. Functional Linear Models for Association Analysis of Quantitative Traits

    PubMed Central

    Fan, Ruzong; Wang, Yifan; Mills, James L.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao

    2014-01-01

    Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. PMID:24130119

  16. Functional linear models for association analysis of quantitative traits.

    PubMed

    Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

    2013-11-01

    Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study.

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

    PubMed

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

    2009-02-15

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

  18. Prediction and uncertainty in associative learning: examining controlled and automatic components of learned attentional biases.

    PubMed

    Luque, David; Vadillo, Miguel A; Le Pelley, Mike E; Beesley, Tom

    2017-08-01

    It has been suggested that attention is guided by two factors that operate during associative learning: a predictiveness principle, by which attention is allocated to the best predictors of outcomes, and an uncertainty principle, by which attention is allocated to learn about the less known features of the environment. Recent studies have shown that predictiveness-driven attention can operate rapidly and in an automatic way to exploit known relationships. The corresponding characteristics of uncertainty-driven attention, on the other hand, remain unexplored. In two experiments we examined whether both predictiveness and uncertainty modulate attentional processing in an adaptation of the dot probe task. This task provides a measure of automatic orientation to cues during associative learning. The stimulus onset asynchrony of the probe display was manipulated in order to explore temporal characteristics of predictiveness- and uncertainty-driven attentional effects. Results showed that the predictive status of cues determined selective attention, with faster attentional capture to predictive than to non-predictive cues. In contrast, the level of uncertainty slowed down responses to the probe regardless of the predictive status of the cues. Both predictiveness- and uncertainty-driven attentional effects were very rapid (at 250 ms from cue onset) and were automatically activated.

  19. Intrapersonal and Interpersonal Functions of Non Suicidal Self-Injury: Associations with Emotional and Social Functioning

    ERIC Educational Resources Information Center

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

    2012-01-01

    Understanding the functions of nonsuicidal self-injury (NSSI) has important implications for the development and refinement of theoretical models and treatments of NSSI. Emotional and social vulnerabilities associated with five common functions of NSSI-emotion relief (ER), feeling generation (FG), self-punishment (SP), interpersonal influence…

  20. Anemia and Red Blood Cell Indices Predict HIV-Associated Neurocognitive Impairment in the Highly Active Antiretroviral Therapy Era

    PubMed Central

    Kallianpur, Asha R.; Wang, Quan; Jia, Peilin; Hulgan, Todd; Zhao, Zhongming; Letendre, Scott L.; Ellis, Ronald J.; Heaton, Robert K.; Franklin, Donald R.; Barnholtz-Sloan, Jill; Collier, Ann C.; Marra, Christina M.; Clifford, David B.; Gelman, Benjamin B.; McArthur, Justin C.; Morgello, Susan; Simpson, David M.; McCutchan, J. A.; Grant, Igor

    2016-01-01

    Background. Anemia has been linked to adverse human immunodeficiency virus (HIV) outcomes, including dementia, in the era before highly active antiretroviral therapy (HAART). Milder forms of HIV-associated neurocognitive disorder (HAND) remain common in HIV-infected persons, despite HAART, but whether anemia predicts HAND in the HAART era is unknown. Methods. We evaluated time-dependent associations of anemia and cross-sectional associations of red blood cell indices with neurocognitive impairment in a multicenter, HAART-era HIV cohort study (N = 1261), adjusting for potential confounders, including age, nadir CD4+ T-cell count, zidovudine use, and comorbid conditions. Subjects underwent comprehensive neuropsychiatric and neuromedical assessments. Results. HAND, defined according to standardized criteria, occurred in 595 subjects (47%) at entry. Mean corpuscular volume and mean corpuscular hemoglobin were positively associated with the global deficit score, a continuous measure of neurocognitive impairment (both P < .01), as well as with all HAND, milder forms of HAND, and HIV-associated dementia in multivariable analyses (all P < .05). Anemia independently predicted development of HAND during a median follow-up of 72 months (adjusted hazard ratio, 1.55; P < .01). Conclusions. Anemia and red blood cell indices predict HAND in the HAART era and may contribute to risk assessment. Future studies should address whether treating anemia may help to prevent HAND or improve cognitive function in HIV-infected persons. PMID:26690344

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

    PubMed

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

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

  2. Does cognitive functioning predict chronic pain? Results from a prospective surgical cohort.

    PubMed

    Attal, Nadine; Masselin-Dubois, Anne; Martinez, Valéria; Jayr, Christian; Albi, Aline; Fermanian, Jacques; Bouhassira, Didier; Baudic, Sophie

    2014-03-01

    It is well established that chronic pain impairs cognition, particularly memory, attention and mental flexibility. Overlaps have been found between the brain regions involved in pain modulation and cognition, including in particular the prefrontal cortex and the anterior cingulate cortex, which are involved in executive function, attention and memory. However, whether cognitive function may predict chronic pain has not been investigated. We addressed this question in surgical patients, because such patients can be followed prospectively and may have no pain before surgery. In this prospective longitudinal study, we investigated the links between executive function, visual memory and attention, as assessed by clinical measurements and the development of chronic pain, its severity and neuropathic symptoms (based on the 'Douleur Neuropathique 4' questionnaire), 6 and 12 months after surgery (total knee arthroplasty for osteoarthritis or breast surgery for cancer). Neuropsychological tests included the Trail-Making Test A and B, and the Rey-Osterrieth Complex Figure copy and immediate recall, which assess cognitive flexibility, visuospatial processing and visual memory. Anxiety, depression and coping strategies were also evaluated. In total, we investigated 189 patients before surgery: 96% were re-evaluated at 6 months, and 88% at 12 months. Multivariate logistic regression (stepwise selection) for the total group of patients indicated that the presence of clinical meaningful pain at 6 and 12 months (pain intensity ≥ 3/10) was predicted by poorer cognitive performance in the Trail Making Test B (P = 0.0009 and 0.02 for pain at 6 and 12 months, respectively), Rey-Osterrieth Complex Figure copy (P = 0.015 and 0.006 for pain at 6 and 12 months, respectively) and recall (P = 0.016 for pain at 12 months), independently of affective variables. Linear regression analyses indicated that impaired scores on these tests predicted pain intensity (P < 0.01) and neuropathic

  3. Sparse Markov chain-based semi-supervised multi-instance multi-label method for protein function prediction.

    PubMed

    Han, Chao; Chen, Jian; Wu, Qingyao; Mu, Shuai; Min, Huaqing

    2015-10-01

    Automated assignment of protein function has received considerable attention in recent years for genome-wide study. With the rapid accumulation of genome sequencing data produced by high-throughput experimental techniques, the process of manually predicting functional properties of proteins has become increasingly cumbersome. Such large genomics data sets can only be annotated computationally. However, automated assignment of functions to unknown protein is challenging due to its inherent difficulty and complexity. Previous studies have revealed that solving problems involving complicated objects with multiple semantic meanings using the multi-instance multi-label (MIML) framework is effective. For the protein function prediction problems, each protein object in nature may associate with distinct structural units (instances) and multiple functional properties (class labels) where each unit is described by an instance and each functional property is considered as a class label. Thus, it is convenient and natural to tackle the protein function prediction problem by using the MIML framework. In this paper, we propose a sparse Markov chain-based semi-supervised MIML method, called Sparse-Markov. A sparse transductive probability graph is constructed to encode the affinity information of the data based on ensemble of Hausdorff distance metrics. Our goal is to exploit the affinity between protein objects in the sparse transductive probability graph to seek a sparse steady state probability of the Markov chain model to do protein function prediction, such that two proteins are given similar functional labels if they are close to each other in terms of an ensemble Hausdorff distance in the graph. Experimental results on seven real-world organism data sets covering three biological domains show that our proposed Sparse-Markov method is able to achieve better performance than four state-of-the-art MIML learning algorithms.

  4. The Prediction of Broadband Shock-Associated Noise from Dualstream and Rectangular Jets Using RANS CFD

    NASA Technical Reports Server (NTRS)

    Miller, Steven A.; Morris, Philip J.

    2010-01-01

    Supersonic jets operating off-design produce broadband shock-associated noise. Broadband shock-associated noise is characterized by multiple broadband peaks in the far-field and is often the dominant source of noise towards the sideline and upstream direction relative to the jet axis. It is due to large scale coherent turbulence structures in the jet shear layers interacting with the shock cell structure. A broadband shock-associated noise model recently developed by the authors predicts this noise component from solutions to the Reynolds averaged Navier-Stokes equations using a two-equation turbulence model. The broadband shock-associated noise model is applied to dualstream and rectangular nozzles operating supersonically, heated, and off-design. The dualstream jet broadband shock-associated noise predictions are conducted for cases when the core jet is supersonic and the fan jet is subsonic, the core jet is subsonic and the fan jet is supersonic, and when both jet streams operate supersonically. Rectangular jet predictions are shown for a convergent-divergent nozzle operating both over- and under-expanded for cold and heated conditions. The original model implementation has been heavily modified to make accurate predictions for the dualstream jets. It is also argued that for over-expanded jets the oblique shock wave attached to the nozzle lip contributes little to broadband shock-associated noise. All predictions are compared with experiments.

  5. Protein Function Prediction using Text-based Features extracted from the Biomedical Literature: The CAFA Challenge

    PubMed Central

    2013-01-01

    Background Advances in sequencing technology over the past decade have resulted in an abundance of sequenced proteins whose function is yet unknown. As such, computational systems that can automatically predict and annotate protein function are in demand. Most computational systems use features derived from protein sequence or protein structure to predict function. In an earlier work, we demonstrated the utility of biomedical literature as a source of text features for predicting protein subcellular location. We have also shown that the combination of text-based and sequence-based prediction improves the performance of location predictors. Following up on this work, for the Critical Assessment of Function Annotations (CAFA) Challenge, we developed a text-based system that aims to predict molecular function and biological process (using Gene Ontology terms) for unannotated proteins. In this paper, we present the preliminary work and evaluation that we performed for our system, as part of the CAFA challenge. Results We have developed a preliminary system that represents proteins using text-based features and predicts protein function using a k-nearest neighbour classifier (Text-KNN). We selected text features for our classifier by extracting key terms from biomedical abstracts based on their statistical properties. The system was trained and tested using 5-fold cross-validation over a dataset of 36,536 proteins. System performance was measured using the standard measures of precision, recall, F-measure and overall accuracy. The performance of our system was compared to two baseline classifiers: one that assigns function based solely on the prior distribution of protein function (Base-Prior) and one that assigns function based on sequence similarity (Base-Seq). The overall prediction accuracy of Text-KNN, Base-Prior, and Base-Seq for molecular function classes are 62%, 43%, and 58% while the overall accuracy for biological process classes are 17%, 11%, and 28

  6. Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency.

    PubMed

    Wang, Hua; Huang, Heng; Ding, Chris

    2015-06-01

    Conventional computational approaches for protein function prediction usually predict one function at a time, fundamentally. As a result, the protein functions are treated as separate target classes. However, biological processes are highly correlated in reality, which makes multiple functions assigned to a protein not independent. Therefore, it would be beneficial to make use of function category correlations when predicting protein functions. In this article, we propose a novel Maximization of Data-Knowledge Consistency (MDKC) approach to exploit function category correlations for protein function prediction. Our approach banks on the assumption that two proteins are likely to have large overlap in their annotated functions if they are highly similar according to certain experimental data. We first establish a new pairwise protein similarity using protein annotations from knowledge perspective. Then by maximizing the consistency between the established knowledge similarity upon annotations and the data similarity upon biological experiments, putative functions are assigned to unannotated proteins. Most importantly, function category correlations are gracefully incorporated into our learning objective through the knowledge similarity. Comprehensive experimental evaluations on the Saccharomyces cerevisiae species have demonstrated promising results that validate the performance of our methods.

  7. FINDSITE: a combined evolution/structure-based approach to protein function prediction

    PubMed Central

    Brylinski, Michal

    2009-01-01

    A key challenge of the post-genomic era is the identification of the function(s) of all the molecules in a given organism. Here, we review the status of sequence and structure-based approaches to protein function inference and ligand screening that can provide functional insights for a significant fraction of the ∼50% of ORFs of unassigned function in an average proteome. We then describe FINDSITE, a recently developed algorithm for ligand binding site prediction, ligand screening and molecular function prediction, which is based on binding site conservation across evolutionary distant proteins identified by threading. Importantly, FINDSITE gives comparable results when high-resolution experimental structures as well as predicted protein models are used. PMID:19324930

  8. Default Mode Functional Connectivity Is Associated With Social Functioning in Schizophrenia.

    PubMed

    Fox, Jaclyn M; Abram, Samantha V; Reilly, James L; Eack, Shaun; Goldman, Morris B; Csernansky, John G; Wang, Lei; Smith, Matthew J

    2017-03-30

    Individuals with schizophrenia display notable deficits in social functioning. Research indicates that neural connectivity within the default mode network (DMN) is related to social cognition and social functioning in healthy and clinical populations. However, the association between DMN connectivity, social cognition, and social functioning has not been studied in schizophrenia. For the present study, the authors used resting-state neuroimaging data to evaluate connectivity between the main DMN hubs (i.e., the medial prefrontal cortex [mPFC] and the posterior cingulate cortex-anterior precuneus [PPC]) in individuals with schizophrenia (n = 28) and controls (n = 32). The authors also examined whether DMN connectivity was associated with social functioning via social attainment (measured by the Specific Levels of Functioning Scale) and social competence (measured by the Social Skills Performance Assessment), and if social cognition mediates the association between DMN connectivity and these measures of social functioning. Results revealed that DMN connectivity did not differ between individuals with schizophrenia and controls. However, connectivity between the mPFC and PCC hubs was significantly associated with social competence and social attainment in individuals with schizophrenia but not in controls as reflected by a significant group-by-connectivity interaction. Social cognition did not mediate the association between DMN connectivity and social functioning in individuals with schizophrenia. The findings suggest that fronto-parietal DMN connectivity in particular may be differentially associated with social functioning in schizophrenia and controls. As a result, DMN connectivity may be used as a neuroimaging marker to monitor treatment response or as a potential target for interventions that aim to enhance social functioning in schizophrenia. (PsycINFO Database Record

  9. Applications of Displacement Transfer Functions to Deformed Shape Predictions of the GIII Swept-Wing Structure

    NASA Technical Reports Server (NTRS)

    Lung, Shun-Fat; Ko, William L.

    2016-01-01

    The displacement transfer functions (DTFs) were applied to the GIII swept wing for the deformed shape prediction. The calculated deformed shapes are very close to the correlated finite element results as well as the measured data. The convergence study showed that using 17 strain stations, the wing-tip displacement prediction error was 1.6 percent, and that there is no need to use a large number of strain stations for G-III wing shape predictions.

  10. What Specific Facets of Executive Function are Associated with Academic Functioning in Youth with Attention-Deficit/Hyperactivity Disorder?

    PubMed Central

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

    2013-01-01

    The purpose of the study was to evaluate the relation between ratings of Executive Function (EF) and academic functioning in a sample of 94 middle-school-aged youth with Attention-Deficit/Hyperactivity Disorder (ADHD; Mage = 11.9; 78% male; 21% minority). This study builds on prior work by evaluating associations between multiple specific aspects of EF (e.g., working memory, inhibition, and planning and organization) as rated by both parents and teachers on the Behavior Rating Inventory of Executive Function (BRIEF), with multiple academic outcomes, including school grades and homework problems. Further, this study examined the relationship between EF and academic outcomes above and beyond ADHD symptoms and controlled for a number of potentially important covariates, including intelligence and achievement scores. The EF Planning and Organization subscale as rated by both parents and teachers predicted school grades above and beyond symptoms of ADHD and relevant covariates. Parent ratings of youth’s ability to transition effectively between tasks/situations (Shift subscale) also predicted school grades. Parent-rated symptoms of inattention, hyperactivity/impulsivity, and planning and organization abilities were significant in the final model predicting homework problems. In contrast, only symptoms of inattention and the Organization of Materials subscale from the BRIEF were significant in the teacher model predicting homework problems. Organization and planning abilities are highly important aspects academic functioning for middle-school-aged youth with ADHD. Implications of these findings for the measurement of EF, and organization and planning abilities in particular, are discussed along with potential implications for intervention. PMID:23640285

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

    PubMed

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

    2013-10-01

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

  12. A functional polymorphism in the MAOA gene promoter (MAOA-LPR) predicts central dopamine function and body mass index.

    PubMed

    Ducci, F; Newman, T K; Funt, S; Brown, G L; Virkkunen, M; Goldman, D

    2006-09-01

    Variation in brain monoaminergic activity is heritable and modulates risk of alcoholism and other addictions, as well as food intake and energy expenditure. Monoamine oxidase A deaminates the monoamine neurotransmitters serotonin, dopamine (DA), and noradrenaline. The monoamine oxidase A (MAOA) gene (Xp11.5) contains a length polymorphism in its promoter region (MAOA-LPR) that putatively affects transcriptional efficiency. Our goals were to test (1) whether MAOA-LPR contributes to interindividual variation in monoamine activity, assessed using levels of cerebrospinal fluid (CSF) monoamine metabolites; and (2) whether MAOA-LPR genotype influences alcoholism and/or body mass index (BMI). Male, unrelated criminal alcoholics (N=278) and controls (N=227) were collected from a homogeneous Finnish source population. CSF concentration of 5-hydroxyindoleacetic acid (5-HIAA), homovanillic acid (HVA), and 3-methoxy-4-hydroxyphenylglycol (MHPG) were available from 208 participants. Single allele, hemizygous genotypes were grouped according to inferred effect of the MAOA alleles on transcriptional activity. MAOA-LPR genotypes had a significant effect on CSF HVA concentration (P=0.01) but explained only 3% of the total variance. There was a detectable but nonsignificant genotype effect on 5-HIAA and no effects on MHPG. Specifically, the genotype conferring high MAOA activity was associated with lower HVA levels in both alcoholics and controls, a finding that persisted after accounting for the potential confounds of alcoholism, BMI, height, and smoking. MAOA-LPR genotype predicted BMI (P<0.005), with the high-activity genotype being associated with lower BMI. MAOA-LPR genotypes were not associated with alcoholism or related psychiatric phenotypes in this data set. Our results suggest that MAOA-LPR allelic variation modulates DA turnover in the CNS, but does so in a manner contrary to our prior expectation that alleles conferring high activity would predict higher HVA levels in

  13. Comparison of Statistical and Clinical Predictions of Functional Outcome after Ischemic Stroke

    PubMed Central

    Thompson, Douglas D.; Murray, Gordon D.; Sudlow, Cathie L. M.; Dennis, Martin; Whiteley, William N.

    2014-01-01

    Background To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor’s clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs). Methods and Findings A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS). Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3) using five previously described CPMs. The specificity of a doctor’s informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97) and similar to CPMs (range 0.94 to 0.96); however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49) and clinical prediction models (range 0.38 to 0.45) was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76) and CPMs (range 0.69 to 0.75). No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients. Conclusions CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined. PMID:25299053

  14. Predicting maize phenology: Intercomparison of functions for developmental response to temperature

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate prediction of phenological development in maize is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were t...

  15. Predicting the biomechanical strength of proximal femur specimens with Minkowski functionals and support vector regression

    NASA Astrophysics Data System (ADS)

    Yang, Chien-Chun; Nagarajan, Mahesh B.; Huber, Markus B.; Carballido-Gamio, Julio; Bauer, Jan S.; Baum, Thomas; Eckstein, Felix; Lochmüller, Eva-Maria; Link, Thomas M.; Wismüller, Axel

    2014-03-01

    Regional trabecular bone quality estimation for purposes of femoral bone strength prediction is important for improving the clinical assessment of osteoporotic fracture risk. In this study, we explore the ability of 3D Minkowski Functionals derived from multi-detector computed tomography (MDCT) images of proximal femur specimens in predicting their corresponding biomechanical strength. MDCT scans were acquired for 50 proximal femur specimens harvested from human cadavers. An automated volume of interest (VOI)-fitting algorithm was used to define a consistent volume in the femoral head of each specimen. In these VOIs, the trabecular bone micro-architecture was characterized by statistical moments of its BMD distribution and by topological features derived from Minkowski Functionals. A linear multiregression analysis and a support vector regression (SVR) algorithm with a linear kernel were used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction result was obtained from the Minkowski Functional surface used in combination with SVR, which had the lowest prediction error (RMSE = 0.939 ± 0.345) and which was significantly lower than mean BMD (RMSE = 1.075 ± 0.279, p<0.005). Our results indicate that the biomechanical strength prediction can be significantly improved in proximal femur specimens with Minkowski Functionals extracted from on MDCT images used in conjunction with support vector regression.

  16. Nurses' Assessment of Rehabilitation Potential and Prediction of Functional Status at Discharge from Inpatient Rehabilitation

    ERIC Educational Resources Information Center

    Myers, Jamie S.; Grigsby, Jim; Teel, Cynthia S.; Kramer, Andrew M.

    2009-01-01

    The goals of this study were to evaluate the accuracy of nurses' predictions of rehabilitation potential in older adults admitted to inpatient rehabilitation facilities and to ascertain whether the addition of a measure of executive cognitive function would enhance predictive accuracy. Secondary analysis was performed on prospective data collected…

  17. Factors Predicting Renal Function Outcome after Augmentation Cystoplasty

    PubMed Central

    Seyam, Raouf; Firdous, Sadia

    2017-01-01

    We determined the cause of renal deterioration after augmentation cystoplasty (AC). Twenty-nine adult patients with refractory bladder dysfunction and who underwent ileocystoplasty from 2004 to 2015 were studied. Patients with a decline in glomerular filtration rate (GFR) after augmentation were reviewed. The primary outcome was to determine the factors that might lead to deterioration of estimated GFR. Median follow-up was 7.0 ± 2.6 years. Significant bladder capacity, end filling pressure, and bladder compliance were achieved from median 114 ± 53.6 to 342.1 ± 68.3 ml (p = .0001), 68.5 ± 19.9 to 28.2 ± 6.9 cm H2O (p = .0001), and 3.0 ± 2.1 to 12.8 ± 3.9 (p = .0001), respectively. Renal function remained stable and improved in 22 (76%) patients from median eGFR 135 ± 81.98 to 142.82 ± 94.4 ml/min/1.73 m2 (p = .160). Significant deterioration was found in 7 (24%) patients from median eGFR 68.25 ± 42 to 36.57 ± 35.33 (p = .001). The causes of renal deterioration were noncompliance to self-catheterization (2 patients), posterior urethral valve/dysplastic kidneys (2 patients), and reflux/infection (2 patients). On multivariate analysis, recurrent pyelonephritis (OR 3.87, p = 0.0155) and noncompliance (OR 30.78, p = 0.0156) were significant. We concluded that AC is not the cause of progression to end-stage renal disease in patients with renal insufficiency. PMID:28367330

  18. Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits

    PubMed Central

    Wolpe, Noham; Ingram, James N.; Tsvetanov, Kamen A.; Geerligs, Linda; Kievit, Rogier A.; Henson, Richard N.; Wolpert, Daniel M.; Tyler, Lorraine K.; Brayne, Carol; Bullmore, Edward; Calder, Andrew; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Matthews, Fiona E.; Marslen-Wilson, William; Shafto, Meredith A.; Campbell, Karen; Cheung, Teresa; Davis, Simon; McCarrey, Anna; Mustafa, Abdur; Price, Darren; Samu, David; Taylor, Jason R.; Treder, Matthias; van Belle, Janna; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Henriques, Rafael; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Barnes, Dan; Dixon, Marie; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Rowe, James B.

    2016-01-01

    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. PMID:27694879

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  20. Functional aspects of membrane association of reggie/flotillin proteins.

    PubMed

    Banning, Antje; Tomasovic, Ana; Tikkanen, Ritva

    2011-12-01

    Flotillin-2 and flotillin-1, also called reggie-1 and reggie-2, are ubiquitously expressed and highly conserved proteins. Originally, they were described as neuronal regeneration proteins, but they appear to function in a wide variety of cellular processes, such as membrane receptor signaling, endocytosis, phagocytosis and cell adhesion. The molecular details of the function of flotillins in these processes have only been partially clarified. Flotillins are associated with cholesterol and sphingolipid enriched membrane microdomains known as rafts, and some findings even suggest that they define their own kind of a microdomain. The mechanism of the membrane association of flotillins appears to rely mainly on acylation (myristoylation and/or palmitoylation), localizing flotillins onto the cytosolic side of the membranes, whereas no transmembrane domains are present. In addition, flotillins show a strong tendency to form homo- and hetero-oligomers with each other. In this review, we will summarize the recent findings on the function of flotillins and discuss the mechanisms that might regulate their function, such as membrane association, oligomerization and phosphorylation.

  1. Epigenetic and immune function profiles associated with posttraumatic stress disorder

    PubMed Central

    Uddin, Monica; Aiello, Allison E.; Wildman, Derek E.; Koenen, Karestan C.; Pawelec, Graham; de los Santos, Regina; Goldmann, Emily; Galea, Sandro

    2010-01-01

    The biologic underpinnings of posttraumatic stress disorder (PTSD) have not been fully elucidated. Previous work suggests that alterations in the immune system are characteristic of the disorder. Identifying the biologic mechanisms by which such alterations occur could provide fundamental insights into the etiology and treatment of PTSD. Here we identify specific epigenetic profiles underlying immune system changes associated with PTSD. Using blood samples (n = 100) obtained from an ongoing, prospective epidemiologic study in Detroit, the Detroit Neighborhood Health Study, we applied methylation microarrays to assay CpG sites from more than 14,000 genes among 23 PTSD-affected and 77 PTSD-unaffected individuals. We show that immune system functions are significantly overrepresented among the annotations associated with genes uniquely unmethylated among those with PTSD. We further demonstrate that genes whose methylation levels are significantly and negatively correlated with traumatic burden show a similar strong signal of immune function among the PTSD affected. The observed epigenetic variability in immune function by PTSD is corroborated using an independent biologic marker of immune response to infection, CMV—a typically latent herpesvirus whose activity was significantly higher among those with PTSD. This report of peripheral epigenomic and CMV profiles associated with mental illness suggests a biologic model of PTSD etiology in which an externally experienced traumatic event induces downstream alterations in immune function by reducing methylation levels of immune-related genes. PMID:20439746

  2. Exercise testing in severe emphysema: association with quality of life and lung function.

    PubMed

    Brown, Cynthia D; Benditt, Joshua O; Sciurba, Frank C; Lee, Shing M; Criner, Gerard J; Mosenifar, Zab; Shade, David M; Slivka, William A; Wise, Robert A

    2008-04-01

    Six-minute walk testing (6MWT) and cardiopulmonary exercise testing (CPX) are used to evaluate impairment in emphysema. However, the extent of impairment in these tests as well as the correlation of these tests with each other and lung function in advanced emphysema is not well characterized. During screening for the National Emphysema Treatment Trial, maximum ergometer CPX and 6MWT were performed in 1,218 individuals with severe COPD with an average FEV(1) of 26.9 +/- 7.1 % predicted. Predicted values for 6MWT and CPX were calculated from reference equations. Correlation coefficients and multivariable regression models were used to determine the association between lung function, quality of life (QOL) scores, and exercise measures. The two forms of exercise testing were correlated with each other (r = 0.57, p < 0.0001). However, the impairment of performance on CPX was greater than on the 6MWT (27.6 +/- 16.8 vs. 67.9 +/- 18.9 % predicted). Both exercise tests had similar correlation with measures of QOL, but maximum exercise capacity was better correlated with lung function measures than 6-minute walk distance. After adjustment, 6MWD had a slightly greater association with total SGRQ score than maximal exercise (effect size 0.37 +/- 0.04 vs. 0.25 +/- 0.03 %predicted/unit). Despite advanced emphysema, patients are able to maintain 6MWD to a greater degree than maximum exercise capacity. Moreover, the 6MWT may be a better test of functional capacity given its greater association with QOL measures whereas CPX is a better test of physiologic impairment.

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

    PubMed

    Wong, Aaron K; Park, Christopher Y; Greene, Casey S; Bongo, Lars A; Guan, Yuanfang; Troyanskaya, Olga G

    2012-07-01

    Integrative multi-species prediction (IMP) is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides a framework for biologists to analyze their candidate gene sets in the context of functional networks, as they expand or focus these sets by mining functional relationships predicted from integrated high-throughput data. IMP integrates prior knowledge and data collections from multiple organisms in its analyses. Through flexible and interactive visualizations, researchers can compare functional contexts and interpret the behavior of their gene sets across organisms. Additionally, IMP identifies homologs with conserved functional roles for knowledge transfer, allowing for accurate function predictions even for biological processes that have very few experimental annotations in a given organism. IMP currently supports seven organisms (Homo sapiens, Mus musculus, Rattus novegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans and Saccharomyces cerevisiae), does not require any registration or installation and is freely available for use at http://imp.princeton.edu.

  4. FNTM: a server for predicting functional networks of tissues in mouse.

    PubMed

    Goya, Jonathan; Wong, Aaron K; Yao, Victoria; Krishnan, Arjun; Homilius, Max; Troyanskaya, Olga G

    2015-07-01

    Functional Networks of Tissues in Mouse (FNTM) provides biomedical researchers with tissue-specific predictions of functional relationships between proteins in the most widely used model organism for human disease, the laboratory mouse. Users can explore FNTM-predicted functional relationships for their tissues and genes of interest or examine gene function and interaction predictions across multiple tissues, all through an interactive, multi-tissue network browser. FNTM makes predictions based on integration of a variety of functional genomic data, including over 13 000 gene expression experiments, and prior knowledge of gene function. FNTM is an ideal starting point for clinical and translational researchers considering a mouse model for their disease of interest, researchers already working with mouse models who are interested in discovering new genes related to their pathways or phenotypes of interest, and biologists working with other organisms to explore the functional relationships of their genes of interest in specific mouse tissue contexts. FNTM predicts tissue-specific functional relationships in 200 tissues, does not require any registration or installation and is freely available for use at http://fntm.princeton.edu.

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

    SciTech Connect

    Kim, K.T.; Lee, J.G.; Quay, B.D.; Santavicca, D.A.

    2010-09-15

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

  6. Associations between preoperative functional status and functional outcomes of total joint replacement in the Dominican Republic

    PubMed Central

    Collins, Jamie E.; Ghazinouri, Roya; Alcantara, Luis; Thornhill, Thomas S.; Katz, Jeffrey N.

    2013-01-01

    Objective. In developed countries, the functional status scores of patients with poor preoperative scores undergoing total joint replacement (TJR) improve more following TJR than those for patients with better preoperative scores. However, those with better preoperative scores achieve the best postoperative functional outcomes. We determined whether similar associations exist in a developing country. Methods. Dominican patients undergoing total hip or knee replacement completed WOMAC and SF-36 surveys preoperatively and at 12-month follow-up. Patients were stratified into low-, medium- and high-scoring preoperative groups based on their preoperative WOMAC function scores. We examined the associations between the baseline functional status of these groups and two outcomes—improvement in functional status over 12 months and functional status at 12 months—using analysis of variance with multivariable linear regression. Results. Patients who scored the lowest preoperatively made the greatest gains in function and pain relief following their TJRs. However, there were no significant differences in pain or function at 12-month follow-up between patients who scored low and those who scored high on preoperative WOMAC and SF-36 surveys. Conclusion. Patients with poor preoperative functional status had greater improvement but similar 12-month functional outcomes compared with patients who had a higher level of function before surgery. These results suggest that a policy of focusing scarce resources on patients with worse functional status in developing countries may optimize improvement following TJR without threatening functional outcome. Additional research is needed to confirm these findings in other developing countries and to understand why these associations vary between patients in the Dominican Republic and patients from developed countries. PMID:23748412

  7. IRWRLDA: improved random walk with restart for lncRNA-disease association prediction

    PubMed Central

    Chen, Xing; You, Zhu-Hong; Yan, Gui-Ying; Gong, Dun-Wei

    2016-01-01

    In recent years, accumulating evidences have shown that the dysregulations of lncRNAs are associated with a wide range of human diseases. It is necessary and feasible to analyze known lncRNA-disease associations, predict potential lncRNA-disease associations, and provide the most possible lncRNA-disease pairs for experimental validation. Considering the limitations of traditional Random Walk with Restart (RWR), the model of Improved Random Walk with Restart for LncRNA-Disease Association prediction (IRWRLDA) was developed to predict novel lncRNA-disease associations by integrating known lncRNA-disease associations, disease semantic similarity, and various lncRNA similarity measures. The novelty of IRWRLDA lies in the incorporation of lncRNA expression similarity and disease semantic similarity to set the initial probability vector of the RWR. Therefore, IRWRLDA could be applied to diseases without any known related lncRNAs. IRWRLDA significantly improved previous classical models with reliable AUCs of 0.7242 and 0.7872 in two known lncRNA-disease association datasets downloaded from the lncRNADisease database, respectively. Further case studies of colon cancer and leukemia were implemented for IRWRLDA and 60% of lncRNAs in the top 10 prediction lists have been confirmed by recent experimental reports. PMID:27517318

  8. The Dopamine Prediction Error: Contributions to Associative Models of Reward Learning

    PubMed Central

    Nasser, Helen M.; Calu, Donna J.; Schoenbaum, Geoffrey; Sharpe, Melissa J.

    2017-01-01

    Phasic activity of midbrain dopamine neurons is currently thought to encapsulate the prediction-error signal described in Sutton and Barto’s (1981) model-free reinforcement learning algorithm. This phasic signal is thought to contain information about the quantitative value of reward, which transfers to the reward-predictive cue after learning. This is argued to endow the reward-predictive cue with the value inherent in the reward, motivating behavior toward cues signaling the presence of reward. Yet theoretical and empirical research has implicated prediction-error signaling in learning that extends far beyond a transfer of quantitative value to a reward-predictive cue. Here, we review the research which demonstrates the complexity of how dopaminergic prediction errors facilitate learning. After briefly discussing the literature demonstrating that phasic dopaminergic signals can act in the manner described by Sutton and Barto (1981), we consider how these signals may also influence attentional processing across multiple attentional systems in distinct brain circuits. Then, we discuss how prediction errors encode and promote the development of context-specific associations between cues and rewards. Finally, we consider recent evidence that shows dopaminergic activity contains information about causal relationships between cues and rewards that reflect information garnered from rich associative models of the world that can be adapted in the absence of direct experience. In discussing this research we hope to support the expansion of how dopaminergic prediction errors are thought to contribute to the learning process beyond the traditional concept of transferring quantitative value. PMID:28275359

  9. The Dopamine Prediction Error: Contributions to Associative Models of Reward Learning.

    PubMed

    Nasser, Helen M; Calu, Donna J; Schoenbaum, Geoffrey; Sharpe, Melissa J

    2017-01-01

    Phasic activity of midbrain dopamine neurons is currently thought to encapsulate the prediction-error signal described in Sutton and Barto's (1981) model-free reinforcement learning algorithm. This phasic signal is thought to contain information about the quantitative value of reward, which transfers to the reward-predictive cue after learning. This is argued to endow the reward-predictive cue with the value inherent in the reward, motivating behavior toward cues signaling the presence of reward. Yet theoretical and empirical research has implicated prediction-error signaling in learning that extends far beyond a transfer of quantitative value to a reward-predictive cue. Here, we review the research which demonstrates the complexity of how dopaminergic prediction errors facilitate learning. After briefly discussing the literature demonstrating that phasic dopaminergic signals can act in the manner described by Sutton and Barto (1981), we consider how these signals may also influence attentional processing across multiple attentional systems in distinct brain circuits. Then, we discuss how prediction errors encode and promote the development of context-specific associations between cues and rewards. Finally, we consider recent evidence that shows dopaminergic activity contains information about causal relationships between cues and rewards that reflect information garnered from rich associative models of the world that can be adapted in the absence of direct experience. In discussing this research we hope to support the expansion of how dopaminergic prediction errors are thought to contribute to the learning process beyond the traditional concept of transferring quantitative value.

  10. A new approach to assess and predict the functional roles of proteins across all known structures.

    PubMed

    Julfayev, Elchin S; McLaughlin, Ryan J; Tao, Yi-Ping; McLaughlin, William A

    2011-03-01

    The three dimensional atomic structures of proteins provide information regarding their function; and codified relationships between structure and function enable the assessment of function from structure. In the current study, a new data mining tool was implemented that checks current gene ontology (GO) annotations and predicts new ones across all the protein structures available in the Protein Data Bank (PDB). The tool overcomes some of the challenges of utilizing large amounts of protein annotation and measurement information to form correspondences between protein structure and function. Protein attributes were extracted from the Structural Biology Knowledgebase and open source biological databases. Based on the presence or absence of a given set of attributes, a given protein's functional annotations were inferred. The results show that attributes derived from the three dimensional structures of proteins enhanced predictions over that using attributes only derived from primary amino acid sequence. Some predictions reflected known but not completely documented GO annotations. For example, predictions for the GO term for copper ion binding reflected used information a copper ion was known to interact with the protein based on information in a ligand interaction database. Other predictions were novel and require further experimental validation. These include predictions for proteins labeled as unknown function in the PDB. Two examples are a role in the regulation of transcription for the protein AF1396 from Archaeoglobus fulgidus and a role in RNA metabolism for the protein psuG from Thermotoga maritima.

  11. Surfactant-associated proteins: structure, function and clinical implications.

    PubMed

    Ketko, Anastasia K; Donn, Steven M

    2014-01-01

    Surfactant replacement therapy is now the standard of care for infants with respiratory distress syndrome. As the understanding of surfactant structure and function has evolved, surfactant-associated proteins are now understood to be essential components of pulmonary surfactant. Their structural and functional diversity detail the complexity of their contributions to normal pulmonary physiology, and deficiency states result in significant pathology. Engineering synthetic surfactant protein constructs has been a major research focus for replacement therapies. This review highlights what is known about surfactant proteins and how this knowledge is pivotal for future advancements in treating respiratory distress syndrome as well as other pulmonary diseases characterized by surfactant deficiency or inactivation.

  12. Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes

    PubMed Central

    Rowland, Jessica; Guan, Yuanfang; Bongo, Lars A.; Burdine, Rebecca D.; Troyanskaya, Olga G.

    2013-01-01

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

  13. Improved prediction of accessible surface area results in efficient energy function application.

    PubMed

    Iqbal, Sumaiya; Mishra, Avdesh; Hoque, Md Tamjidul

    2015-09-07

    An accurate prediction of real value accessible surface area (ASA) from protein sequence alone has wide application in the field of bioinformatics and computational biology. ASA has been helpful in understanding the 3-dimensional structure and function of a protein, acting as high impact feature in secondary structure prediction, disorder prediction, binding region identification and fold recognition applications. To enhance and support broad applications of ASA, we have made an attempt to improve the prediction accuracy of absolute accessible surface area by developing a new predictor paradigm, namely REGAd(3)p, for real value prediction through classical Exact Regression with Regularization and polynomial kernel of degree 3 which was further optimized using Genetic Algorithm. ASA assisting effective energy function, motivated us to enhance the accuracy of predicted ASA for better energy function application. Our ASA prediction paradigm was trained and tested using a new benchmark dataset, proposed in this work, consisting of 1001 and 298 protein chains, respectively. We achieved maximum Pearson Correlation Coefficient (PCC) of 0.76 and 1.45% improved PCC when compared with existing top performing predictor, SPINE-X, in ASA prediction on independent test set. Furthermore, we modeled the error between actual and predicted ASA in terms of energy and combined this energy linearly with the energy function 3DIGARS which resulted in an effective energy function, namely 3DIGARS2.0, outperforming all the state-of-the-art energy functions. Based on Rosetta and Tasser decoy-sets 3DIGARS2.0 resulted 80.78%, 73.77%, 141.24%, 16.52%, and 32.32% improvement over DFIRE, RWplus, dDFIRE, GOAP and 3DIGARS respectively.

  14. Neuropsychological Characteristics and Their Association with Higher-Level Functional Capacity in Parkinson's Disease

    PubMed Central

    Miura, Kayoko; Matsui, Mie; Takashima, Shutaro; Tanaka, Kortaro

    2015-01-01

    Background/Aims Little is known about the relationship between cognitive functions and higher-level functional capacity (e.g. intellectual activity, social role, and social participation) in Parkinson's disease (PD). The purpose of this study was to clarify neuropsychological characteristics and their association with higher-level functional capacity in PD patients. Methods Participants were 31 PD patients and 23 demographically matched healthy controls. Neuropsychological tests were conducted. One year later, a questionnaire survey evaluated higher-level functional capacity in daily living. Results The PD group scored significantly lower than the control group in all cognitive domains, particularly executive function and processing. Executive function, processing speed, language, and memory were significantly correlated with higher-level functional capacity in PD patients. Stepwise regression showed that only executive function (Trail Making Test-B), together with disease severity (HY stage), predicted the higher-level functional capacity. Conclusion Our findings provide evidence of a relationship between executive function and higher-level functional capacity in patients with PD. PMID:26273243

  15. The Meteoroid Input Function and predictions of mid-latitude meteor observations by the MU radar

    NASA Astrophysics Data System (ADS)

    Pifko, Steven; Janches, Diego; Close, Sigrid; Sparks, Jonathan; Nakamura, Takuji; Nesvorny, David

    2013-03-01

    The majority of extraterrestrial particles entering Earth’s atmosphere originate from the Sporadic Meteoroid Complex (SMC) and are associated with many mesospheric layer phenomena. The Meteoroid Input Function (MIF) is a model that has been developed with the purpose of understanding the temporal and spatial variability of the meteoroid impact in the atmosphere. The MIF has been shown to accurately predict the seasonal and diurnal variations of the meteor flux observed by High Power Large Aperture (HPLA) radars at various geographic locations, including the Arecibo Observatory (AO) and the Poker Flat Incoherent Scatter Radar (PFISR). For this, the model requires the assessment of a potential observational bias of the particular HPLA radar utilized: the minimum detectable radar cross-section (RCS). The RCS sensitivity threshold provides a metric to characterize the radar system’s ability to detect particles with a given mass and speed. In this paper, the MIF model was used to predict meteor properties (e.g. the distributions of areal density, speed, and radiant location) observed by the Middle and Upper atmosphere (MU) radar while leveraging the system’s interferometric capability to address the model’s ability to predict meteor observations at middle geographic latitudes and for a radar operating frequency in the low VHF band. This study demonstrates that the MIF accurately considered the speed and sporadic source distributions for the portion of the meteoroid population observable by the MU radar, and the applicability of the MIF to the MU system increases the confidence of using it as a global model.

  16. Utility of Urinary Biomarkers in Predicting Loss of Residual Renal Function: The balANZ Trial

    PubMed Central

    Cho, Yeoungjee; Johnson, David W.; Vesey, David A.; Hawley, Carmel M.; Clarke, Margaret; Topley, Nicholas

    2015-01-01

    ♦ Background: The ability of urinary biomarkers to predict residual renal function (RRF) decline in peritoneal dialysis (PD) patients has not been defined. The present study aimed to explore the utility of established biomarkers from kidney injury models for predicting loss of RRF in incident PD patients, and to evaluate the impact on RRF of using neutral-pH PD solution low in glucose degradation products. ♦ Methods: The study included 50 randomly selected participants from the balANZ trial who had completed 24 months of follow-up. A change in glomerular filtration rate (GFR) was used as the primary clinical outcome measure. In a mixed-effects general linear model, baseline measurements of 18 novel urinary biomarkers and albumin were used to predict GFR change. The model was further used to evaluate the impact of biocompatible PD solution on RRF, adjusted for each biomarker. ♦ Results: Baseline albuminuria was not a useful predictor of change in RRF in PD patients (p = 0.84). Only clusterin was a significant predictor of GFR decline in the whole population (p = 0.04, adjusted for baseline GFR and albuminuria). However, the relationship was no longer apparent when albuminuria was removed from the model (p = 0.31). When the effect of the administered PD solutions was examined using a model adjusted for PD solution type, baseline albuminuria, and GFR, higher baseline urinary concentrations of trefoil factor 3 (TFF3, p = 0.02), kidney injury molecule 1 (KIM-1, p = 0.04), and interferon γ-induced protein 10 (IP-10, p = 0.03) were associated with more rapid decline of RRF in patients receiving conventional PD solution compared with biocompatible PD solution. ♦ Conclusions: Higher urinary levels of kidney injury biomarkers (TFF3, KIM-1, IP-10) at baseline predicted significantly slower RRF decline in patients receiving biocompatible PD solutions. Findings from the present investigation should help to guide future studies to validate the utility of urinary

  17. Comparison of Local Information Indices Applied in Resting State Functional Brain Network Connectivity Prediction

    PubMed Central

    Cheng, Chen; Chen, Junjie; Cao, Xiaohua; Guo, Hao

    2016-01-01

    Anatomical distance has been widely used to predict functional connectivity because of the potential relationship between structural connectivity and functional connectivity. The basic implicit assumption of this method is “distance penalization.” But studies have shown that one-parameter model (anatomical distance) cannot account for the small-worldness, modularity, and degree distribution of normal human brain functional networks. Two local information indices–common neighbor (CN) and preferential attachment index (PA), are introduced into the prediction model as another parameter to emulate many key topological of brain functional networks in the previous study. In addition to these two indices, many other local information indices can be chosen for investigation. Different indices evaluate local similarity from different perspectives. Currently, we still have no idea about how to select local information indices to achieve higher predicted accuracy of functional connectivity. Here, seven local information indices are chosen, including CN, hub depressed index (HDI), hub promoted index (HPI), Leicht-Holme-Newman index (LHN-I), Sørensen index (SI), PA, and resource allocation index (RA). Statistical analyses were performed on eight network topological properties to evaluate the predictions. Analysis shows that different prediction models have different performances in terms of simulating topological properties and most of the predicted network properties are close to the real data. There are four topological properties whose average relative error is less than 5%, including characteristic path length, clustering coefficient, global efficiency, and local efficiency. CN model shows the most accurate predictions. Statistical analysis reveals that five properties within the CN-predicted network do not differ significantly from the real data (P > 0.05, false-discovery rate method corrected for seven comparisons). PA model shows the worst prediction performance

  18. Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

    PubMed Central

    Luo, Feng; Yang, Yunfeng; Zhong, Jianxin; Gao, Haichun; Khan, Latifur; Thompson, Dorothea K; Zhou, Jizhong

    2007-01-01

    recovery of gene co-expression network. Moreover, the cellular roles of 215 functionally unknown genes from yeast, E. coli and S. oneidensis are predicted by the gene co-expression networks using guilt-by-association principle, many of which are supported by existing information or our experimental verification, further demonstrating the reliability of this approach for gene function prediction. Conclusion Our rigorous analysis of gene expression microarray profiles using RMT has showed that the transition of NNSD of correlation matrix of microarray profile provides a profound theoretical criterion to determine the correlation threshold for identifying gene co-expression networks. PMID:17697349

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

    PubMed

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

    2015-09-01

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

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

    PubMed Central

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

    2016-01-01

    There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated: (1) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (2) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a two-minute resting period during which ECG was continually assessed. In the next phase, the women completed an array of executive function and non-executive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. PMID:26018941

  1. Biogenesis and Function of Ago-Associated RNAs.

    PubMed

    Daugaard, Iben; Hansen, Thomas Birkballe

    2017-03-01

    Numerous sophisticated high-throughput sequencing technologies have been developed over the past decade, and these have enabled the discovery of a diverse catalog of small non-coding (nc)RNA molecules that function as regulatory entities by associating with Argonaute (Ago) proteins. MicroRNAs (miRNAs) are currently the best-described class of post-transcriptional regulators that follow a specific biogenesis pathway characterized by Drosha/DGCR8 and Dicer processing. However, more exotic miRNA-like species that bypass particular steps of the canonical miRNA biogenesis pathway continue to emerge, with one of the most recent additions being the agotrons, which escape both Drosha/DGCR8- and Dicer-processing. We review here the current knowledge and most recent discoveries relating to alternative functions and biogenesis strategies for Ago-associated RNAs in mammals.

  2. The utility of pulmonary function testing in predicting outcomes following liver transplantation.

    PubMed

    Kia, Leila; Cuttica, Michael J; Yang, Amy; Donnan, Erica N; Whitsett, Maureen; Singhvi, Ajay; Lemmer, Alexander; Levitsky, Josh

    2016-06-01

    Although pulmonary function tests (PFTs) are routinely performed in patients during the evaluation period before liver transplantation (LT), their utility in predicting post-LT mortality and morbidity outcomes is not known. The aim of this study was to determine the impact of obstructive and/or restrictive lung disease on post-LT outcomes. We conducted a retrospective analysis of patients who had pre-LT PFTs and underwent a subsequent LT (2007-2013). We used statistical analyses to determine independent associations between PFT parameters and outcomes (graft/patient survival, time on ventilator, and hospital/intensive care unit [ICU] length of stay [LOS]). A total of 415 LT recipients with available PFT data were included: 65% of patients had normal PFTs; 8% had obstructive lung disease; and 27% had restrictive lung disease. There was no difference in patient and graft survival between patients with normal, obstructive, and restrictive lung disease. However, restrictive lung disease was associated with longer post-LT time on ventilator and both ICU and hospital LOS (P < 0.05). More specific PFT parameters (diffusing capacity of the lungs for carbon monoxide, total lung capacity, and residual volume) were all significant predictors of ventilator time and both ICU and hospital LOS (P < 0.05). Although pre-LT PFT parameters may not predict post-LT mortality, restrictive abnormalities correlate with prolonged post-LT ventilation and LOS. Efforts to identify and minimize the impact of restrictive abnormalities on PFTs might improve such outcomes. Liver Transplantation 22 805-811 2016 AASLD.

  3. Macrophage density in early surveillance biopsies predicts future renal transplant function.

    PubMed

    Bräsen, Jan Hinrich; Khalifa, Abedalrazag; Schmitz, Jessica; Dai, Wei; Einecke, Gunilla; Schwarz, Anke; Hallensleben, Michael; Schmidt, Bernhard M W; Kreipe, Hans H; Haller, Hermann; von Vietinghoff, Sibylle

    2017-03-27

    Inflammation impairs renal allograft survival but is difficult to quantify by eye at low densities. Here we measured leukocyte abundance in early surveillance biopsies by digital image analysis to test for a role of chemokine receptor genotypes and analyze the predictive value of leukocyte subsets to allograft function. In six-week surveillance biopsies, T-cell (CD3), B-cell (CD20), macrophage (CD68), and dendritic cell (CD209) densities were assessed in whole slide scans. Renal cortical CD3, CD20, and CD68 were significantly higher in histologic rejection. The CCR2 V64I genotype was associated with lower CD3 and CD209 densities. Above-median CD68 density was significantly associated with lower combined patient and graft survival with a hazard ratio of 3.5 (95% confidence interval 1.1-11.0). Both CD20 and CD68 densities inversely correlated with estimated glomerular filtration rate (eGFR) four years after transplantation. Additionally, CD68 correlated with eGFR loss. Among histological measurements including a complete Banff classification, only CD68 density was a significant predictor of an eGFR under 30ml/min after four years (odds ratio 7.4, 1.8-31.0) and part of the best eGFR prediction set in a multivariable linear regression analysis of multiple clinical and pathologic parameters. In a second independent cohort, the original CD68 median maintained its discriminative power for survival and eGFR. Thus, digital high-resolution assessment of CD68(+) leukocyte infiltration significantly improves prognostic value of early renal transplant biopsies.

  4. Gene Ontology consistent protein function prediction: the FALCON algorithm applied to six eukaryotic genomes.

    PubMed

    Kourmpetis, Yiannis Ai; van Dijk, Aalt Dj; Ter Braak, Cajo Jf

    2013-03-27

    : Gene Ontology (GO) is a hierarchical vocabulary for the description of biological functions and locations, often employed by computational methods for protein function prediction. Due to the structure of GO, function predictions can be self- contradictory. For example, a protein may be predicted to belong to a detailed functional class, but not in a broader class that, due to the vocabulary structure, includes the predicted one.We present a novel discrete optimization algorithm called Functional Annotation with Labeling CONsistency (FALCON) that resolves such contradictions. The GO is modeled as a discrete Bayesian Network. For any given input of GO term membership probabilities, the algorithm returns the most probable GO term assignments that are in accordance with the Gene Ontology structure. The optimization is done using the Differential Evolution algorithm. Performance is evaluated on simulated and also real data from Arabidopsis thaliana showing improvement compared to related approaches. We finally applied the FALCON algorithm to obtain genome-wide function predictions for six eukaryotic species based on data provided by the CAFA (Critical Assessment of Function Annotation) project.

  5. Functional classification of protein 3D structures from predicted local interaction sites.

    PubMed

    Parasuram, Ramya; Lee, Joslynn S; Yin, Pengcheng; Somarowthu, Srinivas; Ondrechen, Mary Jo

    2010-12-01

    A new approach to the functional classification of protein 3D structures is described with application to some examples from structural genomics. This approach is based on functional site prediction with THEMATICS and POOL. THEMATICS employs calculated electrostatic potentials of the query structure. POOL is a machine learning method that utilizes THEMATICS features and has been shown to predict accurate, precise, highly localized interaction sites. Extension to the functional classification of structural genomics proteins is now described. Predicted functionally important residues are structurally aligned with those of proteins with previously characterized biochemical functions. A 3D structure match at the predicted local functional site then serves as a more reliable predictor of biochemical function than an overall structure match. Annotation is confirmed for a structural genomics protein with the ribulose phosphate binding barrel (RPBB) fold. A putative glucoamylase from Bacteroides fragilis (PDB ID 3eu8) is shown to be in fact probably not a glucoamylase. Finally a structural genomics protein from Streptomyces coelicolor annotated as an enoyl-CoA hydratase (PDB ID 3g64) is shown to be misannotated. Its predicted active site does not match the well-characterized enoyl-CoA hydratases of similar structure but rather bears closer resemblance to those of a dehalogenase with similar fold.

  6. Compositional changes upon compression of sodium azide predicted using density functional theory

    NASA Astrophysics Data System (ADS)

    Steele, Brad; Landerville, Aaron; Oleynik, Ivan

    2014-03-01

    The pressure induced phase transitions in sodium azide, which include a potential polymeric nitrogen phase transition, are investigated using evolutionary crystal structure prediction methods coupled with density functional theory calculations. Two new phases are predicted to be stable above 53 GPa that have an inequivalent ratio of sodium to nitrogen atoms as compared to sodium azide. The Raman spectrum is calculated from 0-100 GPa using these newly predicted structures, as well as the newly discovered I4/mcm phase of sodium azide. The predicted Raman spectrum is shown to give good agreement to experimental data above 30 GPa and below 15 GPa.

  7. Association of social-environmental factors with cognitive function in children with sickle cell disease.

    PubMed

    Yarboi, Janet; Compas, Bruce E; Brody, Gene H; White, Desiree; Rees Patterson, Jenny; Ziara, Kristen; King, Allison

    2017-04-01

    The aim of this study was to examine the relationship between cognitive function in pediatric sickle cell disease (SCD) patients and mothers' reports of social-environmental stress, depressive symptoms, and parenting. A total of 65 children with SCD completed comprehensive neuropsychological testing to assess several domains of cognitive functioning, including general intellectual ability, academic achievement, and executive function. Mothers reported on demographics, social-environmental stress, depressive symptoms, and parenting. As predicted, children with SCD significantly underperformed relative to normative data on measures of cognitive function. Associations between maternal social-environmental stress, maternal depressive symptoms, and parenting were mixed. The results show partial support for the hypothesis that greater stress and depressive symptoms and less positive parenting are associated with poorer cognitive function in children with SCD. Linear regression analyses showed that maternal financial stress was the strongest predictor across all domains of cognitive function. The findings replicate and extend past research, reaffirming that children with SCD are at risk for cognitive impairment across multiple domains. Additionally, social-environmental stress, particularly financial strain, is linked to mothers' depressive symptoms and parenting behaviors as well as children's cognitive function. Future studies using direct observations of parenting behaviors are needed. These findings, along with recent research on parenting interventions, may inform the development of concrete, teachable parenting and coping skills to improve cognitive functioning in children with SCD.

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

    PubMed

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

    2016-01-01

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

  9. Cognitive Impairment Precedes and Predicts Functional Impairment in Mild Alzheimer’s Disease

    PubMed Central

    Liu-Seifert, Hong; Siemers, Eric; Price, Karen; Han, Baoguang; Selzler, Katherine J.; Henley, David; Sundell, Karen; Aisen, Paul; Cummings, Jeffrey; Raskin, Joel; Mohs, Richard

    2015-01-01

    Abstract Background: The temporal relationship of cognitive deficit and functional impairment in Alzheimer’s disease (AD) is not well characterized. Recent analyses suggest cognitive decline predicts subsequent functional decline throughout AD progression. Objective: To better understand the relationship between cognitive and functional decline in mild AD using autoregressive cross-lagged (ARCL) panel analyses in several clinical trials. Methods: Data included placebo patients with mild AD pooled from two multicenter, double-blind, Phase 3 solanezumab (EXPEDITION/2) or semagacestat (IDENTITY/2) studies, and from AD patients participating in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cognitive and functional outcomes were assessed using AD Assessment Scale-Cognitive subscale (ADAS-Cog), AD Cooperative Study-Activities of Daily Living instrumental subscale (ADCS-iADL), or Functional Activities Questionnaire (FAQ), respectively. ARCL panel analyses evaluated relationships between cognitive and functional impairment over time. Results: In EXPEDITION, ARCL panel analyses demonstrated cognitive scores significantly predicted future functional impairment at 5 of 6 time points, while functional scores predicted subsequent cognitive scores in only 1 of 6 time points. Data from IDENTITY and ADNI programs yielded consistent results whereby cognition predicted subsequent function, but not vice-versa. Conclusions: Analyses from three databases indicated cognitive decline precedes and predicts subsequent functional decline in mild AD dementia, consistent with previously proposed hypotheses, and corroborate recent publications using similar methodologies. Cognitive impairment may be used as a predictor of future functional impairment in mild AD dementia and can be considered a critical target for prevention strategies to limit future functional decline in the dementia process. PMID:26402769

  10. Growth failure and pituitary function in CHARGE and VATER associations

    PubMed Central

    Khadilkar, V; Cameron, F; Stanhope, R

    1999-01-01

    Growth failure and anterior pituitary dysfunction are clinical features of the CHARGE and VATER associations. This study investigated pituitary dysfunction as a potential cause of poor growth in a series of four and three patients with the CHARGE and VATER associations, respectively, who had height standard deviation scores (SDS) less than −2. Five of the seven patients had associated subnormal growth velocity SDS. Patients were investigated with a combination of dynamic and basal endocrine tests. All patients were found to be normonatraemic and to have normal basal thyrotroph and stimulated corticotroph function. The one peripubertal patient had evidence of biochemical gonadotroph dysfunction. Although two patients had marginally low stimulated serum growth hormone responses to glucagon stimulation testing, this was associated with either normal growth velocity or normal serum insulin-like growth factor binding protein 3 (IGFBP-3) concentrations. Thus, somatotroph dysfunction could not be demonstrated unequivocally in any patient. Poor childhood linear growth in the CHARGE and VATER associations does not appear to be associated with pituitary dysfunction.

 PMID:10325734

  11. Functional organization of telencephalic visual association fields in pigeons.

    PubMed

    Stacho, Martin; Ströckens, Felix; Xiao, Qian; Güntürkün, Onur

    2016-04-15

    Birds show remarkable visual abilities that surpass most of our visual psychophysiological abilities. In this study, we investigated visual associative areas of the tectofugal visual system in pigeons. Similar to the condition in mammals, ascending visual pathways in birds are subdivided into parallel form/color vs. motion streams at the thalamic and primary telencephalic level. However, we know practically nothing about the functional organization of those telencephalic areas that receive input from the primary visual telencephalic fields. The current study therefore had two objectives: first, to reveal whether these visual associative areas of the tectofugal system are activated during visual discrimination tasks; second, to test whether separated form/color vs. motion pathways can be discerned among these association fields. To this end, we trained pigeons to discriminate either form/color or motion stimuli and used the immediate early gene protein ZENK to capture the activity of the visual associative areas during the task. We could indeed identify several visual associative telencephalic structures by activity pattern changes during discriminations. However, none of these areas displayed a difference between form/color vs. motion sessions. The presence of such a distinction in thalamo-telencephalic, but not in further downstream visual association areas opens the possibility that these separate streams converge very early in birds, which possibly minimizes long-range connections due to the evolutionary pressure toward miniaturized brains.

  12. Position of the American Dietetic Association: functional foods.

    PubMed

    Hasler, Clare M; Brown, Amy C

    2009-04-01

    All foods are functional at some physiological level, but it is the position of the American Dietetic Association (ADA) that functional foods that include whole foods and fortified, enriched, or enhanced foods have a potentially beneficial effect on health when consumed as part of a varied diet on a regular basis, at effective levels. ADA supports research to further define the health benefits and risks of individual functional foods and their physiologically active components. Health claims on food products, including functional foods, should be based on the significant scientific agreement standard of evidence and ADA supports label claims based on such strong scientific substantiation. Food and nutrition professionals will continue to work with the food industry, allied health professionals, the government, the scientific community, and the media to ensure that the public has accurate information regarding functional foods and thus should continue to educate themselves on this emerging area of food and nutrition science. Knowledge of the role of physiologically active food components, from plant, animal, and microbial food sources, has changed the role of diet in health. Functional foods have evolved as food and nutrition science has advanced beyond the treatment of deficiency syndromes to reduction of disease risk and health promotion. This position paper reviews the definition of functional foods, their regulation, and the scientific evidence supporting this evolving area of food and nutrition. Foods can no longer be evaluated only in terms of macronutrient and micronutrient content alone. Analyzing the content of other physiologically active components and evaluating their role in health promotion will be necessary. The availability of health-promoting functional foods in the US diet has the potential to help ensure a healthier population. However, each functional food should be evaluated on the basis of scientific evidence to ensure appropriate integration

  13. Gene-Specific Function Prediction for Non-Synonymous Mutations in Monogenic Diabetes Genes

    PubMed Central

    Li, Quan; Liu, Xiaoming; Gibbs, Richard A.; Boerwinkle, Eric; Polychronakos, Constantin; Qu, Hui-Qi

    2014-01-01

    The rapid progress of genomic technologies has been providing new opportunities to address the need of maturity-onset diabetes of the young (MODY) molecular diagnosis. However, whether a new mutation causes MODY can be questionable. A number of in silico methods have been developed to predict functional effects of rare human mutations. The purpose of this study is to compare the performance of different bioinformatics methods in the functional prediction of nonsynonymous mutations in each MODY gene, and provides reference matrices to assist the molecular diagnosis of MODY. Our study showed that the prediction scores by different methods of the diabetes mutations were highly correlated, but were more complimentary than replacement to each other. The available in silico methods for the prediction of diabetes mutations had varied performances across different genes. Applying gene-specific thresholds defined by this study may be able to increase the performance of in silico prediction of disease-causing mutations. PMID:25136813

  14. Functional Coherence of Insula Networks is Associated with Externalizing Behavior

    PubMed Central

    Abram, Samantha V.; Wisner, Krista M.; Grazioplene, Rachael G.; Krueger, Robert F.; MacDonald, Angus W.; DeYoung, Colin G.

    2015-01-01

    The externalizing spectrum encompasses a range of maladaptive behaviors, including substance use problems, impulsivity, and aggression. While previous literature has linked externalizing behaviors with prefrontal and amygdala abnormalities, recent studies suggest insula functionality is implicated. The present study investigated the relation between insula functional coherence and externalizing in a large community sample (N=244). Participants underwent a resting functional magnetic resonance imaging scan. Three non-artifactual intrinsic connectivity networks (ICNs) substantially involving the insula were identified after completing independent components analysis. Three externalizing domains—general disinhibition, substance abuse, and callous aggression—were measured with the Externalizing Spectrum Inventory. Regression models tested whether within-network coherence for the three insula ICNs was related to each externalizing domain. Posterior insula coherence was positively associated with general disinhibition and substance abuse. Anterior insula/ventral striatum/anterior cingulate network coherence was negatively associated with general disinhibition. Insula coherence did not relate to the callous aggression domain. Follow-up analyses indicated specificity for insula ICNs in their relation to general disinhibition and substance abuse as compared to other frontal and limbic ICNs. This study found insula network coherence was significantly associated with externalizing behaviors in community participants. Frontal and limbic ICNs containing less insular cortex were not related to externalizing. Thus, the neural synchrony of insula networks may be central for understanding externalizing psychopathology. PMID:26301974

  15. A density functional theory for association of fluid molecules with a functionalized surface: fluid-wall single and double bonding

    NASA Astrophysics Data System (ADS)

    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.

  16. Association between symptomatic remission and functional outcome in first-episode schizophrenia.

    PubMed

    Bodén, Robert; Sundström, Johan; Lindström, Eva; Lindström, Leif

    2009-02-01

    Although operational criteria for remission in schizophrenia have recently been proposed, the association of this definition with broader functional outcome has not yet been established in first-episode patients. The severity criteria for remission consist of a score of mild or less on eight core symptoms of schizophrenia. We applied the severity criteria for remission to a sample of patients with first-episode schizophrenia (n=76) in order to explore the association with functional outcome five years after first presentation to mental healthcare. We evaluated whether other factors than those included in the remission definition predicted good function in logistic regression models. The discriminatory capacities for remission and other factors for good function were tested using C-statistics. The proportions of remitters and non-remitters having good function were 73% and 17%, respectively. Furthermore, remitters had a higher level of subjective satisfaction with life. In comparison with non-remission, symptomatic remission was strongly associated with good function: odds ratio 13.2, 95% confidence interval, 4.3 to 40.3. A duration of untreated psychosis of three months or less as compared with a longer duration was associated with having good function at a five-year follow-up independently of remission status. The discriminatory capacity for symptomatic remission between having good function vs. not was acceptable (C-statistic=0.78), which was significantly improved to an excellent discriminatory capacity by adding duration of untreated psychosis less than three months (C-statistic=0.83, p=0.04). In conclusion, core symptoms of schizophrenia have an important limiting effect on functioning and subjective life satisfaction in the early course of the illness.

  17. Quantification of protein group coherence and pathway assignment using functional association

    PubMed Central

    2011-01-01

    Background Genomics and proteomics experiments produce a large amount of data that are awaiting functional elucidation. An important step in analyzing such data is to identify functional units, which consist of proteins that play coherent roles to carry out the function. Importantly, functional coherence is not identical with functional similarity. For example, proteins in the same pathway may not share the same Gene Ontology (GO) terms, but they work in a coordinated fashion so that the aimed function can be performed. Thus, simply applying existing functional similarity measures might not be the best solution to identify functional units in omics data. Results We have designed two scores for quantifying the functional coherence by considering association of GO terms observed in two biological contexts, co-occurrences in protein annotations and co-mentions in literature in the PubMed database. The counted co-occurrences of GO terms were normalized in a similar fashion as the statistical amino acid contact potential is computed in the protein structure prediction field. We demonstrate that the developed scores can identify functionally coherent protein sets, i.e. proteins in the same pathways, co-localized proteins, and protein complexes, with statistically significant score values showing a better accuracy than existing functional similarity scores. The scores are also capable of detecting protein pairs that interact with each other. It is further shown that the functional coherence scores can accurately assign proteins to their respective pathways. Conclusion We have developed two scores which quantify the functional coherence of sets of proteins. The scores reflect the actual associations of GO terms observed either in protein annotations or in literature. It has been shown that they have the ability to accurately distinguish biologically relevant groups of proteins from random ones as well as a good discriminative power for detecting interacting pairs of

  18. The Predictive Utility of Early Childhood Disruptive Behaviors for School-Age Social Functioning

    PubMed Central

    Shaw, Daniel S.; Dishion, Thomas J.; Wilson, Melvin N.

    2016-01-01

    Research suggests that school-age children with disruptive behavior (DB) problems frequently demonstrate impaired social skills and experience rejection from peers, which plays a crucial role in the pathway to more serious antisocial behavior. A critical question is which DB problems in early childhood are prognostic of impaired social functioning in school-age children. This study examines the hypothesis that aggression in early childhood will be the more consistent predictor of compromised social functioning than inattentive, hyperactive-impulsive, or oppositional behavior. Participants included an ethnically diverse sample of 725 high-risk children from 3 geographically distinct areas followed from ages 2 to 8.5. Four latent growth models of DB from child ages 2 to 5, and potential interactions between dimensions, were used to predict latent parent and teacher ratings of school-age social dysfunction. Analyses were conducted in a multi-group format to examine potential differences between intervention and control group participants. Results showed that age 2 aggression was the DB problem most consistently associated with both parent- and teacher-rated social dysfunction for both groups. Early starting aggressive behavior may be particularly important for the early identification of children at risk for school-age social difficulties. PMID:25526865

  19. Distributed patterns of occipito-parietal functional connectivity predict the precision of visual working memory.

    PubMed

    Galeano Weber, Elena M; Hahn, Tim; Hilger, Kirsten; Fiebach, Christian J

    2017-02-01

    Limitations in visual working memory (WM) quality (i.e., WM precision) may depend on perceptual and attentional limitations during stimulus encoding, thereby affecting WM capacity. WM encoding relies on the interaction between sensory processing systems and fronto-parietal 'control' regions, and differences in the quality of this interaction are a plausible source of individual differences in WM capacity. Accordingly, we hypothesized that the coupling between perceptual and attentional systems affects the quality of WM encoding. We combined fMRI connectivity analysis with behavioral modeling by fitting a variable precision and fixed capacity model to the performance data obtained while participants performed a visual delayed continuous response WM task. We quantified functional connectivity during WM encoding between occipital and parietal brain regions activated during both perception and WM encoding, as determined using a conjunction of two independent experiments. The multivariate pattern of voxel-wise inter-areal functional connectivity significantly predicted WM performance, most specifically the mean of WM precision but not the individual number of items that could be stored in memory. In particular, higher occipito-parietal connectivity was associated with higher behavioral mean precision. These results are consistent with a network perspective of WM capacity, suggesting that the efficiency of information flow between perceptual and attentional neural systems is a critical determinant of limitations in WM quality.

  20. The Predictive Utility of Early Childhood Disruptive Behaviors for School-Age Social Functioning.

    PubMed

    Brennan, Lauretta M; Shaw, Daniel S; Dishion, Thomas J; Wilson, Melvin N

    2015-08-01

    Research suggests that school-age children with disruptive behavior (DB) problems frequently demonstrate impaired social skills and experience rejection from peers, which plays a crucial role in the pathway to more serious antisocial behavior. A critical question is which DB problems in early childhood are prognostic of impaired social functioning in school-age children. This study examines the hypothesis that aggression in early childhood will be the more consistent predictor of compromised social functioning than inattentive, hyperactive-impulsive, or oppositional behavior. Participants included an ethnically diverse sample of 725 high-risk children from 3 geographically distinct areas followed from ages 2 to 8.5. Four latent growth models of DB from child ages 2 to 5, and potential interactions between dimensions, were used to predict latent parent and teacher ratings of school-age social dysfunction. Analyses were conducted in a multi-group format to examine potential differences between intervention and control group participants. Results showed that age 2 aggression was the DB problem most consistently associated with both parent- and teacher-rated social dysfunction for both groups. Early starting aggressive behavior may be particularly important for the early identification of children at risk for school-age social difficulties.

  1. Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function

    SciTech Connect

    Xi, T; Jones, I M; Mohrenweiser, H W

    2003-11-03

    Over 520 different amino acid substitution variants have been previously identified in the systematic screening of 91 human DNA repair genes for sequence variation. Two algorithms were employed to predict the impact of these amino acid substitutions on protein activity. Sorting Intolerant From Tolerant (SIFT) classified 226 of 508 variants (44%) as ''Intolerant''. Polymorphism Phenotyping (PolyPhen) classed 165 of 489 amino acid substitutions (34%) as ''Probably or Possibly Damaging''. Another 9-15% of the variants were classed as ''Potentially Intolerant or Damaging''. The results from the two algorithms are highly associated, with concordance in predicted impact observed for {approx}62% of the variants. Twenty one to thirty one percent of the variant proteins are predicted to exhibit reduced activity by both algorithms. These variants occur at slightly lower individual allele frequency than do the variants classified as ''Tolerant'' or ''Benign''. Both algorithms correctly predicted the impact of 26 functionally characterized amino acid substitutions in the APE1 protein on biochemical activity, with one exception. It is concluded that a substantial fraction of the missense variants observed in the general human population are functionally relevant. These variants are expected to be the molecular genetic and biochemical basis for the associations of reduced DNA repair capacity phenotypes with elevated cancer risk.

  2. Dynamic functional connectivity shapes individual differences in associative learning.

    PubMed

    Fatima, Zainab; Kovacevic, Natasha; Misic, Bratislav; McIntosh, Anthony Randal

    2016-11-01

    Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc.

  3. Information theory applied to the sparse gene ontology annotation network to predict novel gene function

    PubMed Central

    Tao, Ying; Li, Jianrong

    2010-01-01

    Motivation Despite advances in the gene annotation process, the functions of a large portion of the gene products remain insufficiently characterized. In addition, the “in silico” prediction of novel Gene Ontology (GO) annotations for partially characterized gene functions or processes is highly dependent on reverse genetic or function genomics approaches. Results We propose a novel approach, Information Theory-based Semantic Similarity (ITSS), to automatically predict molecular functions of genes based on Gene Ontology annotations. We have demonstrated using a 10-fold cross-validation that the ITSS algorithm obtains prediction accuracies (Precision 97%, Recall 77%) comparable to other machine learning algorithms when applied to similarly dense annotated portions of the GO datasets. In addition, such method can generate highly accurate predictions in sparsely annotated portions of GO, in which previous algorithm failed to do so. As a result, our technique generates an order of magnitude more gene function predictions than previous methods. Further, this paper presents the first historical rollback validation for the predicted GO annotations, which may represent more realistic conditions for an evaluation than generally used cross-validations type of evaluations. By manually assessing a random sample of 100 predictions conducted in a historical roll-back evaluation, we estimate that a minimum precision of 51% (95% confidence interval: 43%–58%) can be achieved for the human GO Annotation file dated 2003. Availability The program is available on request. The 97,732 positive predictions of novel gene annotations from the 2005 GO Annotation dataset are available at http://phenos.bsd.uchicago.edu/mphenogo/prediction_result_2005.txt. PMID:17646340

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

    PubMed Central

    Choi, Sungkyoung; Bae, Sunghwan

    2016-01-01

    The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes. PMID:28154504

  5. Predictive criteria to study the pathogenesis of malaria-associated ALI/ARDS in mice.

    PubMed

    Ortolan, Luana S; Sercundes, Michelle K; Barboza, Renato; Debone, Daniela; Murillo, Oscar; Hagen, Stefano C F; Russo, Momtchilo; D' Império Lima, Maria Regina; Alvarez, José M; Amaku, Marcos; Marinho, Claudio R F; Epiphanio, Sabrina

    2014-01-01

    Malaria-associated acute lung injury/acute respiratory distress syndrome (ALI/ARDS) often results in morbidity and mortality. Murine models to study malaria-associated ALI/ARDS have been described; we still lack a method of distinguishing which mice will develop ALI/ARDS before death. This work aimed to characterize malaria-associated ALI/ARDS in a murine model and to demonstrate the first method to predict whether mice are suffering from ALI/ARDS before death. DBA/2 mice infected with Plasmodium berghei ANKA developing ALI/ARDS or hyperparasitemia (HP) were compared using histopathology, PaO2 measurement, pulmonary X-ray, breathing capacity, lung permeability, and serum vascular endothelial growth factor (VEGF) levels according to either the day of death or the suggested predictive criteria. We proposed a model to predict malaria-associated ALI/ARDS using breathing patterns (enhanced pause and frequency respiration) and parasitemia as predictive criteria from mice whose cause of death was known to retrospectively diagnose the sacrificed mice as likely to die of ALI/ARDS as early as 7 days after infection. Using this method, we showed increased VEGF levels and increased lung permeability in mice predicted to die of ALI/ARDS. This proposed method for accurately identifying mice suffering from ALI/ARDS before death will enable the use of this model to study the pathogenesis of this disease.

  6. Predictive Criteria to Study the Pathogenesis of Malaria-Associated ALI/ARDS in Mice

    PubMed Central

    Ortolan, Luana S.; Sercundes, Michelle K.; Debone, Daniela; Hagen, Stefano C. F.; D' Império Lima, Maria Regina; Alvarez, José M.; Marinho, Claudio R. F.; Epiphanio, Sabrina

    2014-01-01

    Malaria-associated acute lung injury/acute respiratory distress syndrome (ALI/ARDS) often results in morbidity and mortality. Murine models to study malaria-associated ALI/ARDS have been described; we still lack a method of distinguishing which mice will develop ALI/ARDS before death. This work aimed to characterize malaria-associated ALI/ARDS in a murine model and to demonstrate the first method to predict whether mice are suffering from ALI/ARDS before death. DBA/2 mice infected with Plasmodium berghei ANKA developing ALI/ARDS or hyperparasitemia (HP) were compared using histopathology, PaO2 measurement, pulmonary X-ray, breathing capacity, lung permeability, and serum vascular endothelial growth factor (VEGF) levels according to either the day of death or the suggested predictive criteria. We proposed a model to predict malaria-associated ALI/ARDS using breathing patterns (enhanced pause and frequency respiration) and parasitemia as predictive criteria from mice whose cause of death was known to retrospectively diagnose the sacrificed mice as likely to die of ALI/ARDS as early as 7 days after infection. Using this method, we showed increased VEGF levels and increased lung permeability in mice predicted to die of ALI/ARDS. This proposed method for accurately identifying mice suffering from ALI/ARDS before death will enable the use of this model to study the pathogenesis of this disease. PMID:25276057

  7. Reactive oxygen species–associated molecular signature predicts survival in patients with sepsis

    PubMed Central

    Zhou, Tong; Wang, Ting; Slepian, Marvin J.; Garcia, Joe G. N.; Hecker, Louise

    2016-01-01

    Abstract Sepsis-related multiple organ dysfunction syndrome is a leading cause of death in intensive care units. There is overwhelming evidence that oxidative stress plays a significant role in the pathogenesis of sepsis-associated multiple organ failure; however, reactive oxygen species (ROS)–associated biomarkers and/or diagnostics that define mortality or predict survival in sepsis are lacking. Lung or peripheral blood gene expression analysis has gained increasing recognition as a potential prognostic and/or diagnostic tool. The objective of this study was to identify ROS-associated biomarkers predictive of survival in patients with sepsis. In-silico analyses of expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients. Importantly, this signature performed well in a validation cohort consisting of sepsis patients aggregated from distinct patient populations recruited from different sites. Our signature outperforms randomly generated signatures of the same signature gene size. Our findings further validate the critical role of ROSs in the pathogenesis of sepsis and provide a novel gene signature that predicts survival in sepsis patients. These results also highlight the utility of peripheral blood molecular signatures as biomarkers for predicting mortality risk in patients with sepsis, which could facilitate the development of personalized therapies. PMID:27252846

  8. Lifestyle Factors Associated with Cognitive Functioning in Breast Cancer Survivors

    PubMed Central

    Hartman, Sheri J.; Marinac, Catherine R.; Natarajan, Loki; Patterson, Ruth E.

    2014-01-01

    Objective Weight, physical activity, and sleep are modifiable lifestyle factors that impact cognitive functioning in non-cancer populations, but have yet to be examined in cancer survivors. The aim of the study was to assess the relationship of obesity, physical activity, and sleep, with cognitive functioning among breast cancer survivors. Methods Participants were 136 early-stage post-menopausal breast cancer survivors who completed an assessment of neuropsychological testing, height, weight, physical activity and sleep. Linear regression models examined the associations of the seven neuropsychological domains with obesity, physical activity, and sleep. Logistic regression models examined odd of impairment in each domain. All models controlled for breast cancer treatment variables and relevant demographic and clinical variables. Results Obese participants had significantly worse performance (β=−5.04, SE=2.53) and were almost 3 times more likely to be impaired (OR=2.87; 95% CI:1.02–8.10) on the Information Processing domain. The highest tertile of physical activity was significantly related to better performance on the Executive Functioning domain (β=5.13, SE=2.42) and Attention domain (β=4.26, SE=2.07). The middle tertile of physical activity was significantly related to better performance (β=9.00, SE=3.09) and decreased odds of impairment (OR=0.89, 95% CI:0.07–0.91) on the Visual Spatial domain. More hours of sleep per night was significantly associated with better performance (β = 2.69, SE=0.98) and decreased odds of impairment (OR=0.52; 95% CI:0.33–0.82) on the Verbal Functioning domain. Conclusions These findings suggest that obesity, physical activity, and sleep are related to cognitive functioning among breast cancer survivors and have potential to be intervention targets to improve cognitive functioning. PMID:25073541

  9. Protein function prediction by massive integration of evolutionary analyses and multiple data sources

    PubMed Central

    2013-01-01

    Background Accurate protein function annotation is a severe bottleneck when utilizing the deluge of high-throughput, next generation sequencing data. Keeping database annotations up-to-date has become a major scientific challenge that requires the development of reliable automatic predictors of protein function. The CAFA experiment provided a unique opportunity to undertake comprehensive 'blind testing' of many diverse approaches for automated function prediction. We report on the methodology we used for this challenge and on the lessons we learnt. Methods Our method integrates into a single framework a wide variety of biological information sources, encompassing sequence, gene expression and protein-protein interaction data, as well as annotations in UniProt entries. The methodology transfers functional categories based on the results from complementary homology-based and feature-based analyses. We generated the final molecular function and biological process assignments by combining the initial predictions in a probabilistic manner, which takes into account the Gene Ontology hierarchical structure. Results We propose a novel scoring function called COmbined Graph-Information Content similarity (COGIC) score for the comparison of predicted functional categories and benchmark data. We demonstrate that our integrative approach provides increased scope and accuracy over both the component methods and the naïve predictors. In line with previous studies, we find that molecular function predictions are more accurate than biological process assignments. Conclusions Overall, the results indicate that there is considerable room for improvement in the field. It still remains for the community to invest a great deal of effort to make automated function prediction a useful and routine component in the toolbox of life scientists. As already witnessed in other areas, community-wide blind testing experiments will be pivotal in establishing standards for the evaluation of

  10. How Homes Influence Schools: Early Parenting Predicts African American Children's Classroom Social-Emotional Functioning

    ERIC Educational Resources Information Center

    Baker, Claire E.; Rimm-Kaufman, Sara E.

    2014-01-01

    Data from the Early Childhood Longitudinal Study, Kindergarten Cohort were used to examine the extent to which early parenting predicted African American children's kindergarten social-emotional functioning. Teachers rated children's classroom social-emotional functioning in four areas (i.e., approaches to learning, self-control, interpersonal…

  11. Structure function attributes of gold nanoparticle vaccine association: effect of particle size and association temperature.

    PubMed

    Barhate, Ganesh A; Gaikwad, Sushama M; Jadhav, Suresh S; Pokharkar, Varsha B

    2014-08-25

    Many biotherapeutic applications of gold nanoparticles make use of conjugated or adsorbed protein moieties. Physical parameters of association such as particle size, morphology, surface chemistry and temperature influences the protein-nanoparticle association and thereby their interaction with the biological environment. In present study, effect of size of chitosan reduced gold nanoparticles (CsAuNPs) and association temperature on structure and function of tetanus toxoid (TT) vaccine has been investigated. CsAuNPs were synthesized in the sizes of 20±3, 40±5 and 80±7 nm followed by loading of TT. Binding process of CsAuNPs with TT was investigated at their predetermined micro molar concentrations. Upon binding of TT onto CsAuNPs, particle surface was characterized using X-ray photoelectron spectroscopy. CD spectroscopic evaluation of TT bound 20 nm CsAuNPs led to 75% reduction in secondary structure of TT and thereby compromised immune function. Binding of TT with 40 and 80 nm sized CsAuNPs did not cause significant modifications in secondary structure or function of TT. Thermodynamic studies using temperature dependent fluorescence spectroscopy revealed an increase in association constants with the temperature. Based on thermodynamic data three phases in CsAuNPs and TT association process were traced. Samples from these distinct phases were also investigated for immunological recognition. Ex-vivo interaction of TT-CsAuNPs with TT positive and negative sera followed by relative change in particle size and zeta potential was studied. The findings here suggests prominent role of particle size and association temperature on adsorbed TT structure and function. Such studies may help in engineering functional nanotherapeutics.

  12. Prediction of Functional Class of Proteins and Peptides Irrespective of Sequence Homology by Support Vector Machines

    PubMed Central

    Tang, Zhi Qun; Lin, Hong Huang; Zhang, Hai Lei; Han, Lian Yi; Chen, Xin; Chen, Yu Zong

    2007-01-01

    Various computational methods have been used for the prediction of protein and peptide function based on their sequences. A particular challenge is to derive functional properties from sequences that show low or no homology to proteins of known function. Recently, a machine learning method, support vector machines (SVM), have been explored for predicting functional class of proteins and peptides from amino acid sequence derived properties independent of sequence similarity, which have shown promising potential for a wide spectrum of protein and peptide classes including some of the low- and non-homologous proteins. This method can thus be explored as a potential tool to complement alignment-based, clustering-based, and structure-based methods for predicting protein function. This article reviews the strategies, current progresses, and underlying difficulties in using SVM for predicting the functional class of proteins. The relevant software and web-servers are described. The reported prediction performances in the application of these methods are also presented. PMID:20066123

  13. Predicted functional RNAs within coding regions constrain evolutionary rates of yeast proteins.

    PubMed

    Warden, Charles D; Kim, Seong-Ho; Yi, Soojin V

    2008-02-13

    Functional RNAs (fRNAs) are being recognized as an important regulatory component in biological processes. Interestingly, recent computational studies suggest that the number and biological significance of functional RNAs within coding regions (coding fRNAs) may have been underestimated. We hypothesized that such coding fRNAs will impose additional constraint on sequence evolution because the DNA primary sequence has to simultaneously code for functional RNA secondary structures on the messenger RNA in addition to the amino acid codons for the protein sequence. To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes. We predict that as much as 5% of the genes in the yeast genome contain at least one functional RNA secondary structure within their protein-coding region. We then analyzed the impact of coding fRNAs on the evolutionary rate of protein-coding genes because a decrease in evolutionary rate implies constraint due to biological functionality. We found that our predicted coding fRNAs have a significant influence on evolutionary rates (especially at synonymous sites), independent of other functional measures. Thus, coding fRNA may play a role on sequence evolution. Given that coding regions of humans and flies contain many more predicted coding fRNAs than yeast, the impact of coding fRNAs on sequence evolution may be substantial in genomes of higher eukaryotes.

  14. Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity.

    PubMed

    Chen, Xing; Yan, Chenggang Clarence; Luo, Cai; Ji, Wen; Zhang, Yongdong; Dai, Qionghai

    2015-06-10

    Increasing evidence has indicated that plenty of lncRNAs play important roles in many critical biological processes. Developing powerful computational models to construct lncRNA functional similarity network based on heterogeneous biological datasets is one of the most important and popular topics in the fields of both lncRNAs and complex diseases. Functional similarity network construction could benefit the model development for both lncRNA function inference and lncRNA-disease association identification. However, little effort has been attempted to analysis and calculate lncRNA functional similarity on a large scale. In this study, based on the assumption that functionally similar lncRNAs tend to be associated with similar diseases, we developed two novel lncRNA functional similarity calculation models (LNCSIM). LNCSIM was evaluated by introducing similarity scores into the model of Laplacian Regularized Least Squares for LncRNA-Disease Association (LRLSLDA) for lncRNA-disease association prediction. As a result, new predictive models improved the performance of LRLSLDA in the leave-one-out cross validation of various known lncRNA-disease associations datasets. Furthermore, some of the predictive results for colorectal cancer and lung cancer were verified by independent biological experimental studies. It is anticipated that LNCSIM could be a useful and important biological tool for human disease diagnosis, treatment, and prevention.

  15. Structural and functional connectivity in healthy aging: Associations for cognition and motor behavior.

    PubMed

    Hirsiger, Sarah; Koppelmans, Vincent; Mérillat, Susan; Liem, Franziskus; Erdeniz, Burak; Seidler, Rachael D; Jäncke, Lutz

    2016-03-01

    Age-related behavioral declines may be the result of deterioration of white matter tracts, affecting brain structural (SC) and functional connectivity (FC) during resting state. To date, it is not clear if the combination of SC and FC data could better predict cognitive/motor performance than each measure separately. We probed these relationships in the cingulum bundle, a major white matter pathway of the default mode network. We aimed to attain deeper knowledge about: (a) the relationship between age and the cingulum's SC and FC strength, (b) the association between SC and FC, and particularly (c) how the cingulum's SC and FC are related to cognitive/motor performance separately and combined. We examined these associations in a healthy and well-educated sample of 165 older participants (aged 64-85). SC and FC were acquired using probabilistic tractography to derive measures to capture white matter integrity within the cingulum bundle (fractional anisotropy, mean, axial and radial diffusivity) and a seed-based resting-state functional MRI correlation approach, respectively. Participants performed cognitive tests measuring processing speed, memory and executive functions, and motor tests measuring motor speed and grip force. Our data revealed that only SC but not resting state FC was significantly associated with age. Further, the cingulum's SC and FC showed no relation. Different relationships between cognitive/motor performance and SC/FC separately were found, but no additive effect of the combined analysis of cingulum's SC and FC for predicting cognitive/motor performance was apparent.

  16. Synthesis and phase behavior of end-functionalized associating polymers

    NASA Astrophysics Data System (ADS)

    Wrue, Michelle H.

    chemical cleavage of the end-groups resulted in Tgs near those observed for polymer standards of comparable molecular weight. Aggregation of UPy end-groups in solution was observed using gel permeation chromatography. Aggregation was only observed for telechelic samples of low molecular weight, indicating that the aggregation of end-groups is dependent upon the concentration of the end-groups. The effect of UPy end-groups on blend miscibility was studied in solution using laser light scattering and in the melt state was using laser light scattering, optical microscopy and differential scanning calorimetry. The incorporation of associating groups onto one end of either blend component decreases miscibility relative to unfunctionalized parent blends. Lower miscibility was also observed for blends in which both components were mono-functionalized with associating end-groups. The largest decrease in miscibility was observed for blends containing telechelic UPy-functionalized polymers, which were immiscible across the entire composition range.

  17. Mini-Nutritional Assessment predicts functional decline of elderly Taiwanese: result of a population-representative sample.

    PubMed

    Lee, Li-Chin; Tsai, Alan C

    2012-06-01

    Nutrition is a key element in geriatric health and is important for functional ability. The present study examined the functional status-predictive ability of the Mini-Nutritional Assessment (MNA). We analysed the dataset of the 'Survey of Health and Living Status of the Elderly in Taiwan', a population-based study conducted by the Bureau of Health Promotion of Taiwan. Study subjects (≥65 years old) who completed both the 1999 and 2003 surveys were rated with the long form and short form of the MNA at baseline and with the Activities of Daily Living (ADL) and the Instrument Activities of Daily Living (IADL) scales 4 years later (end-point). The ability of the MNA to predict ADL or IADL dependency was evaluated with logistic regression models. The results showed that the elderly who were rated malnourished or at risk of malnutrition at baseline generally had significantly higher ADL or IADL scores 4 years later. Lower baseline MNA scores also predicted a greater risk of ADL or IADL dependency. These associations exist even among the elderly who were free of ADL or IADL dependency at baseline. The results clearly indicate that the MNA is able to predict ADL and IADL dependency (in addition to rating current nutritional status) of the elderly. The MNA, especially the short form, should be a valuable tool for identifying elderly at risk of functional decline and/or malnutrition in clinical practice or community programmes.

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

    PubMed

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

    2016-06-01

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

  19. Predictability of the Seasonal Climate Associated with ENSO in NCEP Climate Forecast System

    NASA Astrophysics Data System (ADS)

    Zhang, Q.

    2005-05-01

    The predictability of seasonal climate associated with ENSO is studied for NCEP Climate Forecast System (CFS) 23-year retrospective forecasts. Warm-minus-cold composites of the lead 1-6 month sea surface temperature (SST) anomalies show an ENSO-like horse-shoes pattern in the tropical Pacific, comparable with observation. There is a corresponding increased precipitation band along the equator near the dateline extending eastward to the South American coast, as well as the less precipitation over the Maritime Continents and off-equatorial western Pacific. Extended empirical orthogonal function (EEOF) analysis of the SST anomaly recovers ENSO -like dominant mode in the tropics for all seasons. Identification of patterns that optimize the signal-to-noise ratio is obtained by linear regression of the ensemble means on the principal component (PC) time series of SST. The optimized height patterns for boreal winter and spring are similar, although the winter response over the northern extratropics is somewhat weaker. Some subtle changes in amplitude are found in difference of leading initial conditions. The signal-to-noise ratio is significantly greater than unity in the Tropics (all seasons), the northern Pacific and continental North America subtropics (boreal winter and spring), and the southern Pacific subtropics (boreal fall).

  20. INTEGRATIVE ANALYSIS FOR LUNG ADENOCARCINOMA PREDICTS MORPHOLOGICAL FEATURES ASSOCIATED WITH GENETIC VARIATIONS*

    PubMed Central

    WANG, CHAO; SU, HAI; YANG, LIN; HUANG, KUN

    2016-01-01

    Lung cancer is one of the most deadly cancers and lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. However, LUAD is highly heterogeneous due to genetic difference as well as phenotypic differences such as cellular and tissue morphology. In this paper, we systematically examine the relationships between histological features and gene transcription. Specifically, we calculated 283 morphological features from histology images for 201 LUAD patients from TCGA project and identified the morphological feature with strong correlation with patient outcome. We then modeled the morphology feature using multiple co-expressed gene clusters using Lasso-regression. Many of the gene clusters are highly associated with genetic variations, specifically DNA copy number variations, implying that genetic variations play important roles in the development cancer morphology. As far as we know, our finding is the first to directly link the genetic variations and functional genomics to LUAD histology. These observations will lead to new insight on lung cancer development and potential new integrative biomarkers for prediction patient prognosis and response to treatments. PMID:27896964

  1. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

    PubMed

    Wang, Ming; Long, Qi

    2016-09-01

    Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations.

  2. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic

    PubMed Central

    Wang, Ming; Long, Qi

    2016-01-01

    Summary Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c–statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy are assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. PMID:26756274

  3. Association between binge eating disorder and changes in cognitive functioning following bariatric surgery.

    PubMed

    Lavender, Jason M; Alosco, Michael L; Spitznagel, Mary Beth; Strain, Gladys; Devlin, Michael; Cohen, Ronald; Paul, Robert; Crosby, Ross D; Mitchell, James E; Wonderlich, Stephen A; Gunstad, John

    2014-12-01

    Evidence suggests that both obesity and binge eating disorder (BED) may be associated with deficits in cognitive functioning. The purpose of this study was to examine whether a lifetime history of BED would be associated with changes in several domains of cognitive functioning (attention, executive function, language, and memory) following bariatric surgery. Participants were 68 bariatric surgery patients who completed a computerized battery of cognitive tests within 30 days prior to undergoing surgery and again at a 12-Month postoperative follow-up. Results revealed that on the whole, participants displayed improvements from baseline to follow-up in attention, executive function, and memory, even after controlling for diagnostic history of depression; no changes were observed for language. However, individuals with and without a history of BED did not differ in changes in body mass index or in the degree of improvement in cognitive functioning from baseline to follow-up. Such results suggest that a history of BED does not influence changes in cognitive functioning following bariatric surgery. Future research will be needed to further clarify the role of BED in predicting cognitive function over time.

  4. Executive function predicts the development of play skills for verbal preschoolers with autism spectrum disorders.

    PubMed

    Faja, Susan; Dawson, Geraldine; Sullivan, Katherine; Meltzoff, Andrew N; Estes, Annette; Bernier, Raphael

    2016-12-01

    Executive function and play skills develop in early childhood and are linked to cognitive and language ability. The present study examined these abilities longitudinally in two groups with autism spectrum disorder-a group with higher initial language (n = 30) and a group with lower initial language ability (n = 36). Among the lower language group, concurrent nonverbal cognitive ability contributed most to individual differences in executive function and play skills. For the higher language group, executive function during preschool significantly predicted play ability at age 6 over and above intelligence, but early play did not predict later executive function. These results suggested that factors related to the development of play and executive function differ for subgroups of children with different language abilities and that early executive function skills may be critical in order for verbal children with autism to develop play. Autism Res 2016, 9: 1274-1284. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

  5. Functional Imaging of Implicit Marijuana Associations during performance on an Implicit Association Test (IAT)

    PubMed Central

    Ames, Susan L.; Grenard, Jerry L.; Stacy, Alan W.; Xiao, Lin; He, Qinghua; Wong, Savio W.; Xue, Gui; Wiers, Reinout W.; Bechara, Antoine

    2013-01-01

    This research evaluated the neural correlates of implicit associative memory processes (habit-based processes) through the imaging (fMRI) of a marijuana Implicit Association Test. Drug-related associative memory effects have been shown to consistently predict level of drug use. To observe differences in neural activity of associative memory effects, this study compared 13 heavy marijuana users and 15 non-using controls, ranging in age from 18 to 25, during performance of a marijuana Implicit Association Test (IAT). Group by condition interactions in the putamen, caudate, and right inferior frontal gyrus were observed. Relative to non-users, marijuana users showed greater bilateral activity in the dorsal striatum (caudate and putamen) during compatible trials focused on perceived positive outcomes of use. Alternatively, relative to the marijuana-using group, the non-users showed greater activity in the right inferior frontal gyrus during incompatible trials, which require more effortful processing of information. Further, relative to fixation, heavy users showed bilateral activity in the caudate and putamen, hippocampus and some frontal regions during compatible trials and no significant activity during incompatible trials. The non-using group showed greater activity in frontal regions during incompatible trials relative to fixation and no significant activity during compatible trials. These findings are consistent with a dual process framework of appetitive behaviors proposing that (1) implicit associations underlying habit are mediated through neural circuitry dependent on the striatum, and (2) deliberative/controlled behaviors are mediated through circuitry more dependent on the prefrontal cortex. PMID:24029699

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

    PubMed

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

    2011-12-01

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

  7. Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI.

    PubMed

    Crane, Natania A; Jenkins, Lisanne M; Bhaumik, Runa; Dion, Catherine; Gowins, Jennifer R; Mickey, Brian J; Zubieta, Jon-Kar; Langenecker, Scott A

    2017-02-01

    Predicting treatment response for major depressive disorder can provide a tremendous benefit for our overstretched health care system by reducing number of treatments and time to remission, thereby decreasing morbidity. The present study used neural and performance predictors during a cognitive control task to predict treatment response (% change in Hamilton Depression Rating Scale pre- to post-treatment). Forty-nine individuals diagnosed with major depressive disorder were enrolled with intent to treat in the open-label study; 36 completed treatment, had useable data, and were included in most data analyses. Participants included in the data analysis sample received treatment with escitalopram (n = 22) or duloxetine (n = 14) for 10 weeks. Functional MRI and performance during a Parametric Go/No-go test were used to predict per cent reduction in Hamilton Depression Rating Scale scores after treatment. Haemodynamic response function-based contrasts and task-related independent components analysis (subset of sample: n = 29) were predictors. Independent components analysis component beta weights and haemodynamic response function modelling activation during Commission errors in the rostral and dorsal anterior cingulate, mid-cingulate, dorsomedial prefrontal cortex, and lateral orbital frontal cortex predicted treatment response. In addition, more commission errors on the task predicted better treatment response. Together in a regression model, independent component analysis, haemodynamic response function-modelled, and performance measures predicted treatment response with 90% accuracy (compared to 74% accuracy with clinical features alone), with 84% accuracy in 5-fold, leave-one-out cross-validation. Convergence between performance markers and functional magnetic resonance imaging, including novel independent component analysis techniques, achieved high accuracy in prediction of treatment response for major depressive disorder. The strong link to a task paradigm

  8. Renal function is independently associated with circulating betatrophin

    PubMed Central

    Maurer, Lukas; Schwarz, Franziska; Fischer-Rosinsky, Antje; Schlueter, Nina; Brachs, Sebastian; Möhlig, Matthias; Pfeiffer, Andreas; Mai, Knut; Bobbert, Thomas

    2017-01-01

    Objective Betatrophin has been identified as a marker linking liver with beta cell function and lipid metabolism in murine models. Until now, the regulation of circulating betatrophin in humans is not entirely clear. We here analyzed the relation of betatrophin levels to phenotypes of the metabolic syndrome and speculated that renal function might influence circulating betatrophin levels and explain age-dependent changes of betatrophin. Subjects We analyzed blood samples from 535 individuals participating in the Metabolic Syndrome Berlin Potsdam study. Results In a crude analysis we found a positive correlation between betatrophin levels and HbA1c (r = 0.24; p < 0.001), fasting glucose (r = 0.20; p < 0.001) and triglycerides (r = 0.12; p = 0.007). Furthermore betatrophin was positively correlated with age (r = 0.47; p <0.001), systolic blood pressure (r = 0.17; p < 0.001), intima media thickness (r = 0.26; p < 0.001) and negatively correlated with CKD-EPI eGFR (r = -0.33; p < 0.001) as an estimate of renal function. Notably, eGFR remained highly associated with betatrophin after adjustment for age, waist circumference, gender, HbA1c and lipid parameters in a multivariate linear regression model (β = -0.197, p< 0.001). Conclusions Our data suggest that circulating levels of betatrophin depend on age, gender, waist circumference, total/HDL cholesterol ratio and renal function. Especially the association to eGFR highlights the importance for future studies to address renal function as possible influence on betatrophin regulation and consider eGFR as potential confounder when analyzing the role of betatrophin in humans. PMID:28257453

  9. Circulating humanin levels are associated with preserved coronary endothelial function

    PubMed Central

    Widmer, R. J.; Flammer, A. J.; Herrmann, J.; Rodriguez-Porcel, M.; Wan, J.; Cohen, P.; Lerman, L. O.

    2013-01-01

    Humanin is a small endogenous antiapoptotic peptide, originally identified as protective against Alzheimer's disease, but subsequently also found on human endothelium as well as carotid artery plaques. Endothelial dysfunction is a precursor to the development of atherosclerotic plaques, which are characterized by a highly proinflammatory, reactive oxygen species, and apoptotic milieu. Previous animal studies demonstrated that humanin administration may improve endothelial function. Thus the aim of this study was to test the hypothesis that patients with coronary endothelial dysfunction have reduced systemic levels of humanin. Forty patients undergoing coronary angiography and endothelial function testing were included and subsequently divided into two groups based on coronary blood flow (CBF) response to intracoronary acetylcholine (normal ≥ 50% increase from baseline, n = 20 each). Aortic plasma samples were obtained at the time of catheterization for the analysis of humanin levels and traditional biomarkers of atherosclerosis including C-reactive protein, Lp-Pla2, and homocysteine. Baseline characteristics were similar in both groups. Patients with coronary endothelial dysfunction (change in CBF = −33 ± 25%) had significantly lower humanin levels (1.3 ± 1.1 vs. 2.2 ± 1.5 ng/ml, P = 0.03) compared with those with normal coronary endothelial function (change in CBF = 194 ± 157%). There was a significant and positive correlation between improved CBF and humanin levels (P = 0.0091) not seen with changes in coronary flow reserve (P = 0.76). C-reactive protein, Lp-Pla2, and homocysteine were not associated with humanin levels. Thus we observed that preserved human coronary endothelial function is uniquely associated with higher systemic humanin levels, introducing a potential diagnostic and/or therapeutic target for patients with coronary endothelial function. PMID:23220334

  10. Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

    PubMed

    Marcińska, Magdalena; Pośpiech, Ewelina; Abidi, Sarah; Andersen, Jeppe Dyrberg; van den Berge, Margreet; Carracedo, Ángel; Eduardoff, Mayra; Marczakiewicz-Lustig, Anna; Morling, Niels; Sijen, Titia; Skowron, Małgorzata; Söchtig, Jens; Syndercombe-Court, Denise; Weiler, Natalie; Schneider, Peter M; Ballard, David; Børsting, Claus; Parson, Walther; Phillips, Chris; Branicki, Wojciech

    2015-01-01

    Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

  11. Evaluation of DNA Variants Associated with Androgenetic Alopecia and Their Potential to Predict Male Pattern Baldness

    PubMed Central

    Marcińska, Magdalena; Pośpiech, Ewelina; Abidi, Sarah; Andersen, Jeppe Dyrberg; van den Berge, Margreet; Carracedo, Ángel; Eduardoff, Mayra; Marczakiewicz-Lustig, Anna; Morling, Niels; Sijen, Titia; Skowron, Małgorzata; Söchtig, Jens; Syndercombe-Court, Denise; Weiler, Natalie; Schneider, Peter M.; Ballard, David; Børsting, Claus; Parson, Walther; Phillips, Chris; Branicki, Wojciech

    2015-01-01

    Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics. PMID:26001114

  12. Functional disability of adults in Brazil: prevalence and